THE INTERPLAY OF INCIDENTAL EXPOSURE, AFFECT, AND INDIVIDUAL
DIFFERENCES IN L2 ACQUISITION
By
Zachary Forrest Miller

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Second Language Studies—Doctor of Philosophy
2017

ABSTRACT
THE INTERPLAY OF INCIDENTAL EXPOSURE, AFFECT, AND INDIVIDUAL
DIFFERENCES IN L2 ACQUISITION
By
Zachary Forrest Miller
The role of hot cognition, or cognitive processing influenced by emotions, on second
language (L2) learning is relatively understudied (Dörnyei, 2009; MacIntyre, 2002; Swain,
2013). The present research investigated how positive, negative, and neutral mood states
influence aspects of second language acquisition (SLA), as well as potentially moderate the
relationship between certain personality characteristics (i.e., openness, intuition, emotional
intelligence, foreign language anxiety, and impulsivity) and L2 performance. After completing
individual differences questionnaires, participants were divided into either a Comparison group
or one of three emotionally induced treatment groups and subsequently exposed to a
semiartificial language under incidental learning conditions. Immediate and two-week delayed
testing measured grammatical accuracy of the target syntactic forms, while source attribution
data and retrospective verbal reports gauged what types of knowledge (implicit, explicit, or a
combination of both) were acquired by participants. Results suggest that positive emotions are
the most beneficial to L2 learning. Although effects were small, negative mood states appeared
to hinder the ability for long-term L2 retention. Findings also revealed that knowledge gains
were chiefly guided by explicit means. Lastly, results demonstrated that the affective stimuli
played a moderating role in the relationship between immediate L2 performance and the traits of
intellect, stress management, premeditation, perseverance. This study contributes to SLA
literature regarding emotions and their impact on L2 learning and individual differences.

Copyright by
ZACHARY FORREST MILLER
2017

ACKNOWLEDGMENTS

I want to thank my supervisor, Aline Godfroid, for her mentorship and guidance
throughout this challenging, yet fully rewarding dissertation process. Her insights and helpful
discussions have kept me on track and laser-focused. I also want to recognize Paula Winke,
Shawn Loewen, and Jason Moser for their invaluable input and direction in shaping this final
project.
To the faculty and fellow students of the Second Language Studies Program at Michigan
State University—thanks for making my time as a PhD student extremely enjoyable. I have
learned a lot over the years and, more importantly, developed wonderful friendships in the
process.
Finally, I am grateful to my wife, Jung Lae, and my family for their continuous love and
support. Thanks for gently nudging me towards the finish line.

iv

TABLE OF CONTENTS

LIST OF TABLES ....................................................................................................................... viii
LIST OF FIGURES ....................................................................................................................... xi
CHAPTER 1 ................................................................................................................................... 1
REVIEW OF THE LITERATURE ................................................................................................ 1
1.1 Introduction ........................................................................................................................... 1
1.2 What is Hot Cognition? ........................................................................................................ 2
1.3 Hot Cognition, Emotions, and Learning ............................................................................... 3
1.4 Hot Cognition and SLA ........................................................................................................ 6
1.5 Pilot Study............................................................................................................................. 9
1.6 Incidental Learning Conditions and SLA ........................................................................... 11
1.7 Emotions and Implicit Learning ......................................................................................... 15
1.8 Implicit Learning and Individual Differences .................................................................... 17
CHAPTER 2 ................................................................................................................................. 20
CURRENT STUDY...................................................................................................................... 20
2.1 Present Study ...................................................................................................................... 20
2.2 Participants.......................................................................................................................... 20
2.3 Materials ............................................................................................................................. 21
2.3.1 Definitions of Terminology ......................................................................................... 21
2.3.2 Incidental Exposure and Testing Sentences ................................................................. 22
2.3.2.1 Exposure Set ......................................................................................................... 23
2.3.2.2 Testing Set ............................................................................................................ 24
2.3.3 Emotional Stimuli ........................................................................................................ 25
2.3.3.1 Emotional Movie Database (EMDB).................................................................... 26
2.3.3.2 International Affective Picture System (IAPS)..................................................... 27
2.3.4 Subjective Affective Ratings ....................................................................................... 28
2.3.5 Personality Questionnaires ........................................................................................... 28
2.3.5.1 Big Five Aspect Scale (BFAS) ............................................................................. 29
2.3.5.2 Rational Experiential Inventory (REI) .................................................................. 29
2.3.5.3 Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF) ................ 30
2.3.5.4 Foreign Language Classroom Anxiety Scale (FLCAS)........................................ 30
2.3.5.5 UPPS Impulsivity Behavior Scale ........................................................................ 30
2.4 Procedure ............................................................................................................................ 31
2.4.1 The Five Phases of the Procedure ................................................................................ 31
2.4.1.1 Phase 1, Pre-experimental Measures .................................................................... 32
2.4.1.2 Phase 2, Initial Emotional Induction ..................................................................... 33
2.4.1.3 Phase 3, Incidental Exposure and Secondary Emotional Induction ..................... 34
2.4.1.4 Phase 4, Immediate GJT ....................................................................................... 35
2.4.1.5 Phase 5, Delayed GJT and Debriefing Interview.................................................. 36
2.5 Analysis .............................................................................................................................. 37

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2.5.1 Analysis of Emotional Induction ................................................................................. 37
2.5.2 Analysis of RQ1 ........................................................................................................... 37
2.5.3 Analysis of RQ2 ........................................................................................................... 39
2.5.4 Analysis of RQ3 ........................................................................................................... 40
CHAPTER 3 ................................................................................................................................. 42
RESULTS ..................................................................................................................................... 42
3.1 Emotional Induction ........................................................................................................... 42
3.1.1 Valence ........................................................................................................................ 42
3.1.2 Arousal ......................................................................................................................... 45
3.1.3 Qualitative Data ........................................................................................................... 47
3.1.3.1 Positive Group ...................................................................................................... 48
3.1.3.2 Negative Group ..................................................................................................... 48
3.1.3.3 Neutral Group ....................................................................................................... 49
3.2 The Role of Emotion in the Learning and Retention of an L2 Syntax ............................... 49
3.2.1 Exposure Phase ............................................................................................................ 50
3.2.1.1 Elicited Imitations ................................................................................................. 50
3.2.1.2 Plausibility Judgments .......................................................................................... 55
3.2.2 Testing Phase ............................................................................................................... 56
3.2.2.1 Overall Performance, Immediate Grammaticality Judgments .............................. 56
3.2.2.2 Overall Performance, Delayed Grammaticality Judgments.................................. 62
3.2.2.3 Relationship between the Immediate and Delayed GJT Performances ............... 67
3.2.3 Summary of RQ1 ......................................................................................................... 68
3.3 Emotions and the Implicit Acquisition of an L2 Syntax .................................................... 70
3.3.1 Proportions and Accuracies of Source Attributions, Immediate Posttest .................... 70
3.3.2 Proportions and Accuracies of Source Attributions, Delayed Posttest ........................ 74
3.3.3 Verbal Reports ............................................................................................................. 77
3.4 Emotions and the Relationship between Individual Differences and L2 Learning ............ 79
3.4.1 Exploratory Factor Analysis ........................................................................................ 79
3.4.2 Muliple Linear Regression and Moderation Analysis ................................................. 81
3.4.3 Analyses of Significant Interactions ............................................................................ 87
3.5 General Summary of the Results ........................................................................................ 94
CHAPTER 4 ................................................................................................................................. 97
DISCUSSION ............................................................................................................................... 97
4.1 The Effectiveness of Emotional Induction ......................................................................... 98
4.2 Emotional Induction on Learning and Retaining L2 Syntax .............................................. 99
4.3 Emotional Induction and Implicit Knowledge Acquisition .............................................. 104
4.4 Mood States and the Interconnection of Individual Differences and L2 Learning .......... 108
CHAPTER 5 ............................................................................................................................... 113
CONCLUSION ........................................................................................................................... 113
5.1 Summary of the Findings .................................................................................................. 113
5.2 Implications of the Findings ............................................................................................. 115
5.3 Limitations and Future Research ...................................................................................... 117

vi

APPENDICES ............................................................................................................................ 120
APPENDIX A: Sentences from the Exposure Set .................................................................. 121
APPENDIX B: Testing Sentences .......................................................................................... 128
APPENDIX C: Debriefing Interview Questions .................................................................... 133
APPENDIX D: Film Clips and Images, Initial Emotional Induction ..................................... 134
APPENDIX E: Images, Exposure Phase ................................................................................ 138
APPENDIX F: Film Clips and Images, Secondary Emotional Induction .............................. 141
APPENDIX G: Self-Assessment Manikins ............................................................................ 145
APPENDIX H: Written Background Questionnaire .............................................................. 146
APPENDIX I: Verbal Reports ................................................................................................ 147
APPENDIX J: Impacts from Film Clips and Images ............................................................. 159
APPENDIX K: Exploratory Factor Analysis Structure Matrices ........................................... 167
REFERENCES ........................................................................................................................... 173

vii

LIST OF TABLES

Table 1 Definition of Terms ......................................................................................................... 12
Table 2 Definition and Operationalization of Key Terminology.................................................. 21
Table 3 Descriptions and Examples of the Three Verb Placement Rules .................................... 22
Table 4 Syntactic Templates for the Three Verb Placement Rules in the Exposure Set .............. 24
Table 5 Syntactic Templates for All Verb Placement Rules in the Testing Set ........................... 25
Table 6 Guidelines for Source Attribution Ratings of Test Item Grammaticality ........................ 36
Table 7 Descriptive Statistics and Results of Friedman’s Testing for Valence Ratings .............. 43
Table 8 Results of Wilcoxon Signed-Ranks Testing between Valence Ratings .......................... 45
Table 9 Descriptive Statistics and Results of Friedman’s Testing for Arousal Ratings ............... 46
Table 10 Results of Wilcoxon Signed-Ranks Testing between Arousal Ratings ......................... 47
Table 11 Descriptive Statistics for Elicited Imitations ................................................................. 50
Table 12 Descriptive Statistics for Plausibility Judgements ......................................................... 56
Table 13 Grammaticality Judgement Accuracies, Immediate Posttest ......................................... 57
Table 14 D Prime Scores for Grammaticality Judgement Task, Immediate Posttest ................... 59
Table 15 Descriptive Statistics and Accuracy of Verb Pattern Endorsement Ratings,
Immediate Posttest ......................................................................................................... 61
Table 16 Grammaticality Judgement Accuracies, Delayed Posttest ........................................... 63
Table 17 D Prime Scores for Grammaticality Judgement Task, Delayed Posttest ....................... 64
Table 18 Descriptive Statistics and Accuracy of Verb Pattern Endorsement Ratings,
Delayed Posttest ............................................................................................................. 66
Table 19 Summary of Findings for RQ1 ...................................................................................... 69
Table 20 Grammaticality Judgment Accuracies per Source Attribution, Immediate Posttest ..... 72
Table 21 Explicit Source Attribution Use by Verb Pattern, Immediate Posttest .......................... 73
viii

Table 22 Explicit Source Attribution Use by Verb Pattern, Delayed Posttest.............................. 75
Table 23 Grammaticality Judgment Accuracies per Source Attribution, Delayed Posttest ......... 77
Table 24 Summary of Exploratory Factor Analysis ..................................................................... 80
Table 25 Correlations between Factors and Immediate GJT Accuracy for Each Group.............. 83
Table 26 Linear Model of Predictors of Immediate Grammaticality Judgment Accuracy........... 86
Table 27 Correlations of Intellect with Explicit Source Attribution Proportion and Accuracy
by Group ........................................................................................................................ 89
Table 28 Correlations of Stress Management with Implicit Source Attribution Proportion
and Accuracy by Group ................................................................................................. 91
Table 29 Correlations of Premeditation and (Lack of) Perseverance with Implicit Source
Attribution Proportion and Accuracy by Group ............................................................ 94
Table D1 Practice Film Clip for Each Group, Initial Induction ................................................. 134
Table D2 Practice Images for Each Group, Initial Induction ..................................................... 134
Table D3 Positive Group Film Clips, Initial Induction .............................................................. 134
Table D4 Positive Group Images, Initial Induction .................................................................... 135
Table D5 Negative Group Film Clips, Initial Induction ............................................................. 135
Table D6 Negative Group Images, Initial Induction .................................................................. 136
Table D7 Neutral Group Film Clips, Initial Induction ............................................................... 136
Table D8 Neutral Group Images, Initial Induction ..................................................................... 137
Table E1 Positive Group Images, Exposure Phase ..................................................................... 138
Table E2 Negative Group Images, Exposure Phase ................................................................... 139
Table E3 Neutral Group Images, Exposure Phase ...................................................................... 140
Table F1 Positive Group Film Clips, Secondary Induction ........................................................ 141
Table F2 Positive Group Images, Secondary Induction ............................................................. 142
Table F3 Negative Group Film Clips, Secondary Induction ...................................................... 142

ix

Table F4 Negative Group Images, Secondary Induction ............................................................ 143
Table F5 Neutral Group Film Clips, Secondary Induction ......................................................... 143
Table F6 Neutral Group Images, Secondary Induction .............................................................. 144
Table I1 Noticed Verb Patters or Grammatical Regularities, Comparison Group ..................... 147
Table I2 Noticed Verb Patterns or Grammatical Regularities, Positive Group .......................... 150
Table I3 Noticed Verb Patterns or Grammatical Regularities, Negative Group ........................ 153
Table I4 Noticed Verb Patterns or Grammatical Regularities, Neutral Group ........................... 156
Table J1 Impacts from Film Clips and Images, Positive Group ................................................. 159
Table J2 Impacts from Film Clips and Images, Negative Group ............................................... 162
Table J3 Impacts from Film Clips and Images, Neutral Group .................................................. 165
Table K1 Summary of Exploratory Factor Analysis Results for the BFAS Questionnaire
(N = 120) .................................................................................................................... 167
Table K2 Summary of Exploratory Factor Analysis Results for the REI Questionnaire
(N = 120) .................................................................................................................... 168
Table K3 Summary of Exploratory Factor Analysis Results for the TEIQue-SF
Questionnaire (N = 120) ............................................................................................. 169
Table K4 Summary of Exploratory Factor Analysis Results for the FLCAS Questionnaire
(N = 120) .................................................................................................................... 170
Table K5 Summary of Exploratory Factor Analysis Results for the UPPS Questionnaire
(N = 120) .................................................................................................................... 171

x

LIST OF FIGURES

Figure 1. The graphic representation of the current study’s procedure ........................................ 32
Figure 2. Diagram of the initial emotional induction format ........................................................ 33
Figure 3. Incidental exposure for the positive, negative, and neutral treatment groups ............... 35
Figure 4. Valence ratings for each group over the course of the experiment ............................... 43
Figure 5. Arousal ratings for each group over the length of the experiment ................................ 46
Figure 6. Repetition accuracy of the correct verb forms for all 120 sentences from the
exposure set across 24 chronological stages .................................................................. 52
Figure 7. Repetition accuracy of the V2 verb pattern for all 40 sentences from the
exposure set across 20 chronological stages .................................................................. 53
Figure 8. Repetition accuracy of the VF-V1 verb pattern for all 40 sentences from the
exposure set across 20 chronological stages .................................................................. 54
Figure 9. Repetition accuracy of the V2-VF verb pattern for all 40 sentences from the
exposure set across 20 chronological stages .................................................................. 55
Figure 10. Grammaticality judgement accuracy for all 60 testing sentences across 10
chronological stages .................................................................................................... 58
Figure 11. The d prime scores from the immediate grammaticality judgement posttest,
with zero representing chance discrimination............................................................. 59
Figure 12. Endorsement ratings for each verb pattern from the immediate GJT ......................... 61
Figure 13. The d prime scores from the delayed grammaticality judgement posttest,
with zero representing chance discrimination............................................................. 64
Figure 14. Endorsement ratings for each verb pattern from the delayed GJT .............................. 66
Figure 15. Scatterplot of correlations between immediate and delayed GJT performance
by group ...................................................................................................................... 68
Figure 16. Proportion of selected source attributions from the immediate GJT ........................... 71
Figure 17. Proportion of selected source attributions from the delayed GJT ............................... 75

xi

Figure 18. The four categories of verbal reports as described in the retrospective verbal
reports ......................................................................................................................... 79
Figure 19. Scatter plots, by factor, with the largest interactions between a treatment group
and the Comparison group .......................................................................................... 84
Figure 20. Immediate posttest performance by group based upon intellect levels ....................... 88
Figure 21. Immediate posttest performance by group based upon stress management levels ..... 90
Figure 22. Immediate posttest performance by group based upon premeditation levels.............. 92
Figure 23. Immediate posttest performance by group based upon (lack of) perseverance
levels ........................................................................................................................... 93
Figure G1. SAM ratings for valence and arousal ....................................................................... 145

xii

CHAPTER 1
REVIEW OF THE LITERATURE
1.1 Introduction
The role of hot cognitive influencers, such as emotions, on second language (L2) learning
is a wholly recognized, yet an understudied phenomenon in the field of second language
acquisition (SLA) (Dörnyei, 2009; MacIntyre, 2002; Swain, 2013). While many researchers
know that emotions impact complex cognitive abilities (Storbeck & Maswood, 2015; Yang,
Yang, & Isen, 2013) and learning (MacIntyre & Gregersen, 2012; Pekrun, 2014), studies
measuring how affect influences L2 acquisition are limited. This is particularly true in the area
of implicit L2 learning research, where the role of individual differences is ripe for further
exploration (Andringa & Rebuschat, 2015). For the present dissertation, I investigated how
positive, negative, and neutral emotions affected the learning and retention of an L2 syntax under
incidental conditions. I also examined whether incidental exposure facilitated the acquisition of
the target grammatical structure implicitly. Finally, I explored the relationships between
individual differences (i.e., personality characteristics) and incidental task performance in both
neutral and emotionally loaded settings. With this empirical work, I hope to lay a solid
foundation on which additional inquiry into the function of affect and SLA may be built.
This dissertation is divided into five different chapters. The current chapter examines the
literature from recent studies on the following areas: (a) emotions and adult education, (b)
incidental learning conditions in SLA, (c) the role of emotions in implicit learning, and (d) the
relationship between individual differences and implicit learning. In Chapter 2, I provide the
research questions along with the methodological design of the study. I offer the results of my
study in Chapter 3, and later discuss these findings in greater detail within Chapter 4. Lastly, in

1

Chapter 5, I address the pedagogical implications, limitations, and future research directions
based upon my conclusions.
1.2 What is Hot Cognition?
Within the last fifty years, cognitive scientists have decidedly analogized mental
processing with temperature scales: that is, cold versus hot. Cold cognitive processing, as
described by Solomon (2001), focuses on the pursuit of information from a rational perspective,
devoid of emotional influencers. Hot cognition, a term originating in the mid-1960s (Abelson,
1963), is succinctly defined as cognition colored by feeling (Brand, 1987). With this new
definition, researchers attempted to wed cognitive functioning with more humanistic traits, such
as feelings, desire, moods, and self-interest (Solomon, 2001). Emotions and cognition are
generally thought of as interwoven entities (Barrett, 2009; D’Mello & Graesser, 2012; Dörner &
Güss, 2013; Dörnyei, 2009; Lazarus, 1999) because human cognitive functioning rarely occurs
in a neutral state. Basic examples include selecting a meal, voting for a candidate, or falling in
love.
The influences of hot cognition have been studied and discussed across different domains
of both cognitive (Corr, 2013; Madrigal, 2008; Thagard & Kroon, 2006; Unsworth, Heitz, &
Engle, 2005; Worrell, 2014) and social (Lodge & Taber, 2005; Simon, Stenstrom, & Read, 2015;
Simpson & Marshall, 2010; Wyatt et al., 1993) sciences. In one study, Lodge and Taber (2005)
conducted a series of experiments using lexical priming to test whether hot cognition served as
the foundation for motivated reasoning during sociopolitical activities. Results indicated that
participants developed automatic links between political concepts (i.e., leaders, groups, and
symbols) and positive or negative affect. In another study, Wyatt et al. (1993) discovered from
verbal protocols that social scientists evaluated professional-level journal articles via partially

2

hot cognitive processing. The researchers suggested that in certain instances, reading charged
with stronger reactions often occurred during interpretive-evaluations of the text. Cold cognition
accounted for the remaining literal processing of the articles.
Thagard and Kroon (2006) demonstrated that even scientific thinking, normally
associated with cold cognition, is influenced by feelings. The two researchers identified, coded,
and analyzed the amount of emotional words used by scientists James Watson and Francis Crick,
who discovered the DNA molecule’s structure and its role in the operations of genes, during the
time of their discovery. Using the text of Watson’s 1969 short book The Double Helix that
described the two scientists’ work and discussion, Thagard and Kroon identified 235 emotional
words as possessing either a positive (happiness) or negative (sadness) valence. While the
researchers did admit that the author’s emotional self-reports may not have been entirely
psychologically accurate, the text nonetheless provided a rich example of the association
between scientific thinking and emotional states.
1.3 Hot Cognition, Emotions, and Learning
The influence of emotions on learning has received much attention in the fields of
neuroscience (Viinikainen et al., 2012; Wolfe, 2006; Zull, 2006) and cognitive psychology
(Barrett, 2009; Dörner & Güss, 2013; Pekrun, 2006; Ranellucci, Hall, & Goetz, 2015). From a
physical standpoint, human emotion is regulated by two small glands located in the brain, which
are called the amygdala and which release adrenaline during heightened affective states,
producing a memory imprint of the experience (Wolfe, 2006). The amygdala stimulates affective
attention, or prioritized sensory processing for emotional stimuli over neutral items (Pessoa,
2010; Uusberg, Uibo, Kreegipuu, & Allik, 2013). In turn, whether the feeling impacts an
individual’s well-being will be reflected in an approach towards, or avoidance of, the stimuli

3

(Shanahan, 2008). With respect to learning, emotions facilitate the quality and strength of neural
traces, influencing a person’s ability to accurately recall what has been experienced (Dörnyei,
2009; Rager, 2009). Simply put, “emotion drives attention, which drives learning, memory, and
problem-solving behavior” (Weiss, 2000, p. 46). How specific emotions influence this process,
however, is still a matter of debate.
In general, the activation of positive emotions is seen to motivate learning (Arnold, 2011;
MacIntyre & Gregersen, 2012; Pekrun, 2006), as well as promote creative learning strategies
(Isen, 2000) and enhance cognitive functioning (Storbeck & Maswood, 2015; Yang et al., 2013).
Negative emotions, on the other hand, disrupt the learning process and hinder information
retention (Elnicki, 2010; MacIntyre & Gregersen, 2012; Pekrun, Goetz, Frenzel, Barchfeld, &
Perry, 2011; Shang, Fu, Dienes, Shao, & Fu, 2013) and cognitive processing (Curci, Lanciano,
Soleti, & Rimé, 2013). Within the context of general education, research has shown that
different achievement emotions, or emotions tied to achievement outcomes in the classroom
(Pekrun, 2006), impact student performance in a variety of manners (Goetz, Frenzel, Hall, &
Pekrun, 2008; Lichtenfeld, Pekrun, Stupinsky, Reiss, & Murayama, 2012; Linnenbrink-Garcia &
Pekrun, 2011; Luo et al., 2014; Pekrun, Goetz, Titz, & Perry, 2002; Pekrun et al., 2011). For
example, while using an instrument to measure achievement emotions, Pekrun et al. (2011)
discovered relationships between specific emotions and both academic learning and performance
in a large number of Canadian undergraduate students (N = 389). The researchers found positive
correlations between students’ grade point averages and learning variables such as positive,
activating emotions (enjoyment, hope, and pride). Conversely, negative, deactivating emotions
(hopelessness and boredom) and negative, activating emotions (anger, anxiety, and shame)
correlated negatively in the same areas. In the field of SLA, MacIntyre and Gregersen (2012)

4

argued that positive emotions tended to broaden students’ perspectives (positive-broadening),
facilitating L2 absorption within the classroom setting. Conversely, they viewed negative
emotions as more restrictive in nature (negative-narrowing), impeding cognition and limiting
input reception.
To be sure, the compartmentalization of positive emotions as “good” and negative
emotions as “bad” for students in the classroom is not always a given (see Pekrun et al., 2002;
Pekrun, 2014). Wolfe (2006), for instance, viewed emotions as a “double-edged sword” (p.40)
that could benefit or hinder academic performance based on the individual or context. Pekrun
(2014) admitted that positive emotions may pose a detriment to learning if they distracted
students’ attention away from classroom tasks or homework assignments. Excitement over a
sporting event or falling in love are examples of positive emotions brought into the classroom
that may serve to encumber an individual’s learning potential. Pekrun also stated that negative
emotions may be harnessed to increase classroom productivity under certain circumstances.
Anxiety, self-related anger, and shame, in lower intensities, may promote learning if students are
at least confident in their ability to succeed with the course material. Such inconsistencies reveal
that the precise role of emotions in learning is still not clear and may impact individuals in
different ways.
Related to Pekrun’s (2006, 2014) findings, Pessoa (2009) introduced the dual competition
framework to explain how certain emotions could enhance or hinder cognitive processing
depending upon their relative intensity. His framework posited a mutual interaction between
neurological executive systems and affect during behavior performance. For example, higharousal emotional items, either positive or negative (e.g., erotic imagery or fear of shock), divert
mental processing efforts toward the arousing stimuli and away from task execution. Low-threat

5

stimuli, on the other hand, improve task performance by enhancing target processing. Thus, the
influence of emotions on behavioral performance relies primarily on the intensity of the
emotional information (Pessoa, Padmala, Kenzer, & Bauer, 2012). Pessoa et al. (2012) validated
components of the dual competition framework by testing two separate groups using stop-signal
tasks paired with varying affective stimuli. The first group (N = 36), who were exposed to mild
stop-signals (happy and fearful faces), enhanced their response inhibition time relative to the
neutral stimuli (neutral faces). The opposite held true for the second group (N = 22), which
recorded impaired inhibition responses with higher-threat emotional stop-signals (threat of a
mild shock). The researchers did not test high arousing, positive stimuli in the experiment.
Whether or not the dual competition framework applies to complex learning tasks (for the
purposes of this study, L2 acquisition) remains to be investigated.
1.4 Hot Cognition and SLA
For decades, the relevance of emotions and their impact on SLA has been recognized
within the field of L2 studies (Crookes & Schmidt, 1991; MacIntyre, 2002; Schumann, 1994;
Swain, 2013). However, specific research in this area has been limited and “emotions have, in
general, been neglected in SLA literature” (Swain, 2013, p. 195). Typically, inquiry into affect
and L2 acquisition has been relegated into one of three categories: (a) foreign language anxiety,
(b) acquisition of emotional vocabulary, and (c) the role of affect within the L2 classroom. The
following provides a brief overview of each focus.
With respect to “primary” emotions (e.g., joy, interest, sadness; see Reeve, 1997),
MacIntyre (2002) observed that, “the only emotion…to be studied in detail in the language
learning area is anxiety, a variant of fear” (p. 64). Foreign language anxiety (FLA), as defined
by Horwitz, Horwitz, and Cope (1986), reflects a type of situation-specific anxiety caused by

6

negative reactions to L2 learning. Horwitz et al. developed a popular instrument for measuring
FLA in students, (appropriately) named the Foreign Language Classroom Anxiety Scale (see
Section 2.3.4.4 of this paper for more details). The phenomenon has been discussed at great
lengths within the realm of SLA and is generally perceived to hinder L2 acquisition efforts
(Horwitz et al., 1986; Horwitz, 2001; MacIntyre & Gardner, 1989, 1994). Over the past ten
years, researchers have analyzed FLA in a variety of foreign language learning contexts, such as
corrective feedback (Rassaei, 2015; Sheen, 2008) and willingness to communicate (BaranŁucarz, 2014; Liu & Jackson, 2008; MacIntyre, 2007). Different population samples, from adult
(Lim, 2009; Zhao, Dynia, & Guo, 2013) to child (Sparks & Ganschow, 2007; Sparks & Patton,
2013) learners, have also been studied to measure age-related effects. While FLA is indeed an
affective component of L2 learning (MacIntyre, 2002), it only represents one specific emotion
that students may experience in the classroom.
Another area of emotion-related research is the mental representation of emotional lexical
items in bilinguals and L2 learners (Caldwell-Harris, Tong, Lung, & Poo, 2010; Eilola, Havelka,
& Sharma, 2007; Ferré et al., 2010; Pavlenko & Driagina, 2007). Affective lexis normally
examined in this line of inquiry includes taboo and swearwords, insults, reprimands,
endearments, and aversions (see Pavlenko, 2008). Generally speaking, an individual’s L1 is
viewed as more emotional than subsequent languages learned (Dewaele, 2004). In this case, age
of LX acquisition matters, as earlier bilinguals appear to affectively process language to greater
depths than later bilinguals or foreign language learners (Pavlenko, 2012). For example, Sutton,
Altarriba, Gianico, and Basnight-Brown (2007) utilized a Stroop task to measure the interference
effect of L1 and L2 emotional words on early Spanish-English bilinguals. The researchers found
that participants experienced equal interference with the emotional stimuli from both languages,

7

suggesting a shared affective processing rate with the lexical items. Conversely, Winskel (2013)
showed that late Thai-English bilinguals responded less strongly to the emotional arousal of L2
words than L1 words. She used both Stroop and emotionality-rating tasks to measure results.
Recent findings from Ponari, Rodríguez-Cuadrado, Vinson, Fox, Costa, & Vigliocco (2015),
however, have chipped away at this current paradigm. Their study of 156 English as a Second
Language (ESL) learners revealed processing rates of emotional words in lexical decision tasks
that were similar to their native English-speaking counterparts, regardless of L1 or age of
acquisition. In the face of such processing discrepancies, researchers continue to explore and
discern the mental effects of emotional lexicon in the L1 and target language.
The emotional interplay between L2 learning and teaching within the classroom rounds
out the final branch of affect research in SLA. Researchers (Aragão, 2011; Brown & White,
2010; Johnson & Golombek, 2003; Golombek, 2015) have looked at how teachers and students
reflect on and regulate emotions within the L2 classroom from a pedagogical standpoint.
Researchers generally discovered that strong, negative emotions detract from the overall
acquisition process (Arnold, 2011; Brown & White, 2010; MacIntyre & Gregersen, 2012). Some
have identified a need for emotional awareness at the instructor level to facilitate learning and
encourage positive student-teacher relationships (Cao, 2011; Horwitz, 1995; MacIntyre &
Gregersen, 2012). Arnold (2011), for example, suggested that language instructors be concerned
with their students’, as well as their own, affective side to promote L2 development and
assessment. The aforementioned studies, however, primarily focused on specific emotions
generated within the context of the L2 classroom, such as fear and anxiety, which are
subsequently related back to FLA (Horwitz et al., 1986; MacIntyre, 2002) or L2 motivation
(Dörnyei, 2009; Papi, 2010). This leaves the role of positive emotions largely unexplored.

8

1.5 Pilot Study
In the current study, I build on my earlier collaborative research measuring the effects of
hot cognition on explicit, L2 vocabulary acquisition (Miller, Fox, Moser, & Godfroid, under
review). During this preliminary examination, two groups of thirty-five adult language learners
acquired 24 novel, lexical items, in either a neutral or negative emotional state.1 Stimuli used to
induce emotionality derived from film clips known to elicit affective responses as measured on a
9-point Likert scale (1 = low valence, 5 = neutral, 9 = high valence) (from Carvalho, Leite,
Galdo-Álvarez, & Gonçalves, 2012). The neutral group viewed six, 40-second scenery clips that
measured mid-range valence (M = 5.77) and low arousal (M = 2.74) on self-reports. The
negative group watched six horror clips known to produce low valence (M = 1.85) and high
arousal (M = 7.25). Film exposure was 240 seconds for each group. Self-Assessment Manikins
(SAMs), measured on a 9-point Likert scale, were used at various points in the study to capture
the individuals’ subjective emotional states.
Immediately following emotional induction, participants from both treatment groups
participated in paired-associates, vocabulary learning. Participants viewed on a computer screen
an Indonesian word, its English translation, and a pictorial representation (from Szekely et al.,
2004) for eight seconds. Presentation of all 24 items as such constituted one complete block.
Participants watched three blocks, each presented in a random order, for a total exposure time of
24 seconds per item. After the lexical training phase, three types of immediate and delayed
posttests (48 hours later) recorded individual lexical performance. The tests included a (a) free

1

The Miller et al. (under review) study also measured two additional components: (a) the effects
of emotional induction on working memory and (b) the relationship between vocabulary
acquisition and working memory within an emotional state. The results of these measures are
not discussed here, as working memory is not a focus within the current study’s design. As such,
only the vocabulary acquisition portion of the Miller et al. study is examined.
9

recall (provide any English or Indonesian words remembered), (b) L1 to L2 recall (given the
English word, provide the Indonesian equivalent), and (c) L2 to L1 recall (given the Indonesian
word, provide the English word).
Examination of SAM data points for valence (from sad/unpleasant to happy/pleasant)
pre and post film clips indicated successful emotional induction for participants in both treatment
groups. Analysis of vocabulary scores from all three measures revealed that the negative group
learned fewer words than the neutral group. However, significant and near-significant group
differences only occurred during activities that involved L1 pairing or retrieval (i.e., L1 to L2
recall, L2 to L1 recall, and free recall of English words). This effect did not manifest when
participants were asked to provide the L2 items (i.e., free recall of Indonesian words). The
researchers speculated that disembodied cognition, or the inability of learners to assign affective
status to newly acquired L2 forms, explained the disparity of group performance (see Pavlenko,
2005). Instead, participants suppressed L1 retrieval by projecting negative emotionality onto
their native language, which is more susceptible to affective reactivity. From an SLA
perspective, the findings revealed that negative emotional states can encumber students’ abilities
to establish L2-L1 form-meaning by disrupting L1 semantic activation.
Based upon this pilot study, I identified two areas for further inquiry with respect to
emotions and SLA. First, more intense and persistent emotional inductions were likely needed to
impact cognitive functioning in a laboratory setting. As such, a sustained exposure to hot
cognitive influencers before, during, and after the L2 training phase should (a) better mirror L2
learners’ persistent emotional states throughout an assessment period or classroom environment
and therefore, (b) provide a more accurate picture of the role of emotions in learning. Second, I
wanted to extend the examination of hot cognitive effects to incidental learning conditions,

10

where unconscious processing might occur. As evidenced from the pilot study, emotions can
interfere with conscious L2 processing (through explicit instruction). Whether these findings
hold true in the development of implicit L2 knowledge is yet to be determined. A logical
progression extends this investigation to SLA on an unconscious level to understand what role, if
any, emotions play on the type of learning.
1.6 Incidental Learning Conditions and SLA
Within SLA research, the use of training tasks that create incidental learning conditions
has provided a window into unconscious L2 processing (Ender, 2014; Rebuschat & Williams,
2012). Simply stated, incidental learning is learning without intent (Rogers, Révész, &
Rebuschat, 2015). In the context of L2 acquisition, Hulstijn (2013) informally described this
process as, “‘picking up’ an unknown word [or expression] from listening to someone or from
reading a text” (p. 2632), absent the conscious effort to do so. This type of learning process is in
direct contrast with intentional learning, which involves a deliberate attempt to learn or
memorize target material (Gass, Behney, & Plonsky, 2013; Hulstijn, 2003; Rogers et al., 2015).
Examples of intentional learning include the application of mnemonic devices or other types of
rehearsal techniques (Hulstijn, 2003, 2013).
Methodologically speaking, incidental learning is a type of learning condition. Within L2
experimental designs, incidental learning has been operationalized in training tasks so that,
“subjects should not know that they are going to be tested, nor should they be informed about the
nature of the rule system” (Rebuschat, 2013, p. 615; see also Hulstijn, 2003; Williams, 2009).
According to Rogers et al. (2015), researchers interested in facilitating incidental learning often
devise a, “‘cover story’ or task in their training conditions that is designed to orient participants’
attention on the meaning of the input, rather than toward the grammatical features that will later

11

be tested” (p. 782). Recent studies have successfully employed this exact design, for example, to
examine the acquisition of L2 syntax under incidental learning conditions (see Godfroid, 2015;
Grey, Williams, & Rebuschat, 2014; Rebuschat & Williams, 2012).
It is important to note that incidental learning is not a particular type of cognitive process.
Rather, it is learning that takes place under meaning-focused conditions. The terms implicit
learning and explicit learning, instead, refer to the underlying cognitive processes that foment
the acquisition of knowledge (Hulstijn, 2007). Ender (2014) noted that incidental learning can
be the result of either implicit or explicit processes, or both. In this regard, incidental learning
conditions can function as a conduit for one or both processing types to transpire. Subsequently,
the type of knowledge acquired would largely depend upon which processes were activated. For
the student involved in an incidental learning task, then, any implicit learning would likely result
in implicit knowledge of the target L2 structure. Likewise, explicit learning would facilitate the
formation of explicit knowledge (see Hulstijn, 2007). Table 1 provides the definition of terms
used thus far in this section.
Table 1
Definition of Terms
Term
Incidental learning
Intentional learning
Implicit learning
Implicit knowledge
Explicit learning
Explicit knowledge

Definition
Learning that occurs without intent (Rogers et al., 2015); principally a
methodological condition in L2 experimental design.
Learning that involves a deliberate attempt to acquire or memorize
target material (Hulstijn, 2003).
Acquisition that occurs without awareness or intent to learn
(Rebuschat, 2013).
Knowledge that is unconscious, procedural, and intuitive (Loewen,
2015; Zhang, 2015).
Acquisition that involves a specific search for structure (Gass et al.,
2013).
Knowledge that involves awareness and can be accessed consciously
(Loewen, 2015).

12

To gauge what specific types of learning occurred (and subsequently, what types of
knowledge are acquired) during incidental learning conditions, SLA researchers have
successfully employed two distinct measurements: retrospective verbal reports and subjective
sources attributions (Godfroid, 2015; Grey et al., 2014; Rebuschat & Williams, 2012).
Retrospective verbal reports, acquired at the study’s completion, measure whether participants
have gained implicit or explicit knowledge based upon their ability to verbalize any rules that
were noticed during the experiment. According to Rebuschat (2013), the presence of
unconscious knowledge lies at the intersection of a positive training effect (e.g., above-chance
performance on follow-up tasks) and an inability to articulate any knowledge associated with
that effect. This type of verbal report, however, only provides a partial assessment of awareness
and should be accompanied by additional and more immediate measurements. To fill this gap,
subjective source attributions can also discern what types of knowledge (implicit, explicit, or
both) are attained, especially in concert with artificial grammar learning (Dienes, 2008). During
grammaticality judgment tests (GJTs), for example, participants are afforded the opportunity to
indicate what their decisions were based on (e.g., guess, intuition, recollection, or rule
knowledge; see Dienes & Scott, 2005; Rebuschat, 2013; Rebuschat & Williams, 2012). Implicit
knowledge normally corresponds to above-chance GJT performance when either guessing or
using intuition. Explicit knowledge is related more with recollection and rule knowledge. I
utilized both retrospective verbal reports and subjective source attributions in this dissertation to
explore how knowledge is developed from incidental learning conditions.
Several SLA researchers have successfully combined incidental learning tasks with
semiartificial languages (or, languages that adhere to a learner’s L1 lexicon but exhibit different
morphosyntactic structures) to mimic meaningful L2 acquisition contexts (Godfroid, Ahn,

13

Rebuschat, & Dienes, in preparation; Grey et al., 2014; Rebuschat & Williams, 2012; Williams
& Kuribara, 2008). Rebuschat and Williams (2012), for example, used an aural, semiartificial
language involving English words and German syntax to test native English speakers’ (N = 30)
acquisition of German syntax. Participants in the experiment performed significantly above
chance on GJTs after incidental exposure to the German word order. The researchers noted that
the addition of elicited imitations in the training phase may have facilitated learning as it forced
the participants to process the word order more deeply. Analysis of source attributions linked
with accurate GJT responses indicated that participants performed significantly above chance
while using intuition (implicit knowledge) and rule knowledge (explicit knowledge). Post-study
questionnaires revealed that participants acquired no conscious (verbalizable) linguistic rules for
the syntax, further reinforcing the finding of successful acquisition of unconscious knowledge.
Grey et al. (2014) found similar results using the semiartificial language of Japlish. After an
initial incidental training phase, thirty-six undergraduates’ accuracy on immediate
grammaticality acceptability ratings was significantly above chance. The researchers also found
that participants performed significantly above chance when utilizing aspects of unconscious
knowledge (the source attribution of intuition). Delayed testing two weeks later showed that
participants maintained their knowledge, highlighting the durability of L2 learning under
incidental exposure for L2 acquisition. Given the good results that have been obtained with this
paradigm in an incidental learning task, I also used an adapted form of the semiartificial German
language designed by Rebuschat and Williams (2012) for the learning stimuli in this dissertation.
Studying implicit language learning in adults can help provide a better understanding of
the relationship between human cognition and L2 acquisition (Godfroid, 2015; Godfroid &
Winke, 2015). While SLA research into implicit processing is on the rise, more work in niche

14

areas is needed. One such area is how implicit learning, and subsequently implicit knowledge,
develops through incidental learning conditions. The application of implicit learning within
different contexts can also prove useful in fully understanding the limits of the learning
mechanism (Andringa & Rebuschat, 2015). Two key aspects still requiring further inquiry are
(a) the role of emotions on implicit learning and (b) how individual differences affect implicit
learning (see Andringa & Rebuschat, 2015; Rebuschat, 2013; Tagarelli, Borges, & Rebuschat,
2015).
1.7 Emotions and Implicit Learning2
To my knowledge, there is no literature in SLA that details the effects of emotional states
on unconscious processing. Limited to the domain of psychology, few researchers (Braverman,
2005; Naismith, Hickie, Ward, Scott, & Little, 2006; Pretz, Totz, & Kaufman, 2010; Schultheiss
et al., 2005; Shang et al., 2013) have made specific inquiries into the area of implicit learning.
Braverman (2005), for instance, tested the effects of different moods on the detection of
covariation. Ninety-seven undergraduates were subjected to either a happy, neutral, or sad
emotional manipulation via four-minute, mood-inducing, video clips. Immediately following,
the participants saw a series of faces, accompanied by math and verbal scores. The researchers
correlated the nose sizes of the faces with either higher math or verbal scores, establishing a
strong covariation among the variables. Results indicated that individuals from the sad group
learned the covariation significantly better than the happy group, but only slightly better than the
neutral group. Naismith et al. (2006), however, found the opposite to be true with a clinical
population. In their study, 21 subjects with moderate to severe unipolar depression and 21

The term “implicit learning,” as referenced throughout Sections 1.7 and 1.8, is taken directly
from each cited author’s study. Therefore, the term’s use and meaning do not originate from me,
but from the specific researcher.
2

15

matched “healthy” adults completed a serial reaction time (SRT) task to measure implicit
learning. While appearing random, Naismith et al. had actually sequenced the task materials so
that gradual improvements in reaction time indicated implicit learning of the sequence. The
researchers discovered that participants suffering from depression performed significantly worse
than those from the control group. While no group was explicitly induced for emotionality, the
study did find that lower valence (i.e., sadness) impeded attempts at successful implicit learning.
In a more recent study, Pretz et al. (2010) examined emotional effects on two implicit
learning measures: an artificial grammar (AG) task and a SRT task. The researchers initially
divided undergraduates (N = 109) into three groups (positive, negative, and neutral) and utilized
images from the International Affective Picture Database (Lang, Bradley, & Cuthbert, 2008) to
induce a desired mood state. Subsequently, the students completed the AG task, which consisted
of first learning, then identifying letter strings that either did or did not conform to a specific
grammar. For the SRT task, individuals pressed a button corresponding to the location of a
stimulus appearance on the screen, which unbeknownst to participants, followed a probabilistic
pattern. Results for the two tasks were mixed. The researchers found that mood caused a
significant effect on AG learning, with the negative group performing significantly better than
both the neutral and positive groups. They did not measure significant effects, however, for the
SRT task.
While these studies provide preliminary insight into the impact of emotions on implicit
learning, none of the performance tasks relate to the acquisition of a second language per se.
That is, ecologically valid lexical or grammatical structures (e.g., meaningful semiartificial
language) have yet to be tested in concert with mood induction. In order to accomplish this
endeavor, I attempt to facilitate implicit learning (via an incidental learning task) for participants

16

as they try to acquire syntactic structures of a semiartificial language under a variety of
emotional stressors.
1.8 Implicit Learning and Individual Differences
Research into the role of individual differences on implicit learning is decidedly limited
(Granena, 2013; Grey, Williams, & Rebuschat, 2015; Kaufman et al., 2010; Rebuschat, 2013;
Toplak et al., 2010; Strack & Deutsch, 2004; Xie, Gao, & King, 2013). Findings of previous
studies indicate some individual components are more related to implicit learning performance
than others. Self-reported personality aspects, for example, may be among the best predictors in
this area. In a study of 153 participants, Kaufman et al. (2010) correlated implicit learning
performance on a SRT task with a variety of individual measures, ranging from psychometric
intelligence to intuition. The researchers found significant relationships between implicit
learning and the personality characteristics of impulsivity, intuition, and openness to experience.
Woolhouse and Bayne (2000) also found strong correlations between implicit learning and
intuition. They noted that intuitive individuals tended to better utilize unconscious knowledge
when forming strategies on how to accomplish implicit learning tasks. In yet another study on
individual differences, Grey et al. (2015) discovered that extraversion strongly (albeit negatively)
correlated with an implicit, semiartificial language task. The authors suggested that participants
with higher extraversion may have experienced processing interference from unknown, targetlanguage features within the task, not initially explained with explicit grammar rules. Besides
extraversion, the researchers examined other personality features, including neuroticism,
openness to experience, conscientiousness, and agreeableness. They did not find significant
relationships for these four variables. Given the findings above, it seems that openness, intuition,
and impulsivity emerge as good candidates for further inquiry in the context of implicit learning.

17

Weaker relationships, however, have generally been noted between implicit learning and
both intelligence (Gebauer & Mackintosh, 2007; Kaufman et al., 2010; Toplak et al., 2010; Xie
et al., 2013) and working memory capacity (WMC) (Grey et al., 2015; Kaufman et al., 2010;
Tagarelli, Borges Mota, & Rebuschat, 2011). Gebauer and Mackintosh (2007), for instance,
correlated the results of three implicit instructional treatments with a battery of intelligence tests
in a large number of German students (N = 401). The researchers failed to find strong links
between implicit learning performance and measures of fluid intelligence, crystallized
intelligence, and memory. Related to intelligence and cognitive ability, Xie et al. (2013) found
no relationships between implicit learning and the thirteen thinking styles as described by
Sternberg (1997) (categorized into Type 1, creativity and cognitive complexity; Type 2,
preference for norms and cognitive simplicity; and Type 3, value differentiated). Their study,
involving Chinese undergraduates (N = 87), correlated scores from the Thinking Styles
Inventory-Revised II survey (Sternberg, Wagner, & Zhang, 2007) with scores on an artificial
grammar learning task. The researchers measured no significant correlations between the any of
the thinking styles and performance under implicit instruction. WMC has also shown to have a
weak relationship with implicit artificial grammar learning. Both Kaufman et al. (2010) and
Tagarelli et al. (2011) found no significant correlations with operation span tasks and implicit
learning performance. Recently, Grey et al. (2015) tested thirty-six undergraduates and
compared phonological working memory, using non-word repetition tasks, with implicit learning
and found no significant correlations between the variables. Considering the findings from these
studies, I did not focus on intelligence and WMC as mediating factors of implicit learning.
In addition to openness, intuition, and impulsivity, I also examined emotional intelligence
(EI), or the “competence in perceiving emotions (both in oneself and others)” (Zeidner,

18

Matthews, & Roberts, 2009, p. 3), and FLA as characteristics that potentially mediate implicit
learning. Less is known about how these two variables interact with implicit performance. In
the case of EI, Fiori (2009) described how the trait may be linked with certain unconscious
processing and automaticity, possibly facilitating the development of implicit knowledge. From
an SLA perspective, Dewaele, Petrides, and Furnham (2008) discovered that multilinguals (N =
464) with high trait EI possessed lower levels of CA/FLA across languages learned, although
implicit learning was not looked at in the study. The finding, at a minimum, provides evidence
of a possible connection between EI and language learning. Undoubtedly, more research into
this area is needed (Zeidner et al., 2009). Regarding FLA, no studies to my knowledge have
examined the role of this variable in implicit learning. Due to the shortage of research on
individual differences and implicit learning within SLA, I decided to investigate the role of FLA,
EI, openness, intuition, and impulsivity in performance on an incidental, L2 task in both a neutral
state and under emotional strain.

19

CHAPTER 2
CURRENT STUDY
2.1 Present Study
In this study, I sought to better understand how emotions influence aspects of SLA under
incidental exposure. I also explored the relationships between L2 acquisition and certain
personality characteristics to discern possible impacts from individual differences. The
following research questions (RQs) guided my examination into these endeavors:
1. What is the role of positive, negative, and neutral emotional induction in the learning
and retention of L2 syntax?
2. Can learners in a positive, negative, or neutral emotional state acquire L2 syntax
implicitly?
3. How do mood states influence the relationship between openness, intuition, EI, FLA,
and impulsivity and L2 learning performance?
2.2 Participants
One hundred and twenty (N = 120)3 undergraduates from a major Midwestern university
participated in this study. I randomly assigned individuals to a Comparison group (n = 30) or
one of three experimental groups: the Positive (emotional) group (n = 30), the Negative
(emotional) group (n = 30), or the Neutral (emotional) group (n = 30). All participants met the
following criteria for eligibility: they were (a) between the ages of 18 and 30, (b) native-speakers
of English, (c) not heritage speakers of German or any other verb-second (V2) language (e.g.,

Power analysis (using a medium effect size and α = .05) indicated that for four treatment
groups, at least 116 total participants were needed to achieve Power = .8 for between-group
effects.
3

20

Dutch or Yiddish), (d) not regularly exposed to V2 languages, and (e) emotionally fit to view
violent, disturbing, or sexually explicit material (via a pre-screening questionnaire).
Out of the 120 participants, 37 were male and 83 were female. The average age was 21.3
years (SD = 2.68). Across each group, the demographics were nearly identical, as seen in the
following breakdown: (a) Comparison group, males (n = 9), females (n = 21), age (M = 21.5, SD
= 2.61); (b) Positive group, males (n = 9), females (n = 21), age (M = 21.2, SD = 3.45); (c)
Negative group, males (n = 9), females (n = 21), age (M = 21.2, SD = 2.56); and (d) Neutral
group, males (n = 10), females (n = 20), age (M = 21.1, SD = 2.06). Each student was paid $20
for their participation in this study.
2.3 Materials
2.3.1 Definitions of Terminology
Throughout the remainder of this dissertation, I use a variety of terms that may be
unfamiliar to some readers or require further clarification in the context of my study. These
items are briefly defined and operationalized in Table 2.
Table 2
Definition and Operationalization of Key Terminology
Term
Definition
Operationalization
Valence
A participant’s emotional state. 9-point Likert scale from sad/unpleasant to
happy/pleasant.
Arousal
A participant’s level of
9-point Likert scale from
stimulation.
relaxed/unaroused to stimulated/aroused.
Endorsement The acceptance of a sentence as GJT accuracy scores. Endorsements are
grammatical.
grammatical sentences that are judged as
grammatical (correct responses) and
ungrammatical sentences that are judged as
grammatical (incorrect responses).

21

Table 2 (cont’d)
Term
Definition
Grammatical
A measurement that reflects high
accuracy
endorsement rates for grammatical
sentences and low endorsement
rates for ungrammatical sentences.
Learning
Above-chance performance on the
GJTs.
Source
A subjective measurement that
attribution
indicates how a participant arrived
at their grammaticality judgment;
also known as judgment
knowledge.
Explicit
Knowledge that involves
knowledge
awareness and is consciously
accessible.
Implicit
Knowledge that is unconscious,
knowledge
procedural, and intuitive.

Operationalization
The number of correct responses
divided by the total number of items on
the GJTs.
GJT accuracy scores that are
significantly higher than 50%.
Four source attributions used in
conjunction with the GJTs: guess,
intuition, recollection, and rule
knowledge.
Source attributions (recollection and
rule knowledge) and verbal reports.
Source attributions (guess and intuition)
and a lack of verbal reports.

2.3.2 Incidental Exposure and Testing Sentences
I adapted the sentences used for the L2 exposure and testing tasks from Rebuschat’s
(2008) study on implicit language acquisition under incidental conditions. All belonged to a
semiartificial language that blended English words with German syntax. Three verb placement
rules, detailed in Table 3, constituted the linguistic focus of the sentences.
Table 3
Descriptions and Examples of the Three Verb Placement Rules
Rule
Description
Example
V2
Finite verb placed in second phrasal position Last week ate Rose excellent dessert at
of main clauses that are not preceded by a
a café.
subordinate clause.
V1

Finite verb placed in first position in main
clauses that are preceded by a subordinate
clause.

VF

Since his teacher criticism voiced, put
Chris more effort into his work.

Finite verb placed in final position in all
George repeated today that the
subordinate clauses.
movers his table scratched.
Note: V1 = verb first position; V2 = verb second position; VF = verb final position.

22

In total, I employed 180 sentences as the core materials for this study, divided in the
following manner: 120 sentences for the exposure set (plus 4 practice items) and 60 sentences for
the testing set (plus 4 practice items). The sentences were presented aurally to the participants.
A female, native speaker of American English, recorded all sentences using an Olympus VN8100PC digital voice recorder. I subsequently edited these recordings for audio consistency
prior to inclusion into the SuperLab program. The specific information about the exposure and
testing sentences is as follows:
2.3.2.1 Exposure Set
The exposure set, as detailed in Appendix A, consisted of 120 past-tense sentences (plus
4 practice items) that followed one of the three target verb placement rules (i.e., V2, VF-V1, and
V2-VF). The number of sentences per verb rule equaled 40, half of which were semantically
plausible and half of which were implausible. I specifically designed the items so that
participants needed to process the entire auditory string before judging for plausibility.
According to a frequency analysis, average sentence lengths in the exposure set were as follows:
(a) 8.9 words per sentence for V2 items (8.9 for plausible, 8.9 for implausible), (b) 12.8 words
per sentence for VF-V1 items (12.5 for plausible, 13.0 for implausible), and (c) 9.4 words per
sentence for V2-VF items (9.2 for plausible, 9.5 for implausible). Table 4 provides the syntactic
patterns, templates, and frequency counts for all items that appeared in the exposure set.

23

Table 4
Syntactic Templates for the Three Verb Placement Rules in the Exposure Set
Rule Pattern
Template
Freq.
V2
V2
[[NP]subj>[VP]>[AP|NP|PP]temp>[AP|NP|PP]>[AP|NP|PP]]
(20)
Liz heaved today the boxes onto the table.
[[AP|NP|PP]temp>[VP]>[NP]subj>[AP|NP|PP]>[AP|NP|PP]]
(20)
Often sat Sue in the seminar next to the door.
V1
VF-V1 [[[SUB>[NP]subj>[NP|PP]>[VP]]>[VP]>[NP]subj>[NP|PP]>[NP|PP]] (40)
After the police her car seized, expected Rose a fine from the
officer.
VF
V2-VF [[NP]subj>[VP]>[AP|NP|PP]temp>[SUB>[NP]subj>[NP|PP]>[VP]]]
(20)
Brian contested last June that his friend weapons possessed.
[[AP|NP|PP]temp>[VP]>[NP]subj>[SUB>[NP]subj>[NP|PP]>[VP]]]
(20)
Today figured Liz that her spouse an affair conducted.
Note: V1 = verb first position; V2 = verb second position; VF = verb final position; NP = noun
phrase; VP = verb phrase; AP = adverb phrase; PP = prepositional phrase; SUB = subordinate
clause. The sample sentences are in italics.
2.3.2.2 Testing Set
The testing set, listed in Appendix B, included 60 different, past-tense sentences (plus 4
practice items) which were all semantically plausible. Half of the sentences were grammatical
and followed the verb patterns of V2, VF-V1, or V2-VF. The other half were ungrammatical
and utilized one of the following verb placement patterns: *VF, *VF-V2, *V1-VF, *V1, *V3, or
*V4. Frequency analysis indicated that the average length for grammatical items was 10.7
words, whereas ungrammatical items averaged 11.2 words. Table 5 displays the syntactic
templates and frequency counts of all items that appeared in the testing set.

24

Table 5
Syntactic Templates for All Verb Placement Rules in the Testing Set
Pattern
Template
Freq.
V2
[[NP]subj>[VP]>[AP|NP|PP]temp>[AP|NP|PP]>[AP|NP|PP]]
(5)
Jim loaded in the afternoon the wagon with hay.
[[AP|NP|PP]temp>[VP]>[NP]subj>[AP|NP|PP]>[AP|NP|PP]]
(5)
Yesterday enjoyed Emma the food in the dining hall.
VF-V1
[[SUB>[NP]subj>[NP|PP]>[VP]]>[VP]>[NP]subj>[NP|PP]>[NP|PP]]
(10)
Because her company capital lacked, organized Chloe a fundraiser with
her boss.
V2-VF
[[NP]subj>[VP]>[AP|NP|PP]temp>[SUB>[NP]subj>[NP|PP]>[VP]]]
(5)
Emma said in the afternoon that her parents the apartment rented.
[[AP|NP|PP]temp>[VP]>[NP]subj>[SUB>[NP]subj>[NP|PP]>[VP]]]
(5)
Some time ago claimed Jim that his mother Spain liked.
*VF
*[[AP|NP|PP]temp>[NP]subj>[NP|PP]>[NP|PP]>[VP]]
(5)
*Recently John the Boston Marathon in four hours ran.
*VF-V2 *[[SUB>[NP]subj>[AP|NP|PP]temp>[NP|PP]>[VP]]>[NP]subj.>[VP]>[NP|PP]
(5)
*When his parents recently to Paris retired, Paul flew a lot to France.
*V1-VF *[[VP]>[NP]subj>[NP|PP]>[SUB>[NP]subj>[AP|NP|PP]temp>[NP|PP]>[VP]]]
(5)
*Knew Chloe Sydney when her daughter some time ago in Australia lived.
*V1
*[[VP]>[NP]subj>[AP|NP|PP]temp>[AP|NP|PP]>[NP|PP]]
(5)
*Hired Paul yesterday two new chefs for his restaurant.
*V3
*[[AP|NP|PP]temp>[NP]subj>[VP]>[NP|PP]>[NP|PP]]
(5)
*After dinner Chloe smashed the guitar without any warning.
*V4
*[[AP|NP|PP]temp>[NP]subj>[NP|PP]>[VP]>[NP|PP]]
(5)
*Recently Paul much furniture imported for her new weekend retreat.
Note: V1 = verb first position; V2 = verb second position; VF = verb final position; NP = noun
phrase; VP = verb phrase; AP = adverb phrase; PP = prepositional phrase; SUB = subordinate
clause. Sample sentences are in italics; (*) indicates ungrammaticality.
2.3.3 Emotional Stimuli
Researchers have incorporated a variety of visual stimuli to successfully elicit affective
states from their subjects. These include both film clips (Braverman, 2005; Carvalho et al.,
2012; Miller et al., under review; Storbeck & Maswood, 2015; Tsai et al., 2000; Viinikainen et
al., 2012) and photographic imagery (Aldhafeeri et al., 2012; Aluja et al., 2015; Barke, Stahl, &
Kröner-Herwig, 2012; Britton, Taylor, Sudheimer, & Liberzon, 2006; Pretz et al., 2010; Tok,

25

Koyuncu, Dural, & Catikkas, 2010). In the current study, I utilized a combination of the two
formats to facilitate emotional induction in participants.
2.3.3.1 Emotional Movie Database (EMDB)
All movie clips were from the EMDB, a collection of modern film excerpts derived from
a recent Carvalho et al. (2012) study. I selected film clips for each treatment group based on
their specific measured valence (unpleasant to pleasant) and arousal levels, as measured on a 9point Likert scale by Carvalho et al. All film clips were 40 seconds in length, did not have
sound, and maintained a resolution of 720 x 576 pixels. Throughout the experiment, participants
from each treatment group viewed a total of ten affective film clips. The Positive group watched
erotic film excerpts from the EMDB known to stimulate high valence (M = 6.53, SD = 1.75) and
high arousal (M = 5.89, SD = 1.88) in self-reports. The Negative group viewed horror film
excerpts known to stimulate low valence (M = 2.01, SD = 1.58) and high arousal (M = 7.04, SD
= 1.86) in self-reports. Finally, the Neutral group watched scenery film clips that registered midrange valence (M = 6.02, SD = 1.59) and low arousal (M = 2.90, SD = 2.03) in self-reports. I
selected one objects film clip, known to generate mid-range valence (M = 4.90, SD = 1.82) and
low arousal (M = 2.44, SD = 2.23), for pre-treatment practice with all groups.
One-sample t test results indicated that the valence ratings for the positive, t(9) = 17.80, p
<.001, r = .99, negative, t(9) = -25.20, p <.001, r = .99, and neutral, t(9) = 8.07, p <.001, r = .94
movie clips were significantly different from the neutral value of the Likert scale (i.e., “5”).
However, an independent-samples t test showed that the positive clips rated significantly higher
than the neutral ones, t(18) = 3.29, p = .004, r = .61, marking an appropriate valence

26

differentiation between the two genres.4 Lastly, while the valence scores for the erotic and
horror clips are not equally distanced from the neutral Likert value (and thus providing
asymmetrical intensities), they are the only sets of clips from the EMDB that offer both extreme
valence and arousal ratings. As such, I decided against including lesser potent film excerpts to
level mean valence scores for the negative group in order to maintain the highest emotional
impact for participants (see Miller et al., under review). Film clip descriptions and the mean
ratings for valence and arousal as reported by Carvalho et al. (2012) are located in Appendices
D, E, and F.
2.3.3.2 International Affective Picture System (IAPS)
The emotionally-charged images shown to participants came from the IAPS (Lang et al.,
2008). Similar to the EMDB selection criteria, I chose all pictures from the IAPS database with
specific valence (unpleasant to pleasant) and arousal (calm to exciting) ratings (from a 9-point
Likert scale) in mind. The images were in the JPEG (Joint Photographic Experts Group) format
and had been digitally color-corrected (by the IAPS managers) for optimal viewing on a
computer screen. While the dimensions varied slightly, no picture exceeded a resolution of
1,024 x 768 pixels. Participants in the three treatment groups each viewed a total of 70 pictures
at various points in the experiment. The Positive group viewed images with highly rated valence
(M = 6.86, SD = 1.78) and arousal (M = 6.10, SD = 2.17) levels (e.g., erotica, extreme sports,
food). The Negative group watched images that registered low valence (M = 1.94, SD = 1.34)
but high arousal (M = 6.44, SD = 2.28) (e.g., mutilations, aimed guns, attacks). Lastly, the

The inclusion of neutral film clips that have been rated as “slightly positive” did not interfere
with emotional induction for participants in the Neutral group. The valence and arousal patterns
reported by these individuals were similar to those within the Comparison group (see Tables 8
and 10).
4

27

Neutral group saw images associated with mid-range valence (M = 4.96, SD = 1.09) and low
arousal (M = 3.13, SD = 1.94) (e.g., tools, furniture). Two neutral images with mid-range
valence (M = 5.02, SD = .91) and low arousal (M = 2.54, SD = 2.03) ratings were chosen for the
pre-treatment exercise.
One-sample t test results showed that the valence ratings for the positive, t(69) = 30.91, p
<.001, r = .97, and negative, t(69) = -70.04, p <.001, r = .99, images were significantly different
from the neutral value of the Likert scale. The neutral pictures, however, were not significantly
different from “5,” t(69) = -1.07, p = .289, r = .13. As with the EMDB film clips, the positive
and negative images are not equally distanced from the neutral Likert value. Again, I made no
attempt to balance valence ratings because this would have compromised the overall emotional
impact in the negative group. The image descriptions and mean ratings for valence and arousal
as reported by Lang et al. (2008) are found in Appendices D, E, and F.
2.3.4 Subjective Affective Ratings
To measure participants’ subjective emotionality (i.e., self-reports) during the study, I
utilized four SAMs. The SAMs evaluated participants’ valence and arousal levels on a ninepoint Likert scale (see Appendix G). For the purposes of this study, valence was defined as a
positive (e.g. happy, pleasant) or negative (e.g. sad, unpleasant) emotional state, while arousal
signified a high (e.g. stimulated, aroused) or low (e.g. relaxed, unaroused) level of stimulation
(see Reevy, Oxer, & Ito, 2010). Students rated each emotional dimension at various points
throughout the experiment, as explained in the subsequent Procedure section (2.4).
2.3.5 Personality Questionnaires
I used the following five questionnaires to measure individual trait characteristics of all
participants at the beginning of the study.

28

2.3.5.1 Big Five Aspect Scale (BFAS)
The BFAS (DeYoung, Quilty, & Peterson, 2007) measures five distinct aspects (each
divided into two sub-factors) of individual personality. For the current study, I only
administered the items from the Openness/Intellect aspect to participants. Both sub-factors,
intellect and openness, maintained good internal reliabilities from two large-scale studies within
the DeYoung et al. (2007) publication (.79 and .72, respectively, from a sample size of N = 480
and .81 and .77 from a sample size of N = 90). Ten items measured each factor using a 9-point
Likert scale labeled strongly disagree to strongly agree. The sum of the Likert values produced
the score for each factor. According to DeYoung et al., a high intellect score represents a
disposition towards ingenuity and ideas, which has been correlated with fluid intelligence and
working memory (DeYoung, Peterson, & Higgins, 2005). A high openness score relates with
fantasy, feelings, and aesthetics.
2.3.5.2 Rational Experiential Inventory (REI)
The REI (Pacini & Epstein, 1999) measures a preference to engage in either rational or
experiential processing, as well as a self-reported ability to use each mode (Pretz et al., 2014).
According to Pacini and Epstein, individuals with a rational thinking style tend to exert selfcontrol, favor reasoning, and are analytical in nature. Experiential thinkers, however, are more
open-minded and rely on intuition and affect when processing information. For the purposes of
this study, I only used the experiential component of the REI for gauging intuitiveness.
Cronbach’s alpha for this scale, as reported by Pacini and Epstein, was high at α = .87. There
were 20 items on the experiential portion of the REI which were measured on a 9-point Likert
scale (strongly disagree to strongly agree). Overall experientiality was obtained by summing the
Likert values, with high scores representing an inclination towards intuition.

29

2.3.5.3 Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF)
The TEIQue-SF (Cooper & Petrides, 2010) provides a quick assessment of global trait
emotional intelligence. Trait EI encapsulates a variety of emotional dispositions and selfperceptions (Petrides, Pita, & Kokkinaki, 2007) and has been linked with both communicative
anxiety (CA) and FLA in multilinguals (Dewaele et al., 2008). According to Cooper and
Petrides, the TEIQue-SF yielded a high Cronbach’s alpha for both males (α = .88) and females (α
= .87). This abbreviated version consisted of 30 items derived from 15 trait EI features in the
longer, TEIQue test. Responses were measured on a 9-point Likert scale (strongly disagree to
strongly agree) and scored by summing the Likert values. Possible scores ranged from 30 (low
global trait EI) to 270 (high global trait EI).
2.3.5.4 Foreign Language Classroom Anxiety Scale (FLCAS)
The FLCAS (Horwitz et al., 1986) is an oft-used tool in SLA research to measure
individual foreign language anxiety in the L2 classroom. Per Horwitz et al., the test has high
internal reliability (α = .93) and reflects the following three domains: communication
apprehension, test anxiety, and fear of negative evaluation. Reponses to the 33-question survey
were measured on a 9-point Likert scale (strongly disagree to strongly agree). Possible scores,
attained by summing the Likert values, ranged from 33 (low foreign language anxiety) to 297
(high foreign language anxiety).
2.3.5.5 UPPS Impulsivity Behavior Scale
The UPPS (Whiteside & Lynam, 2001) combines four personality facets ((lack of)
premeditation, urgency, sensation seeking, and (lack of) perseverance) to measure individual
impulsivity. As reported by Whiteside and Lynam, the internal consistency coefficients were
high for each scale (.91, .86, .90, and .82 respectively). The total number of items on the UPPS

30

equals 45 and were all measured on a 9-point Likert scale (strongly disagree to strongly agree).
I calculated the scores for each scale by summing the Likert values. Scale interpretations, as
explained by Whiteside, Lynam, Miller, and Reynolds (2005, p. 561), are as follows: (a) a (lack
of) premeditation indicates a “difficulty in thinking and reflecting on the consequences of an act
before engaging in that act;” (b) high urgency shows a “difficulty resisting cravings and
temptations;” (c) high sensation seeking signifies a “tendency to enjoy and pursue activities that
are exciting” or even dangerous; and (d) a (lack of) perseverance highlights a “difficulty
completing projects and working under conditions that require resistance to distracting stimuli.”
2.4 Procedure
2.4.1 The Five Phases of the Procedure
I divided this study, as seen in Figure 1, into five phases: (1) pre-experimental measures,
(2) initial emotional induction, (3) incidental exposure and secondary emotional induction, (4)
immediate language testing, and (5) delayed language testing and debriefing interview.

31

Figure 1. The graphic representation of the current study’s procedure.
2.4.1.1 Phase 1, Pre-experimental Measures
After signing the consent form and completing an initial SAM and background
information (to ascertain demographic information such as gender, age, foreign languages
spoken, number of years of foreign language study, and film preferences), participants filled out
a series of questionnaires (FLCAS, TEIQue-SF, Big Five, REI, and UPPS) to measure specific
personality characteristics. I administered all surveys in a counterbalanced order via hardcopy.
The completion time for Phase 1 was approximately 20 minutes.

32

2.4.1.2 Phase 2, Initial Emotional Induction
Upon completion of the individual personality measures, participants randomly assigned
to one of the treatment groups were seated in front of a computer monitor and began their initial
emotional induction (presented on the SuperLab 5 platform). The students underwent a brief
preparatory session, watching one practice movie clip and two neutral images, for stimulus
familiarization. Next, participants viewed a series of five, 40-second film clips from the EMDB,
intermixed with 20 images from the IAPS (see Appendix D). Each image was displayed for
three seconds, for a total stimulus presentation of 260 seconds. A white screen with a black
crosshair, shown for 500ms, separated each visual stimulus. Figure 2 shows the display format
for the emotional induction.

Figure 2. Diagram of the initial emotional induction format.
After watching all visual stimuli, participants completed a second SAM to record their
subjective, emotional well-being. As a substitute task, individuals assigned to the Comparison
group surfed the internet for six minutes (a comparable length of time to the emotional
induction) prior to SAM 2. The completion time for Phase 2 was six minutes.

33

2.4.1.3 Phase 3, Incidental Exposure and Secondary Emotional Induction
Immediately after the first round of mood induction, I exposed participants to the
semiartificial language under incidental conditions, mirroring the Training Phase in Experiment
2 of Rebuschat and Williams (2012). That is, I instructed individuals to: (a) listen to each
sentence of the exposure set (see Appendix A); (b) repeat the sentence aloud; (c) and judge
whether the sentence was semantically plausible or implausible. I did not inform participants
that the sentences belonged to a new language system, nor that were to be subsequently tested on
the material. A practice session with four sample sentences oriented participants to the
procedure. All sentences from the exposure set were presented in a random order. I captured the
elicited imitations on an Olympus VN-8100PC digital voice recorder and analyzed later for
accuracy of repetition (i.e., verbs in the correct sentence position; lexical substitutions,
insertions, or omissions were ignored). All tasks in Phase 3 were conducted on SuperLab 5.
For the three treatment groups, 30 new images (25% of the total exposure set sentences)
from the IAPS were flashed onto the computer screen at three pseudo-randomized points
throughout the incidental exposure session. The placement of emotional stimuli was informed
by Tobias’ (1986) model that identified three critical points where anxiety most directly affected
learning from instruction (i.e., pre-processing, during processing, and after processing (before
output)). Ten pictures were projected for 1,500ms between the aural presentation of the sentence
and the elicited imitation prompt (pre-processing). Ten were shown for the duration of time
needed for participants to produce an elicited imitation (processing). The remaining ten were
presented for 1,500ms after the elicited imitation but before the sematic plausibility judgement
(after processing (before output)). The inclusion of affective stimuli attempted to simulate
persistent emotionality over the course of the incidental exposure and better represent L2

34

acquisition under emotional strain (see Pessoa, 2009). Individuals assigned to the Comparison
group did not experience any visual stimuli during the exposure set. Figure 3 presents this
procedure for the three treatment groups.

Figure 3. Incidental exposure for the positive, negative, and neutral treatment groups.
After finishing the exposure task, I subjected participants from the three treatment groups
to a secondary round of emotional induction. Similar to Figure 2 in Phase 2, participants viewed
a series of five different, 40-second film clips from the EMDB, intermixed with 20 images from
the IAPS (different from the ones shown during Phase 2 and the exposure task from Phase 3).
Again, the images were displayed for three seconds each with a total visual stimulus presentation
time of 260 seconds. Lastly, participants completed a third SAM to gauge their emotional
bearings. As in Phase 1, Comparison group participants surfed the internet as a substitute task
for emotional induction prior to SAM 3. The completion time for Phase 3 was 45 minutes
(including a short break after SAM 3).
2.4.1.4 Phase 4, Immediate GJT
Similar to the Testing Phase in Experiment 2 of Rebuschat and Williams (2012), I
informed participants from all four groups that the sentences presented in the exposure set

35

represented a new, complex language system instead of an arbitrary pattern of words. I then
asked them to listen to 60 more sentences (see Appendix B) and answer the following the
questions for each item: (a) “is the sentence grammatical (in accordance with the new language
system presented in the exposure set)?” and (b) “what is the basis of your judgment?” Table 6
provides the guidelines for using source attributions to determine one’s basis of judgment. Here,
the subjective measures of guess and intuition suggested the presence of implicit, unconscious
knowledge, whereas recollection and rule knowledge implied the presence of explicit, or
conscious knowledge.
Table 6
Guidelines for Source Attribution Ratings of Test Item Grammaticality
Source Attribution Ratings (select one of four)
Guess
Judgement based on a guess (i.e., flipping a coin).
Intuition
Confident in the decision but not sure why.
Recollection
Recalled the partial or entire sentence from the exposure phase.
Rule knowledge
Acquired a rule during the exposure phase that can be articulated.
Within SuperLab 5, a practice session with four sample test sentences familiarized
participants with the procedure. All sentences from the test set were randomized for each
individual. Upon completion of the immediate posttest, I administered a fourth SAM to measure
participants’ final emotional state. The completion time for Phase 4 was 15 minutes.
2.4.1.5 Phase 5, Delayed GJT and Debriefing Interview
After a two-week period of non-exposure to the L2 syntax, the participants returned and
completed a second GJT on SuperLab 5. The testing sentences (see Appendix B) and the format
were the same as in Phase 4. That is, participants selected which items they believed were
grammatical or ungrammatical based upon what they had heard and repeated during the
incidental exposure period. After each response, participants reported their basis of judgment
using one of the four source attributions listed in Table 5. After completing the delayed posttest,

36

students participated in a debriefing interview (see Appendix C) focused on the following
requests: (a) verbalize any grammar patterns or regularities possibly discerned over the course of
the experiment, and (b) describe any effects to performance from the film clips or images. I
recorded the discussions on an Olympus VN-8100PC digital voice recorder and transcribed the
responses at a later date. The completion time for Phase 5 was 25 minutes.
2.5 Analysis
The following three parts provide a general outline of the analytical processes used to
answer each RQ. Based on the amount and variety of data examined, I provide a more in-depth
account of these analyses alongside my findings within the Results chapter.
2.5.1 Analysis of Emotional Induction
To start, I tested whether the induction material used for this experiment succeeded in
generating the appropriate mood changes for participants within the three treatment groups. To
validate these effects, I analyzed valence and arousal from SAM data at four collection points
throughout the study (i.e., Start, Post Initial Induction, Post Exposure, and End). Because the
data were not normally distributed, I used non-parametric Kruskal-Wallis tests to assess
emotionality differences between groups at the four self-assessment points and I used Friedman’s
ANOVAs to examine within-group changes over time. To add a qualitative dimension, I also
included data and participant excerpts from retrospective debriefing interviews that discussed the
effects of emotional stimuli throughout the exposure phase.
2.5.2 Analysis of RQ1
RQ1 focused on the role of emotion in the learning and retention of a novel grammar
structure. I answered this RQ by examining two different parts of the study: (a) the exposure
phase (i.e., elicited imitations and plausibility judgments) and (b) the testing phase (i.e.,

37

immediate and delayed GJTs). For the first portion, successful navigation of the exposure phase
was a likely indicator of higher scores on the GJT (see Rebuschat & Williams, 2012). The
presence of emotional induction, however, needed to be considered as a possible distraction to
overall learning and knowledge retention (Tobias, 1986). To measure any affective impacts in
these regards, I analyzed both the elicited imitations and the plausibility judgments for each
experimental group.
For the elicited imitations, I awarded one point for every correct verb placement within a
clause (note that VF-V1 and V2-VF have two clauses per item), for a total possible score of 200.
Descriptive statistics provided accuracy rates for (a) total items, (b) plausible and implausible
items, and (c) verb patterns, for each group. Due to non-normal distributions in the data, I used
Kruskal-Wallis testing to compare between-group differences among the four abovementioned
variables. Lastly, I divided the entire exposure set into 24 chronological stages (5 repetitions per
stage) to measure within-group accuracy over time and to determine any impacts from emotional
induction. I repeated this analysis for each of the three target structures individually,
apportioning 20 chronological stages per verb pattern (2 repetitions per stage). With the
plausibility judgments, I utilized descriptive statistics to gauge accuracy ratings among the
groups for total items and plausible/implausible items. Non-parametric testing compared
performances between the groups in each of the three categories.
Next, I analyzed participants’ immediate and delayed GJT scores. Here, one point was
awarded for each correct response (either a correct endorsement of a grammatical item or a
correct rejection of an ungrammatical item) for a total possible score of 60. I then converted
these scores to an overall accuracy rating. In order to examine whether participants from each
experimental group learned the L2 syntax, I compared the mean immediate GJT accuracy rates

38

with chance (50%) using one-samples t tests. I also measured between-group differences with a
one-way ANOVA. Second, I converted participants’ GJT scores into d prime scores (see
MacMillan & Creelman, 2005). D prime values account for the difference between hit rates
(i.e., correctly endorsed grammatical sentences) and false alarms (i.e., incorrectly endorsed
ungrammatical sentences) and help to gauge participants’ response biases. Positive d prime
scores suggest good discrimination among the two items, with a higher tendency to endorse
grammatical sentences. Negative d prime values, however, indicate a bias towards endorsing
ungrammatical items. A score of zero reveals an inability to distinguish between the sentence
types. I compared these values both to chance (zero) and with between-group analysis. Third, I
evaluated the endorsement ratings for all grammatical and ungrammatical verb patterns tested in
the GJT to gauge group performance. To examine whether participants from each experimental
group retained their knowledge of the L2 syntax over time (two weeks), I executed the same
analyses with the delayed GJT results as described for the immediate GJT scores. Lastly, I
assessed the relationship between the two GJT performances using Pearson correlations and
mixed-design ANOVAs.
2.5.3 Analysis of RQ2
The second research question centered on the ability of individuals in positive, negative,
or neutral mood states to acquire an L2 syntax implicitly. For this inquiry, I first checked
whether mood influenced participants’ propensity to select the four different source attribution
categories: guess, intuition, recollection, or rule knowledge. I consolidated these attributions
further (see Dienes & Scott, 2005), combining guess and intuition to represent the presence of
unconscious (implicit) structural knowledge, and recollection and rule knowledge for conscious
(explicit) structural knowledge. Next, I compared the accuracy ratings of the two source

39

attributions with chance performance. Accuracy ratings significantly above 50% would signal
the successful formation of either implicit or explicit knowledge (or a combination of both types)
of the L2 syntax. In order to examine the individual verb patterns more specifically, I performed
binomial logistic regression using Generalized Estimating Equations (GEE) to model the odds of
selecting an explicit category over an implicit one. For each variable, a significant Wald chisquare value (p <.05) for the intercept specified a reliance on explicit knowledge by the reference
group (i.e., Comparison group). Regression coefficients for the different treatment groups
indicated how participants’ reliance on explicit knowledge changed as a result of a mood
induction, with positive values signaling greater use of explicit knowledge and negative values
suggesting a shift towards implicit knowledge. The analysis also supplied an odds ratio value
(Exp(B)). According to Field (2013), an odds ratio greater than 1 means that as the predictor
increases, so too do the odds of the outcome occurring. The converse relationship occurs if the
value is less than 1. Finally, I provided excerpts and analyses from post-experiment verbal
reports to examine if participants from any group had consciously recognized or established
grammatical rules for the target syntax during incidental exposure. An ability to formulate
grammatical patterns or regularities would indicate explicit knowledge acquisition, whereas an
inability to do so would suggest a lack of evidence for explicit knowledge.
2.5.4 Analysis of RQ3
For the final research question, I examined whether connections existed between
individual differences (i.e., openness, intuition, EI, FLA, and impulsivity) and L2 performance
within the context of positive, negative, and neutral emotional states. I conducted this
investigation in two parts. First, I performed an exploratory factor analysis on participants’
subjective ratings from five different personality questionnaires to identify the most relevant

40

constructs in each questionnaire. Subsequently, I examined these factors, along with
corresponding interaction terms, in a linear regression model to determine which explanatory
variables contributed to overall accuracy rates on the immediate GJT. I chose the immediate
posttest as the dependent variable, rather than the delayed posttest, because of its proximity to
the emotional induction. Based on moderation analysis from the linear regression model, I
identified four significant interactions. To examine these interactions further, I graphed the
immediate GJT performances by participants’ self-reported factor (or, trait). For each group,
participants were divided into categories of low (< mean -1SD), average (mean ±1SD), and high
(> mean +1SD) trait levels. After performing within-sub categorical comparisons, I correlated
group trait levels with related source attribution data to ascertain any possible relationships
between the two variables.

41

CHAPTER 3
RESULTS
Within this chapter, I have organized the results based upon the three research questions
for my study. I first examined the effectiveness of my emotional stimuli and their ability to alter
participants’ mood states within the Positive, Negative, and Neutral groups. Secondly, I
investigated the role of affect in an incidental learning task, with a focus on the learning and
retention of an L2 syntax. Next, I looked at GJT accuracy for different source attribution
categories to measure whether participants could acquire an L2 syntax implicitly. Lastly, I
described the relationship between individual differences and learning performance from a hot
cognitive perspective.
3.1 Emotional Induction
3.1.1 Valence
I examined valence data first, and the descriptive statistics are found in Table 7.
According to the initial SAM ratings, participants from all groups began the experiment at a
similar affective state. However, Friedman’s tests revealed significant emotional changes for all
groups over the course of the study. Figure 4 graphically depicts these various fluctuations.

42

Table 7
Descriptive Statistics and Results of Friedman’s Testing for Valence Ratings
Starta
Group

Nc

Comparison

30

Positive

29

Negative

30

Neutral

30

M (SD)
95% CI
7.30 (1.09)
(6.89, 7.71)
6.83 (1.17)
(6.38, 7.27)
6.80 (1.40)
(6.28, 7.32)
6.80 (1.24)
(6.34, 7.26)

Post Initial
Induction
M (SD)
95% CI
7.57 (0.94)
(7.22, 7.92)
6.14 (1.48)
(5.57, 6.70)
3.40 (1.55)
(2.82, 3.98)
6.47 (1.28)
(5.99, 6.94)

Post
Exposureb
M (SD)
95% CI
6.70 (1.29)
(6.22, 7.18)
5.79 (1.50)
(5.22, 6.36)
3.07 (1.74)
(2.42, 3.72)
5.87 (1.66)
(5.25, 6.48)

End
M (SD)
95% CI
5.97 (1.67)
(5.34, 6.59)
5.72 (1.28)
(5.24, 6.21)
4.87 (1.36)
(4.36, 5.37)
6.03 (1.45)
(5.49, 6.57)

Change from
Start to End
χ2(3)

p

29.46

<.001

20.72

<.001

65.12

<.001

20.15

<.001

Note. The scale for the valence ratings is 1 (low valence) to 9 (high valence). During the primary
induction period (i.e., Start through Post Exposure), changes in mean valence ratings (ΔM) by
gender are as follows: Comparison group: male, ΔM = -0.33, female, ΔM = -0.72; Positive group:
male, ΔM = -0.75, female, ΔM = -1.14; Negative group: male, ΔM = -3.22, female, ΔM = -3.95;
Neutral group: male, ΔM = -0.80, female, ΔM = -1.00.
a
Kruskal-Wallis testing revealed no differences between groups, H(3) = 4.26, p = .235.
b
Accounts for both the induction during incidental exposure and the post-exposure, secondary
emotional induction period.
c
One participant was removed from the Positive group due to incomplete data.

Likert Value (1-low, 9-high)

9
8
7
6
5
4
3
2

a

1
Start

Post Initial
Induction

Post Exposure

Comparison Group

Positive Group

Negative Group

Neutral Group

End

Figure 4. Valence ratings for each group over the course of the experiment. Here, a denotes the
start of the immediate posttest. Error bars represent the 95% confidence intervals for each mean
value.

43

For post-hoc analysis, I used Wilcoxon signed-rank tests, with α = .004 to adjust for
multiple testing. These results are listed in Table 8. For the Comparison group, no significant
changes were recorded between Start and Post Initial Induction (which, for this group, consisted
of surfing the internet for six minutes). However, a significant decrease in valence occurred
between Post Initial Induction and Post Exposure, indicating a more unpleasant state prior to the
immediate posttest. This drop likely resulted from experimental fatigue. After this point, the
participants’ mood remained stable through the completion of the study. Individuals from the
Positive group recorded no significant changes in mood between any of the data collection
points, suggesting that the film clips and images helped to sustain a consistent emotionality
throughout the experiment. Interestingly, the positive induction material did not elevate
participants’ valence levels at any point in the study, demonstrating an overall lack of
effectiveness in this regard. Participants in the Negative group measured a significant decrease
in mood from Start to Post Initial Induction, which remained steady through Post Exposure.
Here, the induction material successfully depressed valence levels over multiple SAM points and
led to a generally sad or unpleasant emotional status both during incidental exposure and prior to
the immediate posttest. Valence ratings sharply increased by the end of the experiment,
indicating a significant recovery in mood. Lastly, participants from the Neutral group behaved
similarly to those from the Comparison group, registering a significant drop in emotionality only
between Post Initial Induction and Post Exposure. These results suggest that the neutral
induction material performed as expected and did not function to alleviate experimental fatigue.

44

Table 8
Results of Wilcoxon Signed-Ranks Testing between Valence Ratings
Start to Post
Post Initial
Initial
Induction to
Post Exposure
Induction
Post Exposure
to End
z
z
z
Group
N
r
r
r
1.64
-3.00**
-2.73
Comparison 30
.17
-.32
-.29
-2.59
-1.47
-0.29
Positive
29
-.27
-.16
-.03
-4.64**
-1.58
4.20**
Negative
30
-.49
-.17
.44
-1.82
-2.88*
1.17
Neutral
30
-.19
-.30
.12
*p = .004; **p <.004
3.1.2 Arousal
I evaluated the arousal data using a similar analysis, for which the descriptive statistics
are in Table 9. Initial SAM data again indicated that participants from all groups began the
experiment at comparable levels. Friedman’s testing showed significant changes in arousal
levels throughout the experiment only for the Comparison, Positive, and Negative groups.
Figure 5 provides a graphical representation of this data set.

45

Table 9
Descriptive Statistics and Results of Friedman’s Testing for Arousal Ratings
Starta
Group

N

Comparison

30

Positive

30

Negative

30

Neutral

30

M (SD)
95% CI
3.40 (1.59)
(2.81, 3.99)
3.93 (2.07)
(3.16, 4.71)
3.13 (1.85)
(2.44, 3.82)
3.27 (1.72)
(2.62, 3.91)

Post Initial
Induction
M (SD)
95% CI
3.53 (1.91)
(2.82, 4.25)
4.93 (2.02)
(4.18, 5.69)
5.33 (2.54)
(4.39, 6.28)
3.43 (1.72)
(2.79, 4.07)

Post
Exposureb
M (SD)
95% CI
4.23 (2.27)
(3.39, 5.08)
4.83 (2.07)
(4.06, 5.61)
5.67 (2.68)
(4.67, 6.67)
3.90 (2.30)
(3.04, 4.76)

End
M (SD)
95% CI
3.87 (2.11)
(3.08, 4.66)
3.33 (1.67)
(2.71, 3.96)
3.87 (1.94)
(3.14, 4.59)
3.60 (1.77)
(2.94, 4.26)

Change from
Start to End
χ2(3)

p

8.23

.041

17.89

<.001

41.18

<.001

3.66

.301

Note. The scale for the arousal ratings is 1 (low arousal) to 9 (high arousal). During the primary
induction period (i.e., Start through Post Exposure), changes in mean arousal ratings (ΔM) by
gender are as follows: Comparison group: male, ΔM = 0.67, female, ΔM = 0.90; Positive group:
male, ΔM = 1.77, female, ΔM = 0.52; Negative group: male, ΔM = 1.66, female, ΔM = 2.91;
Neutral group: male, ΔM = 1.80, female, ΔM = 0.05.
a
Kruskal-Wallis testing revealed no differences between groups, H(3) = 2.50, p = .475.
b
Accounts for both the induction during incidental exposure and the post-exposure, secondary
emotional induction period.

Likert Value (1-low, 9-high)

9
8
7
6
5

4
3
a

2
1
Start

Post Initial
Induction

Post Exposure

Comparison Group

Positive Group

Negative Group

Neutral Group

End

Figure 5. Arousal ratings for each group over the length of the experiment. Here, a denotes the
start of the immediate posttest. Error bars represent the 95% confidence intervals for each mean
value.

46

Table 10 displays the results from post-hoc analysis with the Bonferroni correction (α
= .006). As expected, participants from the Comparison group indicated no fluctuations in their
arousal between any of the SAM data points. For the Positive group, participants only
demonstrated a significant change to arousal between Post Exposure and the end of the
experiment, which measured as a decrease. This suggests that the positive induction material
failed to function as a stimulator, leaving those from the Positive group reportedly unaroused
throughout the incidental exposure. Conversely, participants from the Negative group showed a
significant increase in arousal from Start through the Post Initial Induction, which remained
stable prior to the immediate posttest. This rise in arousal levels again confirmed the efficacy of
the negative treatment. Subsequently, individuals from the Negative group significantly
recovered from their agitated state prior to the end of the experiment.
Table 10
Results of Wilcoxon Signed-Ranks Testing between Arousal Ratings
Start to Post
Post Initial
Initial
Induction to
Post Exposure
Induction
Post Exposure
to End
z
z
z
Group
N
r
r
r
.64
2.22
-1.44
Comparison 30
.07
.23
-.15
2.11
-.51
-3.47**
Positive
30
.22
-.05
-.37
3.95**
1.84
-3.69**
Negative
30
.42
.19
-.39
.35
1.92
-.68
Neutral
30
.04
.20
-.07
*p = .006; **p <.006
3.1.3 Qualitative Data
At the completion of the experiment, I conducted retrospective interviews with
participants from the three treatment groups regarding possible impacts from the film clips and

47

images. The specific questions were: (a) “Do you think that the film clips or images affected
your performance in any of the experimental tasks?” and (b) “How did the content of the film
clips and images make you feel during the experiment?” I present the results for each treatment
group within the following sections. Transcriptions of these reports can be found in Appendix J.
3.1.3.1 Positive Group
Within the Positive group (n = 30), 24% of participants reported experiencing a definite
effect from the emotional stimuli, while 43% felt some effect and 33% reported no effect. 60% of
individuals found the film clips and images distracting from the exposure task, using qualifying
terms and phrases such as “annoying” (105), “kind of strange” (108), and “it threw me off”
(123). No one described their emotional state as “positive” during the induction and only two
participants found the stimuli “arousing” (both males). Three participants (all females) claimed
that the induction material made them feel uncomfortable, with one commenting that “it’s pretty
much like porn and I kind of think porn is gross” (114). These findings, in conjunction with
SAM data, suggest that the emotional stimuli did not positively alter valence levels (although it
did sustain them) nor increase arousal rates for participants within this group.
3.1.3.2 Negative Group
For the Negative group (n = 28; two did not return for the second session), 57% of the
participants experienced a definite effect from the film clips and images, while 25% claimed
some effect. Only 18% felt no effect. 75% of individuals described the stimuli as a distraction
from learning. For example, one participant remarked that, “when they [images] would pop up, I
would forget almost instantly what was just read to me” (213). 57% experienced some type of
negative emotion during the induction, which included feeling “nervous” (201), “uncomfortable”
(217), and “scrambled” (230). One individual claimed that the stimuli made her “sad and not

48

really that excited to do the task” (216). Two participants also directly felt “aroused” by the
content (one male and one female). Interestingly, two participants (both females) thought that
the material helped them to better remember sentences from the exposure set. Combined with
SAM data, I concluded that the negative film clips and images successfully reduced valence
levels and increased arousal rates for participants in this group.
3.1.3.3 Neutral Group
Within the Neutral group (n = 30), 38% of participants reported feeling some effect from
the film clips and images. 62% experienced no effect and 0% claimed a definite effect. Only
28% felt that the stimuli were distracting. Eight participants found the induction material
calming, with one individual commenting that “they were pretty relaxing, so it was kind of chill”
(310). No one reported a change in their emotional state while watching the film clips or images.
Finally, three individuals felt that the material helped them focus better during the exposure
phase. These findings, along with the SAM data, confirmed that the treatment material
maintained participants’ valence and arousal rates at neutral levels, which were comparable to
those from the Comparison group.
3.2 The Role of Emotion in the Learning and Retention of an L2 Syntax
The first RQ focused on the role of positive, negative, and neutral mood states in the
learning and retention of an L2 syntax. Before analyzing results from the immediate and delayed
grammaticality judgment measures, I first examined whether emotionality influenced group
performance during the incidental exposure phase. Measured impacts found at this stage could
offer insight into the relationship between affect and the ability to learn a new, L2 syntax (see
Tobias, 1986). The following analyses address the two main tasks from this period: elicited
imitations and plausibility judgments.

49

3.2.1 Exposure Phase
3.2.1.1 Elicited Imitations
As a component of the incidental exposure requirements, participants from all groups
were afforded only one elicited imitation per sentence from the exposure set (or, 120 total). This
allowed me to measure and compare any possible impacts from affect more directly on learners’
ability to recall the syntax correctly. I awarded one point for every correct verb placement
within a clause (for a maximum score of 200 points; see Section 2.5.3) and subsequently
converted the scores into accuracy rates. Table 11 shows the descriptive statistics for the elicited
imitation performance on total items, plausible/implausible items, and the three target verb
placement patterns.
Table 11
Descriptive Statistics for Elicited Imitations

no.
items
Total Items

120

Plausible Items

60

Implausible Items

60

V2 Pattern

40

VF-V1 Pattern

40

V2-VF Pattern

40

Comparison
Group
(n = 30)
M (SD)
95% CI
91.35 (7.88)
(88.41, 94.29)
91.07 (8.98)
(87.71, 94.42)
91.63 (7.52)
(88.82, 94.44)
94.42 (5.90)
(92.22, 96.62)
85.94 (13.94)
(80.74, 91.14)
95.27 (4.89)
(93.44, 97.10)

Positive
Group
(n = 27)a
M (SD)
95% CI
88.11 (11.44)
(83.59, 92.64)
88.74 (11.59)
(84.16, 93.33)
87.48 (11.58)
(82.90, 92.06)
89.35 (15.36)
(83.28, 95.43)
82.39 (17.67)
(75.40, 89.38)
93.28 (6.58)
(90.67, 95.88)

Negative
Group
(n = 30)
M (SD)
95% CI
88.67 (8.25)
(85.59, 91.75)
88.47 (9.49)
(84.92, 92.01)
89.20 (7.49)
(86.41, 92.00)
94.17 (7.17)
(91.49, 96.85)
81.32 (13.16)
(76.41, 86.24)
93.32 (6.21)
(91.00, 95.64)

Neutral
Group
(n = 30)
M (SD)
95% CI
87.78 (11.58)
(83.46, 92.11)
88.13 (12.04)
(83.64, 92.63)
87.43 (11.67)
(83.08, 91.79)
90.00 (13.36)
(85.01, 94.99)
80.52 (18.48)
(73.62, 87.42)
93.98 (7.17)
(91.30, 96.65)

Note. The scores, rated on a scale of 0-100%, indicate the repetition accuracy of correctly placed
verb patterns from the clauses in the exposure set.
a
Due to equipment malfunction, recordings from three participants were incomplete and their
data were excluded from this analysis.

50

Overall, the Comparison group achieved the highest levels of accuracy with elicited
imitations, outperforming the treatment groups on all measures. This group also recorded the
lowest overall standard deviations from the mean value in each category. Larger standard
deviations within the treatment groups suggest that the emotional stimuli may have affected
individuals differently during this task, potentially helping some and disadvantaging others.
Further analysis using Kruskal-Wallis testing, however, revealed no significant differences
between the groups in terms of total performance, H(3) = 2.30, p = .513, or performance in any
of the three verb placement patterns of: V2, H(3) = 3.42, p = .331; VF-V1, H(3) = 2.00, p = .394;
or V2-VF, H(3) = 2.32, p = .508. The four groups performed equally on both the plausible
sentences, H(3) = 1.95, p = .583, and implausible sentences, H(3) = 2.72, p = .437. Finally, all
groups exhibited similarly higher accuracy levels while repeating the V2 and V2-VF verb
patterns. I attribute lower accuracies for the VF-V1 verb pattern to longer average sentence
length and greater syntactic complexity.
In addition to comparing between-group performance, I also analyzed within-group
elicited imitation performance for all 120 sentences from the exposure set. Figure 6 graphically
depicts the groups’ repetition accuracies of this entire set, divided into 24 chronological stages.
Friedman’s testing indicated no significant differences in performance accuracy for the
Comparison group, χ2(23) = 25.16, p = .342, and Neutral group, χ2(23) = 19.76, p = .657,
throughout the experiment. Near-significant differences, however, were recorded for the
Positive group, χ2(23) = 34.25, p = .062, and Negative group, χ2(23) = 34.22, p = .062. These
findings suggest that participants in the neutral conditions exhibited a generally stable
performance overall, whereas participants exposed to positive or negative stimuli performed
somewhat erratically over time.

51

Repetition Accuracy

100%
80%
60%
40%
20%
0%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Comparison Group

Positive Group

Negative Group

Neutral Group

Figure 6. Repetition accuracy of the correct verb forms for all 120 sentences from the exposure
set across 24 chronological stages. Each stage represents the mean accuracy score of five
sentences.
Next, I analyzed elicited imitation performance for the three verb patterns separately.
These data were all measured over 20 chronological stages. Figure 7 illustrates the results for
the V2 verb pattern. Friedman’s testing indicated no significant changes in performance for any
group, with the results of this analysis as follows: Comparison group, χ2(19) = 19.83, p = .405;
Positive group, χ2(19) = 23.74, p = .206; Negative group, χ2(19) = 25.54, p = .144; Neutral
group, χ2(19) = 9.18, p = .970. Here, all groups maintained a high level of consistency while
eliciting the V2 verb pattern with no signs of interference from the emotional induction.

52

Repetition Accuracy

100%
80%
60%
40%
20%
0%
1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20

Comparison Group

Positive Group

Negative Group

Neutral Group

Figure 7. Repetition accuracy of the V2 verb pattern for all 40 sentences from the exposure set
across 20 chronological stages. Each stage represents the mean accuracy score of two
sentences.
For the VF-V1 verb pattern (Figure 8), I found no significant differences across the
chronological stages for the Comparison group, χ2(19) = 27.31, p = .098, Positive group, χ2(19) =
19.15, p = .447, or Neutral group, χ2(19) = 15.75, p = .674. Although this verb pattern was the
most difficult to reproduce (per mean accuracy scores), participants from the three groups still
performed uniformly over time. Conversely, the Negative group, χ2(19) = 42.09, p = .002,
registered inconsistencies in performance that were significant across time. The results suggest
that exposure to negative stimuli hindered the processing and repetition of the most complex
grammatical structure from the L2 system.

53

Repetition Accuracy

100%
80%
60%
40%
20%
0%
1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20

Comparison Group

Positive Group

Negative Group

Neutral Group

Figure 8. Repetition accuracy of the VF-V1 verb pattern for all 40 sentences from the exposure
set across 20 chronological stages. Each stage represents the mean accuracy score of two
sentences.
Lastly, Friedman’s testing of the V2-VF verb pattern (Figure 9) indicated no significant
differences in performance over the 20 stages for any group. The results were: Comparison
group, χ2(19) = 25.85, p = .134; Positive group, χ2(19) = 18.46, p = .492; Negative group, χ2(19)
= 21.74, p = .298; Neutral group, χ2(19) = 27.50, p = .094. As with the V2 form, which shared
almost equally high rates of elicitation accuracy (see Table 11), there appeared to be no
detrimental effects from the emotional induction.

54

Repetition Accuracy

100%
80%
60%
40%
20%
0%
1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20

Comparison Group

Positive Group

Negative Group

Neutral Group

Figure 9. Repetition accuracy of the V2-VF verb pattern for all 40 sentences from the exposure
set across 20 chronological stages. Each stage represents the mean accuracy score of two
sentences.
3.2.1.2 Plausibility Judgments
The second task from the incidental exposure phase required participants to correctly rate
sentences from the exposure set as either plausible or implausible. The descriptive statistics in
Table 12 indicated that the Comparison and Positive groups scored the highest on this activity.
Kruskal-Wallis testing, however, revealed no significant between-group differences in
performance for total sentences, H(3) = 4.39, p = .222, or for the separate plausible, H(3) = 4.21,
p = .240, and implausible items, H(3) = 4.21, p = .240. These findings suggest that all
participants performed with equal accuracy, with no measured impacts from the emotional
stimuli. Wilcoxon signed ranks testing showed that the Comparison group, z = -0.38, p = .706, r
= -.05, Negative group, z = -0.29, p = .776, r = -.04, and Neutral group, z = -0.51, p = .611, r = .07, displayed similar accuracy rates among both the plausible and implausible sentences. The

55

Positive group, z = -2.56, p = .010, r = -.49, was significantly better at categorizing implausible
sentences than plausible ones.
Table 12
Descriptive Statistics for Plausibility Judgements

Total Items
Plausible Items
Implausible Items

Comparison
Group
(n = 27)a
M (SD)
95% CI
90.78 (8.19)
(87.54, 94.02)
90.98 (14.00)
(85.45, 96.52)
90.55 (10.50)
(86.40, 94.71)

Positive
Group
(n = 27)b
M (SD)
95% CI
91.08 (6.33)
(88.58, 93.59)
87.28 (13.08)
(82.11, 92.45)
94.87 (4.06)
(93.27, 96.48)

Negative
Group
(n = 30)
M (SD)
95% CI
88.92 (7.24)
(86.21, 91.62)
88.89 (10.83)
(84.84, 92.93)
88.94 (10.71)
(84.94, 92.94)

Neutral
Group
(n = 30)
M (SD)
95% CI
87.08 (9.76)
(83.43, 90.73)
84.39 (20.28)
(76.82, 91.96)
89.78 (10.09)
(86.02, 93.55)

Note. The scores, rated on a scale of 0-100%, indicate the accuracy of correctly identifying
sentences in the exposure set as either plausible or implausible.
a
Scores were removed for three participants that achieved less than 50% accuracy on either the
plausible or implausible judgements. Here, the individuals likely overemphasized the elicited
imitation task at the expense of the plausibility judgment task.
b
Due to equipment malfunction, plausibility judgements from three participants were incomplete
and their data were excluded from this analysis.
3.2.2 Testing Phase
In order to determine if positive, negative, or neutral mood states affected the learning
and retention of an L2 syntax, I analyzed data from both the immediate and two-week delayed
GJTs. The first section addresses whether participants learned the syntax (i.e., immediate
posttest) and the second section focuses on the retention and consolidation of that knowledge
(i.e., delayed posttest). The final section examines the relationship in performance over time
between the two testing periods.
3.2.2.1 Overall Performance, Immediate Grammaticality Judgments
Based upon the descriptive statistics from the immediate grammaticality judgment
posttest (see Table 13), participants within the Positive, Negative, and Neutral groups performed

56

at higher accuracy rates than those from the Comparison group. Higher standard deviations
within the Positive and Negative treatment groups (over 1.5 times greater than the Comparison
group) suggest that the mood induction may have affected participants differently in these
groups. Further analysis, using one-sample t tests, revealed that all groups performed
significantly better than chance. I also measured no differences between the four groups in terms
of overall accuracy, Welch’s F(3, 62.44) = 1.14, p = .339, ω2 = 0.00. This means that
participants generally showed a learning effect towards the L2 syntax immediately after
exposure, despite the presence of emotional influencers.
Table 13
Grammaticality Judgement Accuracies, Immediate Posttest
Mean Difference from
Chance (50%)
Group
N
M (SD)
95% CI
t
p
r
Comparison
30
52.45 (4.21)
(50.88, 54.02)
3.19
.003
.51
Positive
30
54.94 (7.23)
(52.24, 57.64)
3.74
.001
.57
Negative
30
54.45 (7.32)
(51.71, 57.18)
3.33
.002
.53
Neutral
29
53.39 (4.81)
(51.56, 55.22)
3.80
.001
.58
Note. The scores, rated on a scale of 0-100%, indicate the accuracy of correctly identifying
sentences in the testing set as either grammatical or ungrammatical. Scores ±3 standard
deviations were removed prior to analysis.
Next, I analyzed how each group performed over the course of the immediate posttest.
Figure 10 graphically displays the groups’ scoring performance over ten chronological stages.
Results from one-factor, repeated measures ANOVAs (with sphericity assumed), indicated no
learning effects throughout the posttest for the Comparison group, F(9, 261) = 0.71, p = .702, ηp2
= .02, Positive group, F(9, 261) = 0.41, p = .929, ηp2 = .01, and Neutral group, F(9, 252) = 0.58,
p = .810, ηp2 = .02. The Negative group, however, did measure a significant learning effect, F(9,
261) = 2.14, p = .027, ηp2 = .07, over time. According to Figure 10, the learning effect was

57

negative, meaning participants from this group performed better at the start of the grammaticality

Grammaticality Judgement Accuracy

judgment task than at the end.
100%
80%
60%
40%
20%
0%
1

2

3

4

5

6

7

Comparison Group

Positive Group

Negative Group

Neutral Group

8

9

10

Figure 10. Grammaticality judgement accuracy for all 60 testing sentences across 10
chronological stages. Each stage represents the mean accuracy of six scores.
Thirdly, I converted the accuracy scores into d prime scores for each group to measure
how well participants discriminated the grammatically correct sentences from the ungrammatical
ones (see Figure 11). Table 14 shows that all groups achieved positive d prime scores. There
were no significant differences between groups, Welch’s F(3, 62.15) = 1.27, p = .294, ω2 = 0.01,
although the three treatment groups recorded the highest performances. The four mean scores
were also significantly above chance (zero). These results, especially in concert with the
accuracy scores from Table 13, confirm that incidental exposure facilitated the learning of the L2
syntax, regardless of mood state.

58

1.50

d Prime Score

1.00

0.50
0.00

-0.50
-1.00
-1.50

Comparison
Group

Positive
Group

Negative
Group

Neutral
Group

Figure 11. The d prime scores from the immediate grammaticality judgement posttest, with zero
representing chance discrimination. Scores ±3 standard deviations were removed. One dot
equals one participant.
Table 14
D Prime Scores for Grammaticality Judgement Task, Immediate Posttest
Mean Difference from
Zero
Group
N
M (SD)
95% CI
t
p
r
Comparison
29
0.15 (0.23)
(0.06, 0.24)
3.43
.002
.54
Positive
30
0.30 (0.40)
(0.15, 0.44)
4.08
<.001
.60
Negative
30
0.26 (0.42)
(0.11, 0.42)
3.50
.002
.54
Neutral
29
0.20 (0.28)
(0.10, 0.31)
3.96
<.001
.60
Note. Scores ±3 standard deviations were removed prior to analysis.
Lastly, I examined the endorsement ratings for each verb pattern presented in the GJT.
For the three grammatical patterns, results from one-sample Wilcoxon signed rank testing
indicated that all groups endorsed the V2-VF and VF-V1 grammatical verb patterns at rates
significantly above chance, with all ps <.050. This was not the case for the grammatical V2 verb
pattern, however, which was only endorsed at chance levels (all ps >.096). The finding is quite
odd, considering that all groups achieved highly accurate elicited imitation rates of this structure

59

during the exposure phase. To further inspect this phenomenon, I equally divided the ten V2
sentences by their specific structure (i.e., those with a pre-verbal subject (SV) and those with a
post-verbal subject (VS); see Tables 3 and 4 in Section 2.3 for examples). For balance, I also
separated the V2-VF sentences in a similar manner (i.e., V2(SV)-VF and V2(VS)-VF). I then
graphed the endorsement ratings for each of the eleven verb patterns, which are found in Figure
12. Descriptive statistics from Table 15 reveal that the four groups endorsed each verb pattern
similarly. Kruskal-Wallis testing confirmed this assessment, finding no significant differences
between groups for any syntactic structure, with all ps >.122, except for the trend in *V3, H(3) =
6.95, p = .074.
With respect to the grammatical structures, Wilcoxon signed rank testing indicated that
the Comparison, Negative, and Neutral groups endorsed the V2(VS) verb pattern and all groups
endorsed the V2(VS)-VF and VF-V1 verb patterns at rates significantly above chance. This was
not the case for the grammatical V2(SV) and V2(SV)-VF verb patterns, though, which were only
endorsed at chance levels or outright rejected as part of the new syntax. The findings point to a
near-universal perception of post-verbal subject (VS) and VF structures as essential
characteristics of the L2 grammatical system. This may also explain the high endorsement rates
for the ungrammatical verb patterns of *V1 (apart from the Positive group), *VF, and *V1-VF,
which all possess VS and VF components. However, as *V4 sentences were also highly
endorsed, it appears that participants have not yet developed a complete knowledge of the role of
verb placement within the L2 syntax.

60

Endorsement Rate

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Comparsion Group

Positive Group

Negative Group

Neutral Group

Figure 12. Endorsement ratings for each verb pattern from the immediate GJT. Ungrammatical
verb patterns are marked with an asterisk. For the Comparison, Positive, and Negative groups, n
= 30; for the Neutral group, n = 29. Error bars represent ±1 SEM.
Table 15
Descriptive Statistics and Accuracy of Verb Pattern Endorsement Ratings, Immediate Posttest

Verb Pattern
V2(SV)
V2(VS)
V2(SV)-VF
V2(VS)-VF
VF-V1
*V1
*V3

Comparison
Group
(n = 30)
M (SD)
95% CI
47.33 (30.39)
(35.98, 58.68)
65.33* (30.14)
(54.08, 76.59)
54.67 (30.14)
(43.41, 65.92)
82.67*** (24.49)
(73.52, 91.81)
78.33*** (25.47)
(68.82, 87.85)
66.00* (33.28)
(53.57, 78.43)
21.33*** (31.04)
(9.74, 32.93)

Positive
Group
(n = 30)
M (SD)
95% CI
30.67** (27.16)
(20.53, 40.81)
54.00 (32.86)
(41.73, 66.27)
54.67 (28.25)
(44.12, 65.22)
86.67*** (16.88)
(80.36, 92.97)
79.67*** (19.21)
(72.50, 86.84)
60.67 (29.93)
(49.49, 71.85)
6.00*** (11.92)
(1.55, 10.45)

61

Negative
Group
(n = 30)
M (SD)
95% CI
36.67* (31.55)
(24.89, 48.45)
64.00** (24.86)
(54.72, 73.28)
51.33 (28.62)
(40.65, 62.02)
84.67*** (14.56)
(79.23, 90.10)
74.67*** (20.63)
(66.96, 82.37)
64.67* (30.48)
(53.28, 76.05)
19.33*** (30.39)
(7.99, 30.68)

Neutral
Group
(n = 29)
M (SD)
95% CI
31.74*** (22.37)
(23.21, 40.23)
71.03*** (23.66)
(62.04, 80.03)
49.66 (33.22)
(37.02, 62.29)
84.14*** (25.29)
(74.52, 93.76)
78.28*** (21.72)
(70.01, 86.54)
66.90* (33.92)
(53.99, 79.80)
7.59*** (13.54)
(2.44, 12.74)

Table 15 (cont’d)

Verb Pattern
*V4
*VF
*V1-VF
*VF-V2(SV)

Comparison
Group
(n = 30)
M (SD)
95% CI
73.33*** (24.82)
(64.07, 82.60)
80.67*** (23.18)
(72.01, 89.32)
78.00*** (26.96)
(67.93, 88.07)
58.00 (35.76)
(44.65, 71.35)

Positive
Group
(n = 30)
M (SD)
95% CI
65.33** (25.15)
(55.94, 74.73)
70.67** (27.16)
(60.53, 80.81)
76.00*** (23.72)
(67.14, 84.86)
45.33 (33.19)
(32.94, 57.73)

Negative
Group
(n = 30)
M (SD)
95% CI
68.00** (31.34)
(56.30, 79.70)
64.67* (29.09)
(53.80, 75.53)
70.00** (28.65)
(59.30, 80.70)
44.67 (32.67)
(32.47, 56.87)

Neutral
Group
(n = 29)
M (SD)
95% CI
66.90* (32.19)
(54.65, 79.14)
75.17*** (22.46)
(66.63, 83.72)
74.48*** (27.72)
(63.94, 85.03)
61.38 (33.78)
(48.53, 74.23)

Note. The scores, rated on a scale of 0-100%, indicate the endorsement ratings for each verb
pattern from the immediate GJT. Ungrammatical verb patterns are marked with an asterisk. SV
= subject-verb; VS = verb-subject. Significance from chance (50%) is *p <.05, **p <.01, ***p
<.001.
3.2.2.2 Overall Performance, Delayed Grammaticality Judgments
In this section, I report on whether participants from the four groups successfully retained
their knowledge from incidental exposure of the L2 syntax. After two weeks (with no additional
exposure to the grammatical verb patterns), I administered a delayed GJT to measure group
performance. All participants, except for two from the Negative group, returned for this
assessment.5 Table 16 displays the mean accuracy results from this posttest, with the highest
scores registered by the Positive group, followed by the Comparison and Neutral groups, and
finally the Negative group. Higher standard deviations within the three treatment groups may be
the result of residual affective impacts on learning (either positive or negative) encountered
during the initial exposure phase. While I found no differences in scoring between the groups,
F(3, 114) = 0.35, p = .787, ω2 = -0.02, only the Comparison, Positive, and Neutral groups

5

Two participants from the Negative group (one male and one female) did not return for the
delayed portion of the experiment due to scheduling conflicts. Both achieved a 60% accuracy
rating on the immediate GJT.
62

performed significantly above chance. This suggests that participants from these three groups
maintained their knowledge of the L2 syntax over time (as measured by total accuracy).
Individuals from the Negative group, however, failed in this endeavor, scoring at the chance
level. I also examined if any learning occurred over the course of the delayed posttest by
dividing group performance into ten chronological stages. Results from one-factor, repeated
measures ANOVAs (with sphericity assumed), found that all groups performed consistently
throughout the test, with all ps >.183.
Table 16
Grammaticality Judgement Accuracies, Delayed Posttest
Mean Difference from
Chance (50%)
Group
N
M (SD)
95% CI
t
p
r
Comparison
30
53.84 (5.96)
(51.61, 56.06)
3.53
.001
.55
Positive
30
54.72 (7.49)
(51.93, 57.52)
3.45
.002
.54
Negative
28
52.63 (8.45)
(49.35, 55.91)
1.65
.111
.30
Neutral
30
53.50 (9.17)
(50.08, 56.92)
2.09
.045
.36
Note. The scores, rated on a scale of 0-100%, indicate the accuracy of correctly identifying
sentences in the testing set as either grammatical or ungrammatical. Scores ±3 standard
deviations were removed.
Analysis of group d prime scores revealed similarities to the total accuracy performances
found in Table 16. Data depicted in Figure 13 and Table 17 show participants within the
Positive group as the best discriminators of grammatical and ungrammatical sentences, followed
by the Comparison and Neutral groups, and then the Negative group. Although significant group
differences did not emerge, F(3, 114) = 0.37, p = .777, ω2 = -0.02, those in the Comparison,
Positive, and Neutral groups performed significantly above chance, suggesting knowledge of the
L2 grammatical structures was retained. The Negative group, however, failed to discriminate
between grammatical and ungrammatical sentences (at chance levels), signifying a diminished

63

learning effect over time. The relationship between immediate and delayed posttest
performances are discussed in Section 3.2.2.3.
1.50

d Prime Score

1.00
0.50
0.00
-0.50
-1.00
-1.50

Comparison
Group

Positive
Group

Negative
Group

Neutral
Group

Figure 13. The d prime scores from the delayed grammaticality judgement posttest, with zero
representing chance discrimination. For the Comparison, Positive, and Neutral groups, n = 30;
for the Negative group, n = 28. Scores ±3 standard deviations were removed. One dot equals
one participant.
Table 17
D Prime Scores for Grammaticality Judgement Task, Delayed Posttest
Mean Difference from
Zero
Group
N
M (SD)
95% CI
t
p
r
Comparison
30
0.22 (0.33)
(0.10, 0.35)
3.65
.001
.56
Positive
30
0.26 (0.40)
(0.12, 0.41)
3.63
.001
.56
Negative
28
0.15 (0.45)
(-0.03, 0.32)
1.73
.095
.32
Neutral
30
0.21 (0.50)
(0.02, 0.40)
2.31
.028
.39
Note. Scores ±3 standard deviations were removed.
Next, I examined the endorsement ratings of all eleven verb patterns (graphed in Figure
14) from the delayed GJT. The descriptive statistics, found in Table 18, summarize the different
performances per group. For the grammatical verb patterns, all endorsed the V2(VS)-VF and

64

VF-V1 patterns at similarly high rates and significantly above chance, showing positive retention
of the target structures. This was not the case for the V2(VS) pattern, which was endorsed
significantly above chance by the Comparison group, but only at chance levels by the Positive,
Negative, and Neutral groups. Here, participants in the Negative and Neutral groups displayed a
reduction in knowledge of this structure from the immediate to delayed GJT. I also measured a
significant difference between-groups for the V2(VS) pattern, H(3) = 11.02, p = .012. Post-hoc
analysis, with Bonferroni correction (α = .008), found a significant separation between the
Comparison and Negative groups, z = -3.21, p = .001, and near-significant difference between
the Comparison and Positive groups, z = -2.62, p = .009. Finally, all groups remained skeptical
of the grammatical patterns which contained pre-verbal subject components, and endorsed them
at levels significantly below chance (V2(SV)) or at chance (V2(SV)-VF).
Regarding the ungrammatical verb forms, the four groups showed similar endorsement
ratings for the *V1, *V3, *V4, and *VF-V2 patterns, with all ps >.104. More specifically,
endorsements dropped to at-chance levels for both the *V1 (minus the Comparison group) and
*V4 (except the Comparison and Positive groups) forms. This means that non-target-like
knowledge was not consolidated for these specific ungrammatical items by the treatment groups.
Endorsement rates of the *V3 (categorical rejection) and *VF-V2 verb patterns (at-chance
levels) remained steady compared to the immediate posttest results. Lastly, all groups continued
to highly endorse the *VF and *V1-VF patterns, indicating an incomplete understanding of how
verb-final clauses functioned in the L2 syntax and an acceptance of the VS component as an
indicator of grammaticality in complex sentences. Interestingly, significant differences betweengroups emerged with the two patterns during this posttest. For the *VF sentences, H(3) = 7.85, p
= .045, I found a near-significant separation (with α adjusted to .008) between the Comparison

65

and Positive groups, z = -2.54, p = .011. Analysis of the *V1-VF form, H(3) = 13.97, p = .003,
revealed that the Positive group endorsed this pattern the most and at a near-categorical level of
91%. This rating was significantly higher than the Negative, z = -3.43, p = .001, and Neutral
groups, z = -3.24, p = .001, and at a near-significant level to the Comparison group, z = -2.23, p

Endorsement Rate

= .026.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

Comparsion Group

Positive Group

Negative Group

Neutral Group

Figure 14. Endorsement ratings for each verb pattern from the delayed GJT. Ungrammatical
verb patterns are marked with an asterisk. For the Comparison, Positive, and Neutral groups, n =
30; for the Negative group, n = 28. Error bars represent ±1 SEM.
Table 18
Descriptive Statistics and Accuracy of Verb Pattern Endorsement Ratings, Delayed Posttest

Verb Pattern
V2(SV)
V2(VS)
V2(SV)-VF

Comparison
Group
(n = 30)
M (SD)
95% CI
28.00*** (25.52)
(18.47, 37.53)
76.00*** (25.41)
(66.51, 85.49)
53.33 (28.45)
(42.71, 6.96)

Positive
Group
(n = 30)
M (SD)
95% CI
23.33*** (22.94)
(14.77, 31.90)
54.00 (32.86)
(41.73, 66.27)
42.67 (27.66)
(32.34, 53.00)

66

Negative
Group
(n = 28)
M (SD)
95% CI
21.43*** (19.57)
(13.84, 29.02)
51.43 (27.98)
(40.58, 62.28)
44.29 (37.46)
(29.76, 58.81)

Neutral
Group
(n = 30)
M (SD)
95% CI
29.33** (28.64)
(18.64, 40.03)
62.67 (35.13)
(49.55, 75.78)
48.67 (30.93)
(37.12, 60.22)

Table 18 (cont’d)

Verb Pattern
V2(VS)-VF
VF-V1
*V1
*V3
*V4
*VF
*V1-VF
*VF-V2(SV)

Comparison
Group
(n = 30)
M (SD)
95% CI
84.00*** (25.94)
(74.31, 93.69)
80.67*** (20.50)
(73.01, 88.32)
67.33** (31.29)
(55.65, 79.02)
9.33*** (17.21)
(2.91, 15.76)
67.33** (31.72)
(55.49, 79.18)
80.00*** (27.29)
(69.81, 90.19)
78.67*** (25.69)
(69.07, 88.26)
53.33 (33.36)
(40.88, 65.79)

Positive
Group
(n = 30)
M (SD)
95% CI
88.00*** (16.27)
(81.92, 94.08)
83.33*** (22.34)
(74.99, 91.67)
56.00 (32.12)
(44.01, 67.99)
2.00*** (8.05)
(-1.01, 5.01)
64.00* (32.97)
(51.69, 76.31)
65.33* (29.68)
(54.25, 76.42)
90.67*** (20.83)
(82.89, 98.45)
40.67 (35.81)
(27.30, 54.04)

Negative
Group
(n = 28)
M (SD)
95% CI
82.14*** (21.32)
(73.88, 90.41)
73.57** (27.38)
(62.96, 84.19)
55.00 (35.54)
(41.22, 68.78)
9.29*** (22.76)
(0.46, 18.11)
54.29 (32.14)
(41.82, 66.75)
77.14*** (30.65)
(65.26, 89.03)
69.29** (29.56)
(57.83, 80.75)
50.00 (31.51)
(37.78, 62.22)

Neutral
Group
(n = 30)
M (SD)
95% CI
78.00*** (23.69)
(69.15, 86.85)
71.33** (28.62)
(60.65, 82.02)
60.67 (34.23)
(47.88, 73.45)
7.33*** (14.37)
(1.97, 12.70)
60.67 (30.84)
(49.15, 72.18)
66.00* (31.58)
(54.21, 77.79)
73.33*** (25.91)
(63.66, 83.01)
51.33 (35.89)
(37.93, 64.73)

Note. The scores, rated on a scale of 0-100%, indicate the endorsement ratings for each verb
pattern from the delayed GJT. Ungrammatical verb patterns are marked with an asterisk. SV =
subject-verb; VS = verb-subject. Significance from chance (50%) is *p <.05, **p <.01, ***p
<.001.
3.2.2.3 Relationship between the Immediate and Delayed GJT Performances
To analyze the association between immediate and delayed GJT performances, I
conducted two measures: (a) a correlation between the two posttest scores for each group and (b)
mixed-design ANOVAs for both the accuracy rates and d prime scores. Results from the
correlations, shown in Figure 15, reveal that individuals from the Positive, r = .451, p = .012, and
Negative, r = .536, p = .003, groups (and to a lesser extent, the Neutral group, r = .321, p = .089)
were more likely to replicate their immediate GJT performance on the delayed posttest.
Alternatively, participants from the Comparison group, r = .069, p = .716, were more inclined to
score closer to the group mean of 53.84% on the delayed posttest, regardless of their immediate

67

GJT performance.

Figure 15. Scatterplot of correlations between immediate and delayed GJT performance by
group.
From a more general perspective, mixed-design ANOVAs indicated no within-group
differences in scoring between accuracy rates, F(1, 113) = .08, p = .772, ηp2 = .00, and d prime
scores, F(1, 112) = .31, p = .577, ηp2 = .00, over the two-week time span. These findings are
promising and confirm the effectiveness and durability of incidental exposure, particularly in the
face of different emotional distractors.
3.2.3 Summary of RQ1
In sum, participants subjected to positive, negative, and neutral emotional induction
displayed aspects of learning a novel L2 syntax to which they were exposed incidentally in a
meaning-focused task. After two weeks, and with no additional exposure to the L2, only

68

individuals from the Positive and Neutral group successfully retained their knowledge of the
grammatical structure. Table 19 provides a synopsis of the results.
Table 19
Summary of Findings for RQ1
Comparison
Group

Positive
Group

Negative
Group

Neutral
Group

Total elicited imitation
accuracy

91.35%

88.11%

88.67%

87.78%

Total plausibility judgment
accuracy

90.78%

91.08%

88.92%

87.08%

Accuracy/significance above
chance (50%)

52.45%
p = .003

54.94%
p = .001

54.45%
p = .002

53.39%
p = .001

D prime/significance above
chance (0)

0.15
p = .002

0.30
p <.001

0.26
p = .002

0.20
p <.001

Grammatical verb patterns
endorsed significantly above
chance (50%)

V2(VS),
(V2)VS-VF,
VF-V1

(V2)VS-VF,
VF-V1

V2(VS),
(V2)VS-VF,
VF-V1

V2(VS),
(V2)VS-VF,
VF-V1

Ungrammatical verb patterns
endorsed significantly above
chance (50%)

*V1, *V4,
*VF, *V1-VF

*V4, *VF,
*V1-VF

*V1, *V4,
*VF, *V1-VF

*V1, *V4,
*VF, *V1-VF

Accuracy/significance above
chance (50%)

53.84%
p = .001

54.72%
p = .002

52.63%
p = .111

53.50%
p = .045

D prime/significance above
chance (0)

0.22
p = .001

0.26
p = .003

0.15
p = .095

0.21
p = .028

Grammatical verb patterns
endorsed significantly above
chance (50%)

V2(VS),
(V2)VS-VF,
VF-V1

(V2)VS-VF,
VF-V1

(V2)VS-VF,
VF-V1

(V2)VS-VF,
VF-V1

Ungrammatical verb patterns
endorsed significantly above
chance (50%)

*V1, *V4,
*VF, *V1-VF

*V4, *VF,
*V1-VF

*VF, *V1-VF

*VF, *V1-VF

Exposure

Immediate GJT

Delayed GJT

69

Although the Negative group did not perform above chance on the delayed posttest in
terms of total accuracy and grammatical/ungrammatical discrimination, there are two caveats to
this finding that must be addressed. First, two participants from the Negative group, both of
whom achieved a 60% accuracy rate on the immediate GJT, did not return for the delayed
posttest. While I can only speculate as to whether their delayed GJT performances would have
raised the Negative group’s scores significantly, correlation results from Figure 15 make the
scenario more probable than not. Secondly, mixed-design ANOVAs revealed no within-group
differences in scoring between the two measures over the two-week time span. Thus, this
analysis did not support the view that participants from the Negative group, or indeed any
treatment group, forgot significant amounts of their initial knowledge of the L2 syntax over time.
Therefore, the within-group ANOVAs, combined with attrition in the Negative group, cast some
doubt on whether retention in the Negative group was truly impaired. The results are best
characterized as tenuous and deserving of further inspection. That said, future discussion of this
topic (see Section 4.2) will focus on the possible reasons for the decline in performance, which is
still the empirical finding from the study.
3.3 Emotions and the Implicit Acquisition of an L2 Syntax
RQ2 inquired if participants in positive, negative, or neutral emotional states could
acquire the grammar system of a novel L2 implicitly. The following analyses were based
primarily on source attribution data (i.e., guess, intuition, recollection, and rule knowledge) from
both the immediate and delayed GJTs, as well as post-experiment verbal reports.
3.3.1 Proportions and Accuracies of Source Attributions, Immediate Posttest
Source attribution proportions from the immediate posttest, displayed in Figure 16, show
how each group classified their grammaticality judgments. In order to further examine these

70

relationships, I developed an explicit-to-implicit knowledge ratio for each participant based on
the proportion data. The calculated means (SD) of the four experimental groups were: (a)
Comparison group, M = 5.19 (10.84); (b) Positive group, M = 1.76 (1.74); (c) Negative group, M
= 3.19 (6.19); and (d) Neutral group, M = 3.87 (6.13). Using a Kruskal-Wallis test, I discovered
no between-group difference among the ratios, H(3) = 3.72, p = .294. However, one-sample
Wilcoxon signed rank tests (with a test value of 1), indicated nuances in how each group relied
on the two source attribution types. Here, the ratios of the Comparison group (p = .001) and
Neutral group (p = .003) were significantly higher than the test value. These participants, then,
relied more on their perceived, explicit structural knowledge of the L2 syntax to navigate the
immediate posttest. The Positive group (p = .074) and the Negative group (p = .082) ratios,
however, were not significantly different from the test value, suggesting an almost equal use of

Proportion of Source Attributions

explicit and implicit attributions when determining grammaticality responses.
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

61

39

Comparison Group

54

55

46

45

Positive Group

Negative Group

Implicit Knowledge

61

39

Neutral Group

Explicit Knowledge

Figure 16. Proportion of selected source attributions from the immediate GJT. Implicit
knowledge underlies the subjective attributions of guess and intuition, whereas explicit
knowledge is derived from recollection and rule knowledge. For the Comparison, Positive, and
Negative groups, n = 30; for the Neutral group, n = 29.

71

Table 20 provides group accuracy ratings for the two categories of source attributions
during the immediate posttest. According to one-sample Wilcoxon signed rank tests, all groups
performed significantly above chance when utilizing explicit source attributions, meaning that all
groups acquired explicit structural knowledge of the L2 grammar system. Apart from a nearsignificant performance by the Positive group, no group was accurate above chance when basing
their decisions on implicit structural knowledge. These findings suggest that participants from
all groups, regardless of mood state, did not acquire implicit structural knowledge of the L2
syntax.
Table 20
Grammaticality Judgment Accuracies per Source Attribution, Immediate Posttest
Mean Difference
Mean Difference
Implicit
from Chance
Explicit
from Chance
Knowledge
(50%)
Knowledge
(50%)
Group
M (SD)
z, p
M (SD)
z, p
Comparison 48.97 (18.25)
-.55, .581
55.22 (8.87)
3.34, .001
Positive
53.54 (9.86)
1.82, .069
57.15 (9.87)
3.24, .001
Negative
54.68 (15.06)
1.61, .108
58.92 (12.78)
3.44, .001
Neutral
49.05 (14.08)
.05, .959
57.83 (9.83)
4.33, <.001
Note. The scores, rated on a scale of 0-100%, indicate the accuracy ratings for each source
attribution from the immediate GJT. Guess and intuition are implicit attributions, whereas
recollection and rule knowledge are explicit attributions. For the Comparison, Positive, and
Negative groups, n = 30; for the Neutral group, n = 29.
While not reaching the level of significance, proportion data (Figure 16) and accuracy
data (Table 20) suggested that participants from the Positive and Negative groups utilized more
implicit source attributions than those from the Comparison and Neutral groups. To explore this
finding further, I examined group proportion data for each verb pattern to identify whether any
individual structures were chiefly guided by implicit knowledge. Table 21 shows the results
from binomial logistic regression using GEE, which modeled the odds of an explicit response
over an implicit response. Here, the verb patterns of V2(VS), V2(VS)-VF, VFV1, *V3, *VF,

72

and *V1VF were driven primarily by explicit knowledge, whereas the remaining structures were
equally divided between implicit and explicit knowledge use. While all treatment group Wald
chi-square values were similar to their respective intercept values, I did record a few nearsignificant differences. These included three verb patterns from the Positive group, V2(SV), p
= .069; *V1, p = .065; and *VF, p = .063, and one from the Negative group, *VF, p = .068.
Proportion data for these specific structures indicated a preference for guessing and intuition
only by the Positive group when determining GJT responses for the V2(SV) form (56% of the
time) and *V1 form (63% of the time).
Table 21
Explicit Source Attribution Use by Verb Pattern, Immediate Posttest
Intercept
Verb Pattern
V2(SV)
V2(VS)
V2(SV)-VF
V2(VS)-VF
VF-V1
*V1
*V3
*V4
*VF
*V1-VF
*VF-V2(SV)

1.80
1.34 (0.87, 2.07)
4.89*
1.78 (1.07, 2.96)
1.35
1.31 (0.83, 2.06)
6.57**
1.83 (1.15, 2.91)
4.79*
1.68 (1.06, 2.67)
0.21
1.11 (0.71, 1.75)
7.35**
2.00 (1.21, 3.30)
0.10
1.08 (0.65, 1.80)
8.77**
2.06 (1.28, 3.33)
4.06*
1.68 (1.01, 2.78)
1.53
1.38 (0.83, 2.30)

Positive Group
Negative Group
Wald χ2
Exp(B) (95% CI)
3.30
0.49
0.59 (0.33, 1.04)
0.81 (0.44, 1.48)
1.86
1.08
0.63 (0.32, 1.23)
0.70 (0.35, 1.38)
0.07
0.03
1.09 (0.58, 2.02)
0.95 (0.49, 1.84)
0.07
0.14
0.92 (0.49, 1.73)
0.89 (0.49, 1.63)
0.38
0.24
0.83 (0.47, 1.49)
0.86 (0.46, 1.59)
3.40
0.16
0.54 (0.28, 1.04)
0.88 (0.46, 1.67)
0.01
0.43
0.97 (0.50, 1.88)
1.29 (0.61, 2.72)
0.60
2.18
0.77 (0.39, 1.50)
0.58 (0.28, 1.19)
3.47
3.32
0.55 (0.30, 1.03)
0.55 (0.29, 1.05)
0.81
1.70
0.74 (0.38, 1.43)
0.65 (0.33, 1.25)
0.17
1.12
0.87 (0.45, 1.68)
0.69 (0.34, 1.38)

Neutral Group

0.03
1.06 (0.53, 2.09)
0.16
0.87 (0.43, 1.73)
0.03
1.06 (0.54, 2.06)
0.26
1.20 (0.60, 2.40)
0.50
1.27 (0.66, 2.44)
1.06
1.43 (0.73, 2.80)
0.03
0.94 (0.45, 1.96)
0.10
1.11 (0.57, 2.20)
1.41
0.67 (0.35, 1.30)
0.79
0.74 (0.38, 1.44)
0.06
1.09 (0.54, 2.17)

Note. Ungrammatical verb patterns are marked with an asterisk. *p <.05, **p <.01, ***p <.001.

73

3.3.2 Proportions and Accuracies of Source Attributions, Delayed Posttest
Figure 17 summarizes the source attribution proportions measured at the delayed posttest.
Again, I analyzed the explicit-to-implicit knowledge ratios for each group and arrived at the
following mean (SD) values: (a) Comparison group, M = 2.90 (5.67); (b) Positive group, M =
4.22 (8.73); (c) Negative group, M = 1.86 (3.60); and (d) Neutral group, M = 4.24 (8.75).
Kruskal-Wallis testing indicated no differences in values between the four groups, H(3) = 1.34, p
= .720. One-sample Wilcoxon signed rank tests revealed that no group ratios were significantly
different from the mean value, with all ps >.072. This means that all groups were evenly split
between the use of implicit and explicit source attributions on the delayed posttest. Further
analysis of the immediate and delayed explicit-to-implicit knowledge ratios revealed significant
changes in preference for source attributions within the Comparison group, z = -2.37, p = .018, r
= -.31, and Neutral group, z = -2.16, p = .031, r = -.29. Over the two-week period, these
participants placed a greater emphasis on implicit attributions while reducing their utilization of
explicit structural knowledge. Individuals within the Positive and Negative groups, however, did
not measure any changes during the same timeframe, with all ps >.112. The findings show that
at the delayed GJT, all groups selected the two categories equally, marking a failure by
participants to discriminate between the different source attribution types.

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Proportion of Source Attributions

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%

52

51

49

48

49

51

Comparison Group

Positive Group

Negative Group

Implicit Knowledge

55

45

Neutral Group

Explicit Knowledge

Figure 17. Proportion of selected source attributions from the delayed GJT. Implicit knowledge
underlies the subjective attributions of guess and intuition, whereas explicit knowledge is derived
from recollection and rule knowledge. For the Comparison and Positive groups, n = 30; for the
Negative group, n = 27; for the Neutral group, n = 29.
Analysis of the individual verb patterns, using binomial logistic regression (GEE) with
explicit response modeling (see Table 22), confirmed that participants were largely
indiscriminate in their use of implicit and explicit source attributions on the delayed posttest.
The *V3 structure marked the only exception, which was predominantly driven by explicit
knowledge for all groups.
Table 22
Explicit Source Attribution Use by Verb Pattern, Delayed Posttest
Intercept
Verb Pattern
V2(SV)
V2(VS)
V2(SV)-VF

0.54
1.21 (0.73, 1.99)
0.01
0.97 (0.56, 1.68)
0.76
1.24 (0.76, 2.01)

Positive Group
Negative Group
Wald χ2
Exp(B) (95% CI)
0.05
0.13
0.92 (0.47, 1.83)
0.88 (0.43, 1.78)
0.73
0.29
0.72 (0.35, 1.52)
0.82 (0.39, 1.70)
0.29
0.15
0.83 (0.42, 1.65)
0.88 (0.46, 1.70)

75

Neutral Group

0.66
1.35 (0.65, 2.81)
0.18
1.17 (0.56, 2.45)
0.01
1.03 (0.52, 2.02)

Table 22 (cont’d)
Intercept
Verb Pattern
V2(VS)-VF
VF-V1
*V1
*V3
*V4
*VF
*V1-VF
*VF-V2(SV)

2.03
1.42 (0.88, 2.30)
0.01
1.03 (0.66, 1.56)
0.04
0.95 (0.58, 1.56)
7.21**
2.06 (1.22, 3.50)
2.83
0.65 (0.39, 1.07)
0.29
1.14 (0.71, 1.85)
0.00
1.00 (0.65, 1.54)
0.01
1.03 (0.62, 1.70)

Positive Group
Negative Group
Wald χ2
Exp(B) (95% CI)
0.23
1.46
0.85 (0.44, 1.66)
0.67 (0.34, 1.29)
0.16
0.01
1.13 (0.62, 2.05)
0.97 (0.51, 1.86)
1.71
1.28
0.61 (0.29, 1.28)
0.68 (0.35, 1.32)
1.51
0.65
1.72 (0.73, 4.08)
1.40 (0.62, 3.19)
0.02
0.00
0.95 (0.47, 1.91)
1.00 (0.49, 2.04)
0.21
0.29
0.85 (0.43, 1.69)
0.83 (0.41, 1.66)
0.06
0.10
0.92 (0.49, 1.73)
0.89 (0.44, 1.79)
0.02
0.41
0.95 (0.48, 1.87)
0.80 (0.40, 1.60)

Neutral Group

0.03
0.95 (0.48, 1.86)
0.31
1.19 (0.64, 2.21)
0.19
1.17 (0.57, 2.41)
2.60
2.02 (0.86, 4.77)
0.02
1.06 (0.52, 2.15)
0.13
0.88 (0.43, 1.79)
0.03
0.95 (0.50, 1.79)
0.09
1.11 (0.56, 2.22)

Note. Ungrammatical verb patterns are marked with an asterisk. *p <.05, **p <.01, ***p <.001.
Source attribution accuracy data from Table 23 revealed that no group performed
significantly above chance while using implicit source attributions. The Comparison, Positive,
and Neutral groups remained accurate at levels significantly above chance when accessing their
explicit structural knowledge of the target syntax. These findings confirm a consolidation of
conscious, structural knowledge between post-exposure and (two-week) delayed testing.
Interestingly, I recorded no such consolidation with the Negative group, suggesting a lack of
durability in structural knowledge retention.

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Table 23
Grammaticality Judgment Accuracies per Source Attribution, Delayed Posttest
Mean Difference
Mean Difference
Implicit
from Chance
Explicit
from Chance
Knowledge
(50%)
Knowledge
(50%)
Group
M (SD)
z, p
M (SD)
z, p
Comparison 53.22 (10.12)
1.60, .109
56.89 (15.73)
3.10, .002
Positive
49.85 (13.90)
.74, .461
58.18 (17.13)
3.28, .001
Negative
53.10 (11.07)
1.63, .102
54.26 (12.59)
1.47, .141
Neutral
48.33 (13.92)
-.87, .383
56.18 (12.78)
2.64, .008
Note. The scores, rated on a scale of 0-100%, indicate the accuracy ratings for each source
attribution from the delayed GJT. Guess and intuition are implicit attributions, whereas
recollection and rule knowledge are explicit attributions. For the Comparison and Positive
groups, n = 30; for the Negative group, n = 27 (implicit) and n = 26 (explicit); for the Neutral
group, n = 29.
3.3.3 Verbal Reports
At the retrospective interviews, I asked participants if they noticed any types of
grammatical patterns or regularities during their initial exposure to the L2 sentences. The
transcripts of these verbal reports are located in Appendix I. To begin, no one could state the
three specific verb placement rules of the L2 grammar (see Table 2 in Section 2.3.1). Rather,
analysis indicated that participants from each group fell into one of four categories as shown in
Figure 18: (a) no awareness of verb placement, (b) some awareness of verb placement, (c),
awareness of a V2-type rule, and (d) awareness of a VF-type rule. Individuals within the “no
awareness” group failed to notice anything unusual about verb placement in sentences from the
exposure set. The Positive group had the lowest percentage of unaware participants, whereas the
Negative group contained the highest. Individuals who were “somewhat aware” offered general
or simple descriptions of the verb patterns, but lacked an overall specificity of how verbs
functioned within the sentence clauses. Example response from this group included, “the
sentences were mixed up” (417) or “it was pretty clear to me that if it sounded like normal
English, it was almost certainly incorrect” (316). Again, more individuals from the Negative

77

group fell into this category. Those within the “V2-type awareness” group reported some type of
grammar rule that placed the verb before the subject of the sentence. An example rule from this
group included, “I noticed that a lot of the times it would be that the subject came after the verb,
which I know is different from English. It would be like, ‘yesterday cooked Jim the meal’”
(108). More participants from the Positive group mentioned this type of rule than from any other
group. Individuals within the “VF-type awareness” group indicated that verbs could often be
found at the final position of a sentence (although they failed to mention the importance of clause
type), as in, “I think the action was generally last” (322). Those from the Negative group
recognized this rule the most. Overall, these findings suggest that participants from the Positive
group (64%) were better able to verbalize some type of verb pattern rule associated with the L2
grammar. Those from the Negative group were least able to verbalize a pattern, with many
participants (59%) not able to discern any meaningful grammatical regularities from their
exposure to the L2 system.

78

Figure 18. The four categories of verbal reports as described in the retrospective verbal reports.
Percentages in the Positive, Negative, and Neutral groups do not add up to 100. This is because
one participant from each group described both a V2-type and VF-type rule, and is counted
within both subgroups.
3.4 Emotions and the Relationship between Individual Differences and L2 Learning
3.4.1 Exploratory Factor Analysis
RQ3 examined the links between certain individual differences (i.e., openness, intuition,
EL, FLA, and impulsivity) and L2 performance under an affective status. As a first step, I
conducted exploratory factor analysis on each of the five personality questionnaires (i.e., BFAS,
REI, TEIQue-SF, FLCAS, and UPPS) supplied to the participants at the start of the experiment
and before emotional induction. Prior to analysis, I reversed all negatively-worded items to
maintain a uniformity of positive responses throughout. An initial attempt at consolidating all

79

items from the five questionnaires into a single factor analysis failed, resulting in a non-positive
definite matrix. As such, I decided to perform a separate analysis for each individual survey and
examined the scores by principal axis factor analysis with an oblique rotation (direct oblimin).
All Kaiser-Meyer-Olkin measures were above .7 and considered acceptable for the participant
population (Field, 2013). According to corresponding structure matrices, 14 factors in total
emerged from the findings. Secondary analysis revealed high internal reliabilities for each scale
(all Cronbach’s alpha above .74, apart from emotionality towards others at .69). Table 24
provides the results.
Table 24
Summary of Exploratory Factor Analysis
Sphericity
p

Survey

KMO

BFAS

.765

χ2(171) = 761.183
<.001

REI

.849

χ2(120) = 742.19
<.001

TEIQueSF

.792

χ2(276) = 1,240.15
<.001

FLCAS

UPPS

.912

.792

χ2(210) = 1,131.35
<.001

χ2(703) = 2,678.67
<.001

Factors (no. items)
Openness (9)
Intellect (7)
Escapism (2)
Intuitive ability (10)
General intuition (6)
Emotional selfregulation (11)
Emotionality towards
others (5)
Stress management (7)
Foreign language
anxiety (12)
General (academic)
anxiety (9)
Premeditation (10)
Sensation seeking (10)
Urgency (11)
(Lack of)
Perseverance (6)

Eigenvalues
5.02
2.54
1.54
5.92
1.89
6.80

% of
Variance
26.39
13.37
8.11
37.00
11.83
28.33

α
.81
.79
.75
.87
.74
.86

2.22

9.26

.69

2.16
8.47

9.01
40.31

.78
.89

1.62

7.73

.84

9.35
5.25
3.22
2.03

24.60
13.80
8.47
5.33

.88
.87
.87
.83

Note. Only factor loadings over .40 were retained. N = 120.
Appendix K presents the structure matrices for all five exploratory factor analyses.
Within the BFAS, I discovered three factors that accounted for nearly 48% of the variance:

80

openness, intellect, and escapism. Openness and intellect were the previously defined categories
from the BFAS (DeYoung et al., 2007). Scree plot analysis indicated the presence of a third
factor, escapism, which focused on themes of daydreaming. For the REI, two factors emerged
that accounted for over 48% of the variance: intuitive ability and general intuition. Items within
intuitive ability dealt with one’s own perceived intuitive capabilities (e.g., I believe in trusting
my hunches), whereas general intuition centered on one’s overall impressions and value of
intuition (e.g., intuition can be a very useful way to solve problems). Both intuitive ability and
general intuition paralleled the two experiential subscales, ability and engagement, from the REI
(Pacini & Epstein, 1999). The TEIQue-SF yielded three factors that made up over 46% of the
variance: emotional self-regulation, emotionality towards others, and stress management. These
factors corresponded with three of the 15 TEIQue facets (emotional regulation, emotional
perception, and stress management) identified in the long form of the questionnaire (Petrides,
2009). For the FLCAS, two factors emerged that accounted for 48% of the variance: foreign
language anxiety and general (academic) anxiety. These subscales aligned with findings from
MacIntyre and Gardener (1989), but not with MacIntyre and Gardener (1991) or Fox, Miller,
Godfroid, and Moser (in preparation). Finally, I found four factors within the UPPS that
represented over 52% of the variance: premeditation, sensation seeking, urgency, and (lack of)
perseverance. These results mirrored the four defined subscales into which the UPPS is
organized (Whiteside & Lynam, 2001).
3.4.2 Multiple Linear Regression and Moderation Analysis
For the multiple linear regression and moderation analyses, I used the immediate
grammaticality judgment scores as the dependent variable to examine whether individual
differences interacted with mood in shaping performance. There were three different types of

81

predictor variables: (a) emotional treatment (i.e., Positive, Negative, and Neutral dummy
variables, with Comparison as the baseline), (b) the mean values of the 14 factor scores, and (c)
the interactions between factor scores and emotional treatment. The factor scores, generated
from the previous exploratory factor analysis, were derivatives of the Anderson-Rubin method. I
removed all outliers (i.e., ± 3 standard deviations from the mean values) prior to regression
analysis.
Because the number of predictors (14 main effects and 42 interaction terms) exceeded the
capacity of my sample size (N = 120), I ran a series of preliminary analyses to identify the most
relevant predictors for a final regression model. To begin, I created a correlation matrix using
the 14 factors from Table 24 to examine if any of the items were related. A moderate to high
correlation between two factors could indicate that the items are tapping into similar constructs
(or opposite constructs if r is negative). The following factors exhibited moderate correlations
(above .300) with one another: (a) openness and general intuition: r = .354, p <.001; (b)
openness and emotionality towards others: r = .440, p <.001; (c) openness and sensation seeking:
r = .403, p <.001; (d) general intuition and emotionality towards others, r = .354, p <.001; (e)
stress management and intuitive ability, r = .308, p = .001; (f) stress management and sensation
seeking, r = .484, p <.001; and (g) emotional self-regulation and urgency, r = -.451, p <.001.
Next, I correlated the immediate GJT accuracy rates with the 14 factor scores for each
experimental group separately. Large differences in correlation values between the Comparison
group and any of the treatment groups were flagged as likely candidates for further regression.
Table 25 shows the results from this analysis.

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Table 25
Correlations between Factors and Immediate GJT Accuracy for Each Group
Stress
(Lack of)
Group
Intellect
Management Premeditation Perseverance
r
-.149
-.253
.273
.033
.432
.186
.144
.966
Comparison p
n
30
29
30
30
r
-.026
.181
.229
.391
p
.033
.890
.339
.232
Positive
n
30
30
30
29
r
.170
.336
.327
-.388
p
.370
.070
.083
.034
Negative
n
30
30
29
30
r
.154
-.092
-.128
-.391
p
.426
.635
.036
.509
Neutral
n
29
29
29
29
Note. Significant correlations (p <.05) are in bold.
Third, I created scatterplots of all factor scores with fit lines at subgroups to visually
identify interactions among the variables. For potential moderation analysis, I noted any large
deviations in slope of the Positive, Negative, and Neutral groups’ fit lines from the Comparison
group’s fit line. These included: (a) intellect: Positive group; (b) stress management: Negative
group; (c) premeditation: Neutral group; and (e) (lack of) perseverance: Negative group. Figure
19 displays the outcome from this endeavor.

83

Figure 19. Scatter plots, by factor, with the largest interactions between a treatment group and
the Comparison group.

84

Lastly, I performed forced entry, multiple linear regressions for each factor separately.
For all regressions, I entered the three dummy variables in Step 1, the factor score in Step 2, and
the three interaction variables (i.e., dummy variable x factor score) in Step 3. I noted all near
significant and significant predictors, which included: (a) intellect x Positive, b = 3.12 (.00,
6.24), p = .050, (b) stress management x Negative, b = 3.62 (.35, 6.88), p = .030, (c)
premeditation x Neutral, b = -3.26 (-6.55, .02), p = .052, and (d) (lack of) perseverance x
Negative, b = -2.67 (-5.49, .15), p = .064.
Based upon findings from the correlation analysis (Table 25), scatterplots (Figure 19),
and individual linear regressions, I selected the following four factors (with their corresponding
interaction variables) for final multiple linear regression and moderation analysis: intellect, stress
management, premeditation, and (lack of) perseverance. Including the dummy variables, I
arrived at 19 total predictors. This amount moderately exceeded the general rule of one variable
per ten observations for a reliable regression (Field, 2013; Larson-Hall, 2010). Due to the
exploratory nature of the analysis, however, I accepted the associated risks and proceeded with
the examination. Using the forced entry method (i.e., dummy variables in Step 1, factor scores
in Step 2, and interaction variables in Step 3), I arrived at a final model that accounted for 29%
of the variance in immediate posttest performance. With all predictors, the regression equation
was statistical, F19, 96 = 2.02, p = .014. Table 26 provides these findings.

85

Table 26
Linear Model of Predictors of Immediate Grammaticality Judgment Accuracy
R2
Model 1
Constant
Positive group
Negative group
Neutral group
Model 2
Constant
Positive group
Negative group
Neutral group
Intellect
Stress management
Premeditation
(Lack) Perseverance
Model 3
Constant
Positive group
Negative group
Neutral group
Intellect
Stress management
Premeditation
(Lack) Perseverance
Intellect x Positive
Intellect x Negative
Intellect x Neutral
Stress management x Positive
Stress management x Negative
Stress management x Neutral
Premeditation x Positive
Premeditation x Negative
Premeditation x Neutral
(Lack) Perseverance x Positive
(Lack) Perseverance x Negative
(Lack) Perseverance x Neutral

.03

.09

.29*

ΔR2

.03

.06

.20*

b (95% CI)

SE B

Beta

52.19* (49.97, 54.41)
2.98 (-.16, 6.12)
2.01 (-1.13, 5.15)
1.20 (-1.94, 4.34)

1.12
1.58
1.58
1.58

.21
.14
.09

51.83* (49.61, 54.06)
3.55* (.39, 6.71)
2.44 (-.69, 5.57)
1.40 (-1.77, 4.56)
1.16* (.00, 2.32)
-.15 (-1.41, 1.11)
.45 (-.81, 1.71)
-.52 (-1.73, .69)

1.12
1.60
1.58
1.60
.58
.64
.64
.61

.26
.18
.10
.19
-.02
.07
-.08

52.37* (50.14, 54.59)
3.60* (.52, 6.68)
1.46 (-1.65, 4.58)
.82 (-2.32, 3.97)
-.71 (-3.21, 1.79)
-1.99 (-4.49, .51)
1.66 (-.72, 4.04)
-.64 (-2.69, 1.41)
4.16* (.82, 7.50)
1.50 (-1.84, 4.84)
2.18 (-.36, 5.72)
.27 (-3.52, 4.05)
3.67* (.21, 7.13)
1.12 (-2.32, 4.55)
-2.80 (-6.57, .96)
-.03 (-3.31, 3.25)
-4.26* (-7.72, -.81)
3.60 (-.06, 7.25)
-.93 (-3.84, 1.98)
-.55 (-3.87, 2.78)

1.12
1.55
1.57
1.58
1.26
1.26
1.20
1.03
1.68
1.68
1.78
1.91
1.74
1.73
1.90
1.65
1.74
1.84
1.47
1.68

.26
.11
.06
-.12
-.31
.26
-.10
.41
.12
.17
.02
.30
.09
-.20
.00
-.30
.22
-.09
-.04

*p <.05.

86

Findings from Model 3 indicated that exposure to positive film clips and images was a
significant predictor of a positive L2 learning performance, t(96) = 2.32, p = .022. While the
individual factors alone were not significant predictors of GJT performance, some were
important via their interactions with certain mood states. Moderation analysis indicated that the
following interactions were near-significant or significant: (a) intellect x Positive, t(96) = 2.47, p
= .015; (b) stress management x Negative, t(96) = 2.11, p = .038; (c) premeditation x Neutral,
t(96) = -2.45, p = .016; and (d) (lack of) perseverance x Positive, t(96) = 1.95, p = .054.
3.4.3 Analyses of Significant Interactions
Figure 20 shows the results for intellect, which was derived from BFAS items such as, “I
am quick to understand things,” “I formulate ideas clearly,” and “I like to solve complex
problems.” Based on the moderation analysis, participants in the Positive group with higher
reported intellect levels experienced a benefit to learning, performing better than the average
intellect group by 6% and the below-average intellect group by 9%. Such discrepancies were
also noted within the Negative and Neutral groups. This means that individuals with higher
intellect levels were more likely to outperform in L2 learning tasks while experiencing some
form of emotional induction. Those with lower intellect levels, however, were disadvantaged by
their mood state.

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Grammaticality Judgment Accuracy

100%
90%
80%
70%
60%

61%
53% 52% 52%

52%

55%

55% 54%

58%

50%

49%

54% 55%

40%
30%
20%
10%
0%
Comparison Group

Positive Group
Negative Group
Self-reported intellect levels

Below Average (-1 SD)

Average

Neutral Group

Above Average (+1 SD)

Figure 20. Immediate posttest performance by group based upon intellect levels. For the
Comparison, Positive, and Negative groups, n = 30; for the Neutral group, n = 29.
In past research, intellect has been associated with a proclivity for explicit learning
(Gebauer & Mackintosh, 2007; Kaufman et al., 2010; Toplak et al., 2010; Xie et al., 2013). As a
secondary analysis, I correlated this trait with both the proportion and accuracy rates of
participants from each group when basing their judgments on explicit source attributions (i.e.,
recollection or rule knowledge). The findings, presented in Table 27, show that individuals from
the Positive group (and to a lesser extent, Comparison and Neutral groups) with higher reported
levels of intellect were more likely to utilize explicit source attributions during the immediate
GJT. Participants from both the Positive and Negative groups were more accurate when basing
their responses on explicit measures.

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Table 27
Correlations of Intellect with Explicit Source Attribution Proportion and Accuracy by Group
Factor
Group
Proportion
Accuracy
r
.241
-.205
p
.199
.277
Comparison
n
30
30
r
.535
.393
p
.002
.031
Positive
n
30
30
Intellect
r
-.206
.193
p
.274
.308
Negative
n
30
30
r
.230
-.288
p
.230
.130
Neutral
n
29
29
Note. Significant correlations (p <.05) are in bold.
Next, I generated a graph of the stress management interactions, which is found in Figure
21. This factor was composed of TEIQue-SF items such as, “on the whole, I’m able to deal with
stress,” “I generally believe that things will work out fine in my life,” and “generally, I’m able to
adapt to new environments.” Within the Negative group, participants who rated themselves with
average or higher levels of this trait performed the best overall, whereas those with lower levels
performed 7% worse. This trend was not found within the other three groups. The finding
suggests that stress management was only beneficial to L2 learning when activated by a negative
mood state.

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Grammaticality Judgment Accuracy

100%
90%
80%
70%
60%
50%

53% 53%

50%

53% 56% 55%

55% 55%
48%

53% 54% 53%

40%
30%
20%
10%
0%

Comparison Group

Positive Group
Negative Group
Self-reported stress management levels

Below Average (-1 SD)

Average

Neutral Group

Above Average (+1 SD)

Figure 21. Immediate posttest performance by group based upon stress management levels. For
the Positive and Negative groups, n = 30; for the Comparison and Neutral groups, n = 29.
Stress management, which is a component of EI (see Section 1.8) and showed a strong
association with intuitive ability and sensation seeking (see Section 3.4.2), may exhibit properties
related to implicit learning (Fiori, 2009; Zeidner et al., 2009). To test this hypothesis, I
correlated the trait with both the proportion and accuracy rates of participants from each group
when basing their judgments on implicit source attributions (i.e., guess or intuition). The
findings, presented in Table 28, indicate that individuals with higher levels of stress management
were less inclined to select implicit source attributions overall. This was especially evident for
those in the treatment groups, showing that in an emotional state, implicit knowledge was driven
by one’s inability to regulate stress. Interestingly, participants from the Negative group with
above-average levels of stress management were the most accurate when using implicit
measures.

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Table 28
Correlations of Stress Management with Implicit Source Attribution Proportion and Accuracy by
Group
Factor
Group
Proportion
Accuracy
r
-.027
-.072
p
.889
.711
Comparison
n
30
30
r
.176
-.548
p
.002
.353
Positive
n
30
30
Stress
Management
r
-.235
.591
p
.211
.001
Negative
n
30
30
r
-.333
-.226
p
.077
.239
Neutral
n
29
29
Note. Significant correlations (p <.05) are in bold.
Results from the premeditation interactions are graphed in Figure 22. Example UPPS
items for this factor included, “my thinking is usually careful and purposeful,” “I am a cautious
person,” and “before making up my mind, I consider all of the advantages and disadvantages.”
Here, participants from the Neutral group that reported lower levels of premeditation performed
5% better than those with higher rates. The same trend was not found in the other three groups,
where a lack of impulsivity signaled a benefit to L2 learning. This was especially true in the
Negative group, where participants with above-average levels of the trait scored 9% higher than
those with below-average levels.

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Grammaticality Judgment Accuracy

100%
90%
80%
70%
60%

52% 52%

55%

51%

56% 54%

50%

50%

54%

59%

56% 53%

51%

40%
30%
20%
10%
0%
Comparison Group

Positive Group
Negative Group
Self-reported premeditation levels

Below Average (-1 SD)

Average

Neutral Group

Above Average (+1 SD)

Figure 22. Immediate posttest performance by group based upon premeditation levels. For the
Comparison and Positive groups, n = 30; for the Negative and Neutral groups, n = 29.
Figure 23 contains the interaction results based upon (lack of) perseverance. UPPS items
related to this factor were, “I generally [do not] like to see things through to the end,” “I [cannot]
concentrate easily,” and “I tend to give up easily.” From these findings, participants in the
Positive group with higher levels of (lack of) perseverance performed 4.5% better than those
with average or lower levels. Interestingly, the Negative group displayed a reverse pattern, with
higher levels of (lack of) perseverance marking a disadvantage to L2 learning. Immediate GJT
performance within the Comparison and Neutral groups was not impacted by this trait.

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Grammaticality Judgment Accuracy

100%
90%
80%
70%
60%

51% 53% 51%

56% 55%

60%

55% 55%

50%

53% 54% 53%

50%
40%
30%
20%
10%
0%
Comparison Group

Positive Group
Negative Group
Self-reported (lack of) perseverance levels

Below Average (-1 SD)

Average

Neutral Group

Above Average (+1 SD)

Figure 23. Immediate posttest performance by group based upon (lack of) perseverance levels.
For the Comparison and Negative groups, n = 30; for the Positive and Neutral groups, n = 29.
As proxies for impulsivity, a (lack of) premeditation and a (lack of) perseverance have
also been linked to implicit learning (Kaufman et al., 2010; Strack & Deutsch, 2004). To follow
up on these potential relationships, I correlated the traits with both the proportion and accuracy
rates of participants from each group when basing their judgments on implicit source
attributions. Table 29 presents the findings. In agreement with the abovementioned literature,
those with lower reported levels of premeditation tended to select implicit source attributions
more often than their counterparts, regardless of group. Only participants from the Neutral group
with a (lack of) premeditation, however, were more accurate when basing their responses on
guess or intuition. For (lack of) perseverance, the results were mixed. Participants that reported
a (lack of) perseverance utilized implicit source attributions more in the Positive and Neutral
groups. I found the opposite pattern, however, within the Comparison and Negative groups.
Finally, accuracy rates with implicit source attributions were highest for the Positive group

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participants, followed by the Neutral and Comparison group participants, with lower levels of
perseverance.
Table 29
Correlations of Premeditation and (Lack of) Perseverance with Implicit Source Attribution
Proportion and Accuracy by Group
Factor
Group
Proportion
Accuracy
r
-.099
.258
p
.603
.168
Comparison
n
30
30
r
.080
-.380
p
.039
.674
Positive
n
30
30
Premeditation
r
-.073
.347
p
.708
.065
Negative
n
29
29
r
-.103
-.462
p
.596
.012
Neutral
n
29
29
r
-.161
.044
p
.397
.816
Comparison
n
30
30
r
.124
.203
p
.520
.290
Positive
n
29
29
(Lack of)
Perseverance
r
-.049
-.217
p
.799
.250
Negative
n
30
30
r
.293
.058
p
.124
.765
Neutral
n
29
29
Note. Significant correlations (p <.05) are in bold.
3.5 General Summary of the Results
In this study, participants attempted to learn and retain the syntax of a semiartificial L2
presented in a meaning-focused task. Learners in three of the four groups were emotionally
induced (either positively, negatively, or neutrally) throughout the exposure phase to examine the

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effects of mood states on L2 acquisition. Results indicated that all groups learned aspects of the
target L2 verb patterns as measured by immediate GJT accuracy rates and d prime scores. After
a two-week period of no exposure, delayed GJT posttest results showed that participants from
the Comparison, Positive, and Neutral groups successfully retained their acquired knowledge of
the L2 syntax. Individuals within the Negative group, however, failed to perform at levels
significantly above chance, perhaps signaling that their knowledge was not durable. In terms of
the overall learning effect, participants from all experimental groups perceived that post-verbal
subject (VS) and VF structures were essential components of the L2 syntax, while generally
dismissing sentences with pre-verbal subjects as ungrammatical.
Next, analysis of source attribution ratings revealed that participants from all groups
performed significantly above chance only when using the explicit measures of recollection and
rule knowledge. This phenomenon occurred at both the immediate GJT (although there was
evidence that positively and negatively induced participants relied more heavily on guessing and
intuition) and delayed GJT (apart from the Negative group, who performed at chance levels with
explicit attributions on the delayed posttest). The findings suggest that under incidental
exposure, learners did not develop implicit knowledge of the L2 syntax, regardless of mood
state. Analysis of retrospective verbal reports indicated that although the majority of learners in
the Comparison, Positive, and Neutral groups (and less than half from the Negative group) could
verbalize some aspects of the L2 grammar structure (i.e., V2-like and VF-like rules), no one was
able to correctly articulate how verbs functioned within main and subordinate clauses of the
target syntax. This development of conscious, albeit incomplete, knowledge reinforced that
learning gains from incidental exposure overwhelmingly derived from explicit means.

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Lastly, the examination of individual differences measures, mood state, and L2 incidental
exposure indicated a variety of predictors that contributed to overall learning performance. I
found that positive emotionality facilitated higher accuracy rates overall on the immediate GJT.
Moderation analysis also yielded four meaningful interactions. First, a positive mood state
moderated the relationship between intellect and (lack of) perseverance and learning
performance. Those with higher levels of both traits scored better on the immediate posttest than
their counterparts with average to below average levels. Next, negative emotionality moderated
the relationship between stress management and learning performance. Here, the ability to
regulate stress ensured higher GJT scores. Third, a neutral mood state functioned as a
moderating variable between (lack of) premeditation and learning performance, where higher
levels of impulsivity aided higher GJT scoring. Finally, correlation analysis between these four
traits and group source attribution proportion data indicated the following: (a) a positive
correlation between intellect and the use of explicit source attributions (except for the Negative
group); (b) a negative correlation between both stress management and premeditation and the
use of implicit source attributions; and (c) a positive correlation between (lack of) perseverance
and the use of implicit source attributions (except for the Comparison and Negative groups).

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CHAPTER 4
DISCUSSION
In this study, four groups of participants (three emotionally induced and one comparison)
were exposed to a variety of verb placement rules from a V2-structured, semi-artificial language
under incidental conditions. I examined whether participants learned and retained the target
grammar structures of the L2 (via immediate and delayed GJTs) and how this knowledge was
best characterized (via explicit and implicit source attributions and retrospective verbal reports).
Finally, I measured the effects of emotionality on the relationship between a variety of individual
differences and L2 learning performance. My data analysis yielded the following key findings:
(a) according to subjective reports, the EMDB film clips and IAPS images were effective in
generating negative and neutral mood states, but only slightly effectual in producing positive
emotionality; (b) positive, negative, and neutral emotional induction did not interfere with the
immediate learning of an L2 syntax; (c) only participants exposed to negative stimuli failed to
retain their knowledge of the L2 grammar after a two-week period; (d) no treatment group was
able to acquire the target syntax implicitly; (e) positive emotional induction was a significant
predictor of L2 learning performance; (f) positive affect enhanced the relationship between the
traits of intellect and (lack of) perseverance and learning performance; (g) negative affect
diminished the relationship between (lack of) stress management and learning performance; (h)
neutral affect enhanced the relationship between (lack of) premeditation and learning
performance; (i) the use of explicit source attributions correlated positively with intelligence
(minus the Negative group); and (j) the use of implicit source attributions correlated negatively
with both stress management and premeditation for all groups, and positively with (lack of)
perseverance only for the Positive and Neutral groups. Within this chapter, I examine the

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findings of my study in relation to the recent discoveries made by researchers in the fields of
emotional psychology, SLA, and adult education.
4.1 The Effectiveness of Emotional Induction
With respect to the emotional stimuli used in this study, the combination of EMBD film
clips and IAPS pictures successfully produced the expected mood states for participants in the
Negative and Neutral groups (see Tables 8 and 10). That is, the Negative group reported
significant decreases in valence and significant increases in arousal that were sustained
throughout the exposure phase. For the Neutral group, participants’ emotional and arousal states
remained at levels consistent with the Comparison group over the same time course. SAM
ratings and verbal reports from the Positive group, however, indicated that the positive stimuli
did not perform as anticipated. Although these film clips and images counteracted the negative
effects of adaptation (i.e., growing used to the treatment) over time, they failed to significantly
elevate participants’ valence and arousal levels as measured by subjective self-assessments. One
possible explanation for this disparity lies in how men and women generally respond to visual,
erotic stimuli.
Within this study, erotica represented 100% of the EMDB film clips and 44% of the
IAPS images used to induce positive emotions. Although both genders demonstrated similar
decreases in valence over the induction period, the males from the Positive group exhibited an
increase in arousal almost three and a half times greater than their female counterparts (see the
notes sections of Tables 7 and 9).6 These results partly aligned with previous research
identifying gender differences in emotional reactions to sexually explicit material (Bradley,

6

Differences in self-report by gender did not translate into learning differences, as measured by
immediate GJT performance. Here, the mean accuracy rates of males, M = 55.37, and females,
M = 54.76, were not significantly different, U = 86.00, z = -.38, p = .722.
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Codispoti, Sabatinelli, & Lang, 2001; Jacob, Arntz, Domes, Reiss, & Siep, 2011; Rupp &
Wallen, 2008). For instance, Bradley et al. (2001) found that men rated erotic pictures from the
IAPS as significantly more pleasant and arousing than did the female participants. In a separate
study from the same article, the researchers also reported that after viewing images of the
opposite sex, the males often self-described as “sexy” and “excited,” whereas the females felt
“amused” or “embarrassed.” These findings mirrored the gender differences from selfassessment arousal data and retrospective reports (see Appendix J) within the Positive group.
Here, female participants were either genuinely less affected by the (mostly) erotic material or
succumbed to a gender bias often present in emotional reporting. Examples of sociocultural
influences that might lead females to understate their affective status include perceived social
expectations and cultural attitudes toward sexual expression (Rupp & Williams, 2008).
According to Jacob et al. (2011), the inclusion of less sexually-explicit material and more
romantically-themed stimuli (e.g., romantic couples) would perhaps facilitate greater increases
in, and more accurate self-assessments of, positive emotionality and arousal for female
participants. For the purposes of this study, however, I still categorized participants from this
group as “positive” since their valence and arousal ratings were overall consistent with positive
induction, albeit at reduced levels.
4.2 Emotional Induction on Learning and Retaining L2 Syntax
My initial research question focused on the role of positive, negative, and neutral mood
states in the learning and retention of an L2 syntax. I discovered that, on par with the
Comparison group, participants in all three treatment groups successfully acquired aspects of the
key verb placement structures (i.e., V2(VS), V2(VS)-VF, VF-V1) as per their above-chance
accuracy rates and d prime scores from the immediate GJT (see Tables 13 and 14). Here,

99

emotional induction did not appear to restrict L2 grammar learning under incidental conditions.
With respect to retention, only participants from the Comparison, Positive, and Neutral groups
consistently maintained above-chance GJT performance and d prime scores over a two-week
period. Individuals from the Negative group, however, failed to sustain their initial knowledge
gains on the latter posttest, perhaps suggesting that negative mood states may hinder aspects of
long-term, L2 retention (see Tables 16 and 17). While my findings in this regard are somewhat
tenuous, the outcome aligns with previous researchers that have also identified negative affect as
detrimental to learning (Elnicki, 2010; MacIntyre & Gregersen, 2012; Miller et al., under review;
Pekrun et al., 2011; Shang et al., 2013).
One possible explanation for these findings is how the negative stimuli may have
impacted participants’ focus during incidental exposure. I arranged the treatment groups’ film
clips and images throughout the exposure phase in accordance with Tobias’ (1986) model, which
highlighted three points where anxiety most prominently interfered with learning: preprocessing, during processing, and after processing (before output) (see Figure 3). Participants
primarily in the Negative group, and to a lesser extent the Positive group, showed evidence of
processing interference during the exposure phase (Phase 3) of this experiment. For example,
both groups exhibited uneven performances while attempting to repeat the 120 sentences from
the exposure set. Within-group testing showed near-significant differences in accuracy over the
course of exposure. Participants from the Comparison and Neutral groups, however, were more
stable, maintaining more consistently accurate repetitions throughout the same period (see Figure
6). Also, the Negative group displayed significant inconsistencies in reproducing the VF-V1
verb pattern (Figure 8) as compared to the other three groups.

100

During these instances, participants exposed to negative and positive mood states may
have been colored by affective attention that diverted processing resources toward the source of
emotionality rather than the incidental learning task. Subsequently, the prioritization of
emotional information over the target input, especially at the pre-processing stage prior to
sentence repetition, possibly influenced (either positively or negatively) how the material was
encoded and later processed by the learner (Pessoa, 2010; Pessoa et al., 2012; Tobias, 1986).
Interestingly, this phenomenon did not manifest itself in immediate GJT scoring, where both
groups demonstrated a learning effect of the L2 syntax on par with the Comparison and Neutral
groups. Delayed posttest results, however, confirmed that participants in the Negative group
may have failed to fully encode, and thus successfully retain knowledge of, aspects of the L2
syntax that they initially learned. This contrasts with the Positive group, whose delayed GJT
scores remained high after the two-week period.
One reason as to why affective attention was a greater detriment for participants in the
Negative group than those from the Positive group lies with the dual competition framework
(Pessoa, 2009). This model posits that task-irrelevant stimuli (e.g., the film clips and images
used in this study) can impact cognitive control by competing for processing resources needed to
accomplish a primary function (e.g., an L2 learning task). Whether the stimuli interfere with or
facilitate task performance is dependent upon their level of intensity. For some participants in
the Negative group, resources were likely diverted away from the L2 learning task in order to
process the highly arousing (i.e., high threat) film clips and images. While participants in the
Positive group may have also experienced affective impacts, subjective measures (Table 9 in
Section 3.1.2) and verbal reports (Section 3.1.3.1) indicated that the stimuli were less intensive
(i.e., low threat) and unlikely to receive processing prioritization over the requirements set forth

101

in the L2 exposure phase. It is possible, then, that the Positive film clips and images functioned
not to disrupt cognitive control, but instead to keep participants more alert and interested in the
experimental tasks. This broad assessment, of course, does not address the specific individual
differences that may also have played a role in regulating affective attention for participants in
both groups. More discussion on this topic can be found in Section 4.4.
Another interesting finding from this study is how emotions affected the relationship
between immediate and delayed posttest performances by group. As detailed in Section 3.2.2.3,
I discovered significant and near-significant correlations among the two GJT scores for
participants within the three treatment groups. This means that, at the individual level, positive
and negative (and to a lesser extent, neutral) mood states functioned to anchor knowledge
retention relative to the initial amount of knowledge learned. The phenomenon offers a more
complex view of how emotions might influence L2 retention, challenging the general
supposition that positive emotions engender learning, while negative emotions have the opposite
effect (see MacIntyre & Gregersen, 2012). In this study, if mood states (either positive or
negative) were helpful to the individual during learning, long-term retention was likely.
Conversely, if affect interfered with the initial learning process, long-term retention also
suffered. The results offer a stark contrast to the relationship found within the Comparison
group, where delayed posttest scores were at a similar level for all participants and independent
of immediate GJT performance. As I am (I believe) the first to compare short-term and longterm L2 assessments for participants trained under a variety of emotional stressors, these findings
are preliminary and in need of confirmation through future research.
A final area of discussion, not related to emotions, involves the actual learning effect
from this study. Consistent with research using the same semiartificial language and exposure

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set items (Godfroid et al., in preparation; Rebuschat & Williams, 2012), no one from the
treatment groups ascertained the three formal rules of the L2 grammatical system (as outlined in
Table 3). Rather, participants acquired only partial aspects of the L2 syntax. Utilizing the
endorsement rates across sentence types (see Tables 15 and 18), these features can be largely
reduced into three rudimentary “perceived rules.”7 The first is that verbs can appear in the final
position of any clause, which supports the high endorsement rates for the V2(VS)-VF, VF-V1,
*VF, and *V1-VF structures. The second rule is that verbs must precede the subject, which
explains the high endorsements of the V2(VS), V2(VS)-VF, VF-V1, *V1, and *V1-VF forms.
The third rule is that pre-verbal subjects are not a part of the grammar, which resulted in low
endorsement rates for the V2(SV), V2(SV)-VF, *V3, and *VF-V2(SV) structures. Here,
participants did not seem to favor sentences with English-like structures, which included any use
of the SV form. The incongruity between these “perceived rules” and the “formal rules” is not
uncommon, given the complex nature of the L2 syntax and the limited exposure to grammatical
items in the exposure phase (see also Godfroid et al., in preparation). In my view, the
participants’ basic realizations represent an initial, yet positive step in the L2 learning process. I
would offer that additional contact with the semiartificial language, even under incidental
conditions, might allow learners to develop more target-like grammatical knowledge of the L2
over time (see Perruchet & Pacteau, 1990).

7

There are two qualifications to these rules that should be noted. The first pertains to the *V4
structure, which does not align with any of the “perceived rules.” Although participants
overwhelmingly endorsed this form on the immediate posttest, the structure fell out of favor on
the delayed posttest. Next, the V2(VS) form, which is included in the second “perceived rule”
and was highly endorsed on the immediate posttest, dropped to at chance endorsement levels on
the delayed posttest. In my opinion, these aberrations do not necessarily invalidate what
participants seemingly acquired about the L2.
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4.3 Emotional Induction and Implicit Knowledge Acquisition
The second research question asked if individuals exposed to positive, negative, or
neutral mood states could acquire an L2 syntax implicitly. The triangulation of source
attribution and accuracy data from the immediate and delayed posttests (Tables 20 and 23)
provided no definitive evidence that experimental participants developed unconscious structural
knowledge of the L2 grammar system. Individuals exposed to emotional stimuli were
overwhelmingly more accurate on the immediate and delayed (minus the Negative group) GJTs
when attributing their responses to recollection or rule knowledge. That said, participants from
the Positive and Negative groups exhibited a greater predisposition to implicit knowledge
acquisition directly after emotional induction. Indicators from the immediate posttest included
higher (although not significantly higher than chance) accuracy rates when basing GJT responses
on intuition or guess as compared to the Comparison and Neutral groups (Table 20) and a greater
preference for implicit source attributions in general (Figure 16). Analysis of the individual verb
patterns (Table 21) also hinted that unconscious knowledge drove judgments of the V2(SV) and
*V1 structures within the Positive group.8 While these findings are interesting and likely
influenced by processing interferences from the positive and negative film clips and images, they
do not provide sufficient evidence for implicit knowledge acquisition. This conclusion runs
counter to previous L2 research which used semiartificial languages and similar incidental
learning conditions and found evidence of implicit knowledge formation (Grey et al., 2014;
Rebuschat & Williams, 2012). In both studies, the researchers measured participants’ GJT
accuracy rates at levels significantly above chance when paired with the implicit source

8

Given the large amount of verb pattern comparisons in the GEE model, these effects may also
be interpreted as spurious.
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attribution of intuition. This outcome, however, was not replicated by Godfroid et al. (in
preparation). As in this study, Godfroid and colleagues found no meaningful indications that
participants developed unconscious knowledge of the target L2 syntax after incidental exposure.9
With respect to retrospective verbal reporting, no participant could identify the three
specific verb placement rules of the L2 syntax. Based upon responses, individuals fell into one
of four categories: (a) no awareness of verb placement, (b) some awareness of verb placement,
(c) awareness of a V2-type rule, and (d) awareness of a VF-type rule. These findings highlight
the value of multiple awareness measures when assessing what type of knowledge is acquired
from learning under incidental conditions (see also Godfroid et al., in preparation; Rebuschat &
Williams, 2012). Alone, retrospective verbal reporting (Section 3.3.3) would have shown
implicit knowledge to be a significant driver of learning, as many participants displayed abovechance performance on the GJT, but were unable to articulate any rule, regulation, or verb
pattern associated with the L2 syntax. This assumption, of course, is faulty when paired with
analysis from immediate and delayed source attribution data and underscores the issues of
insensitivity and incompleteness with verbal reports (Rebuschat, 2013). Another point to
consider is how the amount of time between the initial L2 exposure and the retrospective
interviews (two weeks) might have affected the quality of the verbal reports. Although
speculative, it is reasonable to assume that the delayed reporting may have generated more
comments signaling “no awareness of verb placement” and “some awareness of verb placement”
due to memory degradation. Nonetheless, a larger percentage of Negative group participants
(54%) failed to recall either a V2-type or VF-type rule as compared to those within the Positive

9

Godfroid and colleagues found evidence of unconscious structural knowledge for only one verb
pattern out of seven (VF-V1) in one subgroup of learners (V2-aware).
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(39%) or Neutral (47%) groups. This phenomenon provides some evidence of negative mood
state interference in long-term, conscious knowledge formation.
One explanation for why participants did not acquire implicit knowledge of the L2
syntax may lie with how adults learn, and ultimately acquire, second languages. The
Fundamental Difference Hypothesis (Bley-Vroman, 1988; DeKeyser, 2003) states that adults
primarily favor problem-solving strategies and analytical processing when learning new
languages. Such techniques allow adults to make sense of new vocabulary and complex
grammars quickly and with minimal input. This contrasts with the language learning
mechanisms of children, which are assumed to be largely implicit and occur without awareness.
Over the past few decades, researchers have noted the importance of explicit cognitive
processing in terms of both adult L2 acquisition (DeKeyser, 2000) and its pedagogical value in
the classroom (Leow, 2015). In accordance with the abovementioned literature, I also
discovered that my participants, all of whom were over the age of 18, relied more on their
conscious knowledge of the novel language to navigate the two performance assessments. This
phenomenon likely occurred because participants either developed an awareness of certain
syntactic features of the L2 or employed explicit processing strategies while exposed to the
incidental learning task (see DeKeyser, 2003). Even when proportion data skewed in favor of
implicit source attributions, as I found in the Positive and Negative groups, participants were still
not accurate in their grammatical judgments. Therefore, I believe that any evidence of implicit
knowledge found within the treatment groups should be solely attributed to mood state
distractions. For adult learners to legitimately manifest unconscious knowledge, they would
have likely needed much more L2 input over an extensive period of time (e.g., akin to a long-

106

term study abroad or immersion program), rather than the 120 sentences from the exposure set
provided in this experiment (DeKeyser, 2000; Loewen, 2015).
Methodological differences, especially with the Rebuschat and Williams (2012) study,
may also account for why I did not find evidence of implicit knowledge (acquisition) among the
treatment groups. The first issue is that of sample size. The experimental group from the
Rebuschat and Williams study included only 15 participants, which is a small number and
arguably not well representative of the target population. Smaller N sizes are also more prone to
sampling errors (see Field, 2013), where certain effects (e.g., high GJT accuracy rates when
basing one’s decision on intuition) may disappear with the inclusion of additional participants. I
believe this to be the case in my study, where the likelihood of unconscious knowledge
acquisition faded over the larger group sample sizes (30 participants each). Secondly, the testing
instructions provided by Rebuschat and Williams may have biased participants towards the
source attribution of intuition. As detailed in the GJT testing guidelines from Experiment 3 of
Rebuschat (2008), from which the Rebuschat and Williams study was derived, the researcher
directed participants to “rely on your intuition when judging the well-formedness of the
sentences” (p. 189). Such a statement may have influenced individuals to inadvertently select
intuition over other source attributions throughout the posttest, thus skewing the overall accuracy
rates. In my experiment, participants were not asked to favor a specific source attribution on the
GJTs, which likely generated a more honest assessment of what knowledge was acquired during
incidental learning.
Finally, I discovered that while source attributions were a helpful tool for gauging
awareness, the measurement’s effectiveness extended only to the immediate posttest. Here, good
discrimination between the two source attribution types emerged within two of the four

107

experimental groups (Comparison and Neutral groups). After a two-week period, however, the
use of source attributions became less reliable as all groups selected the two categories at equal
rates. This finding contrasts with Grey et al. (2014), who still recorded good discrimination
between implicit and explicit source attributions (62% and 38% proportion rates, respectively)
among participants on a delayed acceptability judgment task. Similar to my study, the time
separation between immediate and delayed posttest was two weeks. As very few researchers
have utilized source attributions over extended periods, further applications of delayed posttest
designs are needed to the confirm the validity of the measure.
4.4 Mood States and the Interconnection of Individual Differences and L2 Learning
The final research question centered on whether positive, negative, and neutral mood
states impacted the relationship between openness, intuition, EI, FLA, and impulsivity and L2
learning performance. Using the BFAS, REI, TEIQue-SF, FLCAS, and UPPS questionnaires to
measure participants’ trait levels, I extracted 14 factors for further analysis (see Table 24).
Linear regression revealed that no single factor significantly contributed to learning. Rather,
four specific traits (i.e., intellect, stress management, premeditation, and (lack of) perseverance)
were influential through their interaction with certain mood states (as detailed in Table 26 and
Section 3.4.3). For example, positive affect (and to a lesser extent, negative and neutral affect)
enhanced immediate GJT performance for participants with average to above average levels of
self-reported intellect. This trait, which has been linked to fluid intelligence and working
memory (DeYoung, Peterson, & Higgins, 2005), not only shielded against the negative impacts
of emotional distractors, it also aided in learning. The finding is similar to previous research by
Reeve, Bonaccio, and Winford (2014), who noted that high academic ability functioned to buffer
mood state interferences. As such, the positive film clips and images in this study likely kept

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individuals with higher levels of intellect more alert and engaged during the exposure phase,
rather than hinder L2 learning. Conversely, those with lower trait intellect levels may have
lacked the processing resources required to sufficiently counteract these same emotional
distractors, thus negatively affecting their overall performance (see Pessoa, 2009).
Next, I found that stress management was a contributing factor to learning performance
for participants within the Negative group. In the context of the current study (unfamiliar syntax
exposure combined with high arousal and negative emotional distractors), this outcome makes
sense. As a component of EI, stress management is linked with how one reacts to and regulates
emotional stressors (Petrides, 2009). Here, participants with average or greater than average
levels of this trait were more likely to suppress any debilitating effects from the negative film
clips and images, freeing up additional processing resources for L2 learning (see Fiori, 2009).
Similar to the discussion on intellect, processing competition between the negative stimuli and
the incidental exposure requirements may have contributed to GJT underperformance for those
with lower stress management levels.
The effects of premeditation and (lack of) perseverance on learning performance were
mixed and dependent upon a variety of mood state interactions. On the surface, it would seem
that participants with higher levels of trait impulsivity (i.e., a lack of premeditation or
perseverance) might uniformly underperform complex learning assessments (like the GJTs from
this study) due to a reliance on gut responses over thoughtful contemplation. Grey et al. (2015)
found this to be the case in their study of individual differences and L2 learning, where
performance on Japlish acceptability judgment tasks negatively correlated with impulsivity. It is
worth noting, however, that these results were achieved using cold cognition. With the
introduction of affective interference, trait impulsivity appears much more reactive. For

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example, while I too discovered that impulsivity, as conveyed through a (lack of) premeditation,
was disadvantageous to immediate GJT performance, the findings were only true for participants
exposed to high arousal stimuli (both from the Positive and Negative groups). Unlike the Grey
et al. study, participants with higher levels of impulsivity within the Neutral group outperformed
those with lower levels and impulsivity was a significant predictor of L2 learning. This suggests
that highly impulsive learners may in fact benefit from contact with low-arousal, emotional
stimuli. However, impulsivity, as expressed through a (lack of) perseverance, was found
beneficial to learning performance for those within the high-arousal, Positive group. Although
this outcome was reversed for Negative group participants, it was not significant (see Figure 23)
and may represent an anomaly in the data. The Neutral group remained unaffected by this trait.
The disparity in findings among the factors of premeditation and (lack of) perseverance, as
related to high versus low arousal contexts, highlights the unpredictable nature of impulsivity
within emotional settings and underscores the need for more research on this specific trait.
Since intellect, stress management, premeditation, and (lack of) perseverance were the
most influential individual differences in this study, I also examined their relationships with
explicit and implicit source attribution proportion data for each treatment group. In accordance
with findings from previous literature (Gebauer & Mackintosh, 2007; Kaufman et al., 2010;
Toplak et al., 2010; Xie et al., 2013), intellect positively correlated with the use of explicit
knowledge source attributions in the Positive and Neutral groups (see Table 27). Here,
participants with mid to high trait intellect levels displayed a greater awareness of how they
arrived at their grammaticality judgments, portending an effortful and analytical approach to L2
learning. Interestingly, individuals experiencing negative mood induction did not conform to
this relationship. As explicit knowledge is declarative (Ellis, 2004), an inability to produce rule-

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based expressions may explain the disparity. This finding was confirmed by the post-experiment
verbal reports (see Figure 18), where subjects in the Negative group verbalized fewer rules than
any of the other groups.
In terms of implicit knowledge and the traits of stress management, premeditation, and
(lack of) perseverance, results were mixed. As an element of EI, which itself has loose ties to
implicit learning (Fiori, 2009; Zeidner et al., 2009), stress management correlated negatively
with the use of implicit source attributions by all treatment groups (see Table 28). The
relationship may be related to how participants with lower stress management abilities coped
with the emotional distractions found throughout this study’s exposure phase. As previously
discussed, processing competition from the film clips and images likely restricted these
individuals’ ability to consciously search for grammatical patterns or regularities among the
sentences from the exposure set, leading to an overreliance on guessing and intuition to navigate
the immediate GJT. For impulsivity (Table 29), I discovered a negative relationship between
trait premeditation and the use of implicit source attributions by all treatment groups. This
finding aligns with previous research (Kaufman et al., 2010; Strack & Deutsch, 2004) linking
impulsivity with implicit learning. Here, less deliberate individuals, regardless of mood state
influence, likely made their grammaticality assessments quickly and at the unconscious level.
Those with higher levels of premeditation were more thoughtful in their decisions, relying
instead on their explicit knowledge of the L2 syntax throughout the posttest. Trait (lack of)
perseverance levels exhibited a positive relationship with implicit source attribution use for those
within the Positive and Neutral groups. For this measure of impulsivity, my findings diverged
from Kaufman et al. (2010) and Strack and Deutsch (2004) only for the Negative group, as
participants with lower levels of persistence relied slightly more on their explicit knowledge

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while completing the immediate GJT. Although it is possible that this trait comes with a
sensitivity to explicit processes through negative mood states, the result is counterintuitive.
Further research is needed to understand this finding.
Finally, it is important to address why openness, intuition, and FLA did not significantly
influence learning performance for any of the treatment groups from my study. As previously
discussed in Sections 3.3.1 and 4.3, accuracy on the immediate GJT was primarily driven by
participants’ explicit knowledge of the L2 syntax. Since openness and intuition are strongly
associated with implicit learning processes (Kaufman et al., 2010; Woolhouse & Bayne, 2000), it
is understandable that the two traits offered no tangible benefits to performance in this study. L2
learning performance also suffered no meaningful impacts from FLA, which runs counter to
previous research on the subject (Horwitz et al., 1986; Horwitz, 2001; MacIntyre & Gardner,
1989, 1994). The design of this experiment, which included a semiartificial language with
English vocabulary, may offer a plausible explanation. Here, participants were not informed of
their engagement with a novel language until after the incidental learning task (see Section
2.4.1.4). Any anxiety experienced during the exposure phase (i.e., accurately repeating aloud the
scrambled English sentences) was likely regulated by the stress management trait rather than an
ability to combat FLA.

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CHAPTER 5
CONCLUSION
In this final chapter, I present the following three sections to conclude my dissertation:
(a) a summarized account of my findings and their contributions to the fields of SLA and
cognitive psychology; (b) the pedagogical, theoretical, and methodological implications related
to my results; and (c) the limitations of this study and possible directions for future SLA research
in the context of hot cognition.
5.1 Summary of the Findings
The present study added to the fields of psycholinguistics and cognitive psychology by
investigating the impacts to L2 learning from positive, negative, and neutral mood induction.
First, I examined the role of emotionality on the learning and retention of a semiartificial
language as presented in a meaning-focused task. As measured by immediate GJT accuracy
rates and d prime scores, participants from all three treatment groups were able to learn certain
features of the L2 syntax. This finding is important and demonstrates the effectiveness of
incidental learning conditions in the face of emotional distractors. Regarding retention, only
participants from the Positive and Neutral groups successfully sustained their knowledge gains
over a two-week period. Those from the Negative group, however, failed in this respect. The
findings signal that high arousal, negative stimuli may interfere with aspects of long-term
encoding if the mood occurs at the point of initial L2 exposure. However, as effects for this
result were small, additional research is warranted to verify the conclusion. In terms of what was
actually learned, individuals from all groups seemed to develop similar perceptions about the L2
grammar structure as revealed by their verb pattern endorsement rates. Although not exact,
participants formulated workable ideas of what did or did not belong to the German syntax.

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These “perceived rules” were target-like and proved sufficient for successfully navigating the
learning assessments despite limited access to input.
Next, participants exposed to emotional stimuli in this study did not develop implicit
knowledge of the target L2 syntax. Rather, immediate and delayed GJT performance was solely
predicated on conscious knowledge sources. While individuals that experienced positive and
negative mood state induction did show a greater proclivity for acquiring unconscious
knowledge, the phenomenon was likely related to affective interferences during the incidental
learning period. The results highlight that adults are analytical in their approach to language
learning and, when left to their own devices, are more dependent on explicit means (i.e.,
recollection and rule knowledge) to process and interpret unfamiliar L2 material. The
combination of source attributions and retrospective verbal reports helped to shape this
conclusion, revealing that many treatment group participants developed conscious (yet
incomplete) knowledge of the target structures (i.e., V2-like and VF-like rules).
Lastly, this study showcased the various moderating roles of affective stimuli on the
relationship between L2 learning performance and four specific personality characteristics.
These included intellect and (lack of) perseverance (as moderated by positive emotionality),
stress management (as moderated by negative emotionality), and premeditation (as moderated by
neutral emotionality). The factors of openness, intuition, and FLA, however, were not influential
to learning performance in this study. Additionally, I found that intellect demonstrated a greater
alignment with explicit source attributions, whereas stress management negatively correlated
with implicit source attributions. (Lack of) perseverance and (lack of) premeditation, which are
closely related to impulsivity, exhibited stronger relationships with implicit knowledge overall.

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Only the Negative group, as measured through (lack of) perseverance, did not conform to this
finding.
5.2 Implications of the Findings
From a pedagogical standpoint, this study verified the efficacy of L2 learning under
incidental conditions. Here, all treatment groups successfully learned aspects of a novel
grammar system despite the complexity and limited input of the target structures. While the
participants’ working knowledge of the L2 syntax lacked nuance (e.g., how verbs specifically
functioned within main and subordinate clauses), endorsement rates and GJT performance
signaled a positive first step towards grammatical sensitivity. That this occurred in the presence
of a variety of emotional distractors highlights the hardiness of the learning process. Delayed
GJT accuracy rates among the Positive and Neutral groups also demonstrated that learning under
incidental conditions is durable, even without additional exposure to reinforce the target material.
As evidence exists that semiartificial language learning compares well with natural language
acquisition (see Ettlinger, Morgan-Short, Faretta-Stutenberg, & Wong, 2016), L2 instructors
would be remiss not to include incidental learning tasks (e.g., communicative activities or
reading for content, where the L2 grammar is not the focus; see Loewen, 2015) within their
curriculum.
Next, this study confirmed how certain emotions impact language learning. While the
affective stimuli appeared to either facilitate or hinder L2 acquisition on an individual level, I
found that a positive mood state was the most conducive to learning and a significant predictor of
L2 performance. Conversely, negative emotionality generally impaired L2 retention. Language
instructors should understand that negative feelings have potentially adverse impacts on student
performance that may not manifest themselves until later assessments. This is especially true in

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the context of instructed SLA, where language learning is already a process inherently “fraught
with emotions” (Swain, 2013, p. 198). Therefore, it is recommended that educators promote a
more positive and encouraging learning environment to potentially enhance L2 acquisition.
Such efforts would likely mitigate the stress normally associated with language learning and help
focus students on the target material.
Theoretically speaking, my findings indicated that adult language learners were unable to
acquire implicit knowledge under incidental learning conditions. Even with the presence of
emotional distractors, awareness measures confirmed that knowledge was principally formed
through conscious means. This outcome runs counter to previous research that found evidence
of implicit knowledge acquisition using source attributions and similar learning techniques (Grey
et al., 2014; Rebuschat & Williams, 2012). One possible explanation for the discrepancy is
related to how adults learn novel languages, which has been hypothesized as uniquely explicit
(Bley-Vroman, 1988, DeKeyser, 2000; Leow, 2015). If this is indeed true, a proportion of adult
L2 language instruction should leverage activities that tap into explicit learning skills to
maximize intrinsic cognitive behavior (see DeKeyser, 2003). My experiment also demonstrated
that mood states play an important and complex role in L2 acquisition. To be sure, adult
language learning does not normally occur within the sterile confines of cold cognition. How
affective attention impacts cognitive control during L2 learning tasks, for example, is an area of
psycholinguistics language learning research worthy of further examination. The inclusion of
emotional stressors within SLA research may offer a more accurate perspective of how
individuals acquire novel languages in the face of mood state influencers.
This study also generated several methodological implications for future research on
incidental language learning. The use of multiple awareness measures (i.e., source attributions

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and retrospective verbal reports), for example, proved necessary in determining what types of
knowledge were acquired by participants. As noted by Godfroid et al. (in preparation), source
attributions help make sense of the data (e.g., the verb pattern endorsement rates), while verbal
reports identify the contributing factors to overall performance (e.g., GJT scores) (see also
Dienes & Scott, 2005; Rebuschat, 2013). Researchers should continue assessing participants in
this manner, particularly when GJTs are utilized, to better understand the effects of incidental
exposure on knowledge acquisition. Next, the inclusion of a delayed GJT in this experiment’s
design offered insight into aspects of L2 retention. Future utilization of post-assessments can
inform researchers on both the durability of learning under incidental conditions (see Grey et al.,
2014), as well as the role of emotions on long-term L2 acquisition. Finally, this study
highlighted the importance of including individual differences data within the framework of SLA
research. The examination of personality characteristics and how they may predict L2 learning
performance, particularly in the context of emotional settings, is vital for advancing the fields of
psycholinguistics and instructed SLA.
5.3 Limitations and Future Research
The current study is not without its limitations. One issue resides with the film clips and
images used to emotionally induce participants throughout the incidental learning task. To start,
the affective stimuli only represented discrete subcategories of positive and negative mood
states, namely either low valence, high arousal (e.g., fright, annoyance, and anger) or high
valence, high arousal (e.g., elation, lust, and exhilaration). A concern with such stimuli is that
negative items are generally rated higher in arousal than positive items. This effect does not
allow for a symmetrical comparison of the affective impacts experienced by the Positive and
Negative groups (see Carvalho et al., 2012; Lang et al., 2008). To avoid these issues, future

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research should incorporate a variety of stimuli that evoke different facets of emotionality, such
as feelings of low valence, low arousal (e.g., sadness and depression) or high valence, low
arousal (e.g., contentment and amusement). Besides eliminating incongruities in arousal levels,
this approach would allow researchers to investigate how other emotional states impact aspects
of L2 learning.
Other noted limitations were more specific to either the EMDB or IAPS databases. For
example, EMDB film clips were soundless. The inclusion of television or movie segments with
sound may help to amplify emotional impacts by stimulating the visual and auditory senses of
participants. Also, the neutral films clips (i.e., nature scenes) from this database skewed slightly
pleasant, which may have influenced SAM valence ratings among Neutral group participants.
Within the IAPS, many photos depicted outdated scenes (e.g., older fashions, hairstyles, etc.; see
Jacob et al., 2011) and lacked racial diversity which may have minimized relatability with the
young adults that participated in this study. Members of the SLA community interested in
emotional research should continue to explore a variety of affective mediums to determine which
induction methodologies are best suited for our field of study.
Secondly, I recorded changes in valence and arousal ratings throughout the experiment
using only one measurement tool: SAMs. While the self-assessments allowed for quick and
discreet emotional checks, they were entirely subjective. As such, the SAMs may not have
accurately captured the true effects of the film clips and images on the participants’
psychological state (see Section 4.1). The inclusion of psychophysiological measures in future
studies, such as skin conductance and heart rate data, would offer a more well-rounded
estimation of how mood states affect both the mind and the body during a learning task.

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Finally, this study focused exclusively on receptive tasks (i.e., GJTs) to gauge L2
learning and retention. While participants produced the semiartificial language during the
elicited imitations, they were not required to generate spontaneous speech using the novel
syntax. In the future, researchers that investigate L2 learning under incidental conditions need to
incorporate productive tasks and assessments in order to better understand how the oral process
of communication is affected. Lastly, other subdomains of language besides syntax (e.g.,
phonology or semantics; see Grey et al., 2014) should be evaluated to broaden our perspectives
on the L2 learning process.

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APPENDICES

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APPENDIX A

Sentences from the Exposure Set
The following items constitute the exposure set used in Phase 3 of this study. Aside from
the four practice items, there are a total of 120 different sentences, divided equally into three
verb placement rules (V2, VF-V1, V2-VF). Implausible sentences are labeled with a question
mark (?). All items are adapted from Rebuschat (2008).
Practice sentences:
1. Brian received today a haircut at the barber shop. (V2)
2. Yesterday alleged Sue that the convict to Utah escaped. (V2-VF)
3. ? Last week e-mailed Liz the document to a tomato. (V2)
4. ? After his cat the rats chased, assembled Brian a raisin with a fork. (VF-V1)
V2 sentences:
Average sentence length: 8.9 words (8.9 for plausible, 8.9 for implausible)
Average syllables per sentence: 13.8 syllables (14.0 for plausible, 13.5 for implausible)
1. Chris entertained today his friends with a funny story.
2. Brian played often an important part in the school plays.
3. Jack reacted last week badly against unfounded claims.
4. Mike operated last June on his patient for many hours.
5. George saved yesterday a lot of money during the trip.
6. Liz heaved today the boxes onto the table.
7. Sarah forgot often her problems during the party.
8. Rose satisfied last week all the requirements promptly.

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9. Sue gambled last June with her savings at the casino.
10. Cate justified yesterday the funding during the meeting.
11. Today executed George the plan with efficiency.
12. Often drew Mike his clients in a realistic fashion.
13. Last week ranked Jack his employees according to their skills.
14. Last June rebutted Brian his employee’s claim for payment.
15. Yesterday ranted Chris about the government’s plans.
16. Today challenged Cate the college statutes in her speech.
17. Often sat Sue in the seminar next to the door.
18. Last week ate Rose excellent dessert at a café.
19. Last June defended Sarah many shots during her matches.
20. Yesterday competed Liz with much zest in the tennis match.
21. ? Chris gossiped today in his office with a Martian.
22. ? Brian exploded often all night to a potato.
23. ? Jack scrutinized last week the old goat on planet Mars.
24. ? Mike juggled last June to his friends the purple whale.
25. ? George swallowed yesterday the recipe cards with nails.
26. ? Liz lectured today for a long time to the unicorn.
27. ? Sarah covered often the lava with golden elbows.
28. ? Rose abandoned last week her cats on planet Venus.
29. ? Sue punished last June a bulldozer with her poodle.
30. ? Cate kissed yesterday important discussions with a fork.
31. ? Today bit George the priest in the happy lunchbox.

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32. ? Often vomited Mike the lipstick for his birthday.
33. ? Last week met Jack in Seattle the Mayor of Jupiter.
34. ? Last June preached Brian with Elvis Presley in Memphis.
35. ? Yesterday graduated Chris from school on planet Saturn.
36. ? Today erupted Cate at midnight with a monkey.
37. ? Often repaired Sue the guitar with oranges and lemons.
38. ? Last week angered Rose the course assignments with her rainbow.
39. ? Last June sailed Sarah on a candy bar to Norway.
40. ? Yesterday shattered Liz the window with a leprechaun.
VF-V1 sentences:
Average sentence length: 12.8 words (12.5 for plausible, 13.0 for implausible)
Average syllables per sentence: 17.5 syllables (18.0 for plausible, 17.0 for implausible)
1. Since his teacher criticism voiced, put Chris more effort into his work.
2. After the robber a knife pulled, screamed Brian to the man for help.
3. Since his team against their rivals lost, fired Jack the coach on the spot.
4. After his father a tutor hired, studied Mike harder on his assignments.
5. Since a silver spoon after dinner vanished, accused George his guests of theft.
6. After her mother the house cleaned, admired Liz the state of the bedroom.
7. Since her car in the road stopped, began Sarah to take the bus.
8. After the police her car seized, expected Rose a fine from the officer.
9. After the ATM money withheld, complained Sue about the issue to the bank.
10. Since the famous actor her daughters interviewed, bragged Cate about her kids with pride.
11. After the company his book published, sent George many copies to his friends.

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12. Since the storm many trees uprooted, planted Mike five saplings with friends.
13. After the lottery the prize announced, looked Jack for his ticket at home.
14. Since the company their offer withdrew, sought Brian employment elsewhere.
15. After his friend four goals scored, viewed Chris him with different eyes.
16. Since the factory the river polluted, avoided Cate contact with tap water.
17. After the magazine her designs published, had Sue many calls from buyers.
18. Since her parents their grandchildren visited, passed Rose her day in bed.
19. After the nurse her son vaccinated, texted Sarah her spouse a message.
20. Since many protesters the area occupied, called Liz the police for help.
21. ? Since his boss many sessions scheduled, hammered Chris his soul with a pumpkin.
22. ? After his cats the mice hunted, squandered Brian a new lump in the office.
23. ? Since his son the bread ate, invested Jack a dollar in the moth.
24. ? After his wife an egg craved, flushed Mike his shoes to Japan.
25. ? Since his boss more work promised, enjoyed George a holiday on the moon.
26. ? After her kids to the playground walked, phoned Liz their rabbit in the cave.
27. ? Since her mother the men kissed, showed Sarah her elbow to a bear.
28. ? After her aunt the lagoon purchased, painted Rose dessert at the farm.
29. ? After her son for the bus waited, boarded Sue the microwave to New York.
30. ? Since her friend a tractor owned, cycled Cate her cat on a camel.
31. ? After his wife a thief surprised, drowned George the police with a steak.
32. ? Since the women a garden planted, issued Mike a lobster warning in bed.
33. ? After his wife many chores juggled, ambushed Jack famous oysters from school.
34. ? Since his friend to Russia sailed, spoke Brian about work to sausages.

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35. ? After his son from the airplane resigned, erased Chris the painting in bed.
36. ? Since her son a teacher became, swallowed Cate a doorbell at the table.
37. ? After the shop in her town closed, killed Sue a tasty cake in the bushes.
38. ? Since her friends often hunger feigned, e-mailed Rose in the canyon a soup.
39. ? After her cat the sandbox toured, devoured Sarah clouds for breakfast.
40. ? Since many birds to the ground fell, killed Liz three teeth with a sponge.
V2-VF sentences:
Average sentence length: 9.4 words (9.2 for plausible, 9.5 for implausible)
Average syllables per sentence: 13.7 syllables (13.5 for plausible, 13.9 for implausible)
1. George repeated today that the movers his table scratched.
2. Mike reckoned often that his students about their classes cared.
3. Jack mentioned last week that his father robots designed.
4. Brian contested last June that his friend weapons possessed.
5. Chris stressed yesterday that his children their teeth brushed.
6. Cate realized today that her neighbor illegal drugs dealt.
7. Sue remarked often that the judge innocent people favored.
8. Rose guessed last week that all jurors against her ruled.
9. Sarah advised last June that her students the words learned.
10. Liz recalled yesterday that her mother a cake baked.
11. Today reflected Chris that the fire department all day trained.
12. Often swore Brian that this ointment all wounds healed.
13. Last week alleged Jack that his wife their money lost.
14. Last June yelled Mike that the government welfare encouraged.

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15. Yesterday opined George that the storm his boat destroyed.
16. Today figured Liz that her spouse an affair conducted.
17. Often emphasized Sarah that the college a job offered.
18. Last week explained Rose that profits below average remained.
19. Last June remarked Sue that her son in Miami lived.
20. Yesterday explained Cate that the company sales improved.
21. ? George presumed today that his car the best college swallowed.
22. ? Mike wondered often that his teacher a ghost robbed.
23. ? Jack guessed last week that his parents the unicorns burned.
24. ? Brian reported last June that his egg the ocean attacked.
25. ? Chris said yesterday that the lemon in his office fainted.
26. ? Cate confessed today that her flower the horse murdered.
27. ? Sue posited often that the sandwich her cave jumped.
28. ? Rose assumed last week that the earthworm two debates exploded.
29. ? Sarah testified last June that her moon the snow burned.
30. ? Liz guessed yesterday that the carpet a country baked.
31. ? Today beheld Chris that the earth around socks rotated.
32. ? Often reasoned Brian that the eyeball cash digested.
33. ? Last week proposed Jack that the raccoon for love vomited.
34. ? Last June cried Mike that his toenail in newspapers drowned.
35. ? Yesterday sang George that his hamburger English mumbled.
36. ? Today exclaimed Liz that her parents the hotdog watered.
37. ? Often wished Sarah that the troll in the winter melted.

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38. ? Last week inferred Rose that her scissors a table caressed.
39. ? Last June thought Sue that her boss in cereal floated.
40. ? Yesterday mentioned Cate that the plumber a new frog designed.

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APPENDIX B

Testing Sentences
The following items constitute the testing set used in Phase 4 of this study. Aside from
the four practice items, there are a total of 60 different sentences, divided into 30 grammatical
and 30 ungrammatical items. The grammatical sentences follow the three verb placement rules
(V2, VF-V1, V2-VF) found in the exposure set (Appendix A). Ungrammatical items abide by
different verb placement rules (VF, VF-V2, V1-VF, V1, V3, V4) and are labeled with an asterisk
(*). All items are adapted from Rebuschat (2008).
Practice items:
1. Yesterday purchased Peter a new car in Chicago. (V2)
2. Because his son books needed, visited Sam the library in town. (VF-V1)
3. *When her children recently for school left, Janet watched a movie. (VF-V2)
4. *Yesterday John ate the sandwich during his break. (V3)
V2 sentences:
Average sentence length: 9.7 words
Average syllables per sentence: 15.2 syllables
1. David scribbled yesterday a long letter to his family.
2. John recognized recently the stolen paintings in a museum.
3. Jim loaded in the afternoon the wagon with hay.
4. Paul told after dinner his parents the good news.
5. Peter decided some time ago on a business proposal during a meal.
6. Yesterday enjoyed Emma the food in the dining hall.

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7. Recently spent Chloe her day at the library.
8. In the afternoon drank Jennifer a glass of wine in the local bar.
9. After dinner drove Susan to her son’s house in Dallas.
10. Some time ago arranged Janet a meeting with her tutor.
VF-V1 sentences:
Average sentence length: 12.1 words
Average syllables per sentence: 19.9 syllables
1. When his parents groceries needed, purchased David everything necessary.
2. Because his puppy very annoyingly acted, asked John the vet for advice.
3. When his wife the office building left, prepared Jim dinner for the entire family.
4. Because his children fairy tales loved, invented Paul many stories from them.
5. When his daughter in Detroit worked, visited Peter this city many times.
6. When the children the new flowerbed destroyed, chased Emma the culprits around the garden.
7. Because her company capital lacked, organized Chloe a fundraiser with her boss.
8. When her children from school arrived, interrupted Jennifer her work for a while.
9. Because her daughter sweets adored, brought Susan many desserts to the table.
10. When her friend in Italy dwelled, received Janet postcards from Rome.
V2-VF sentences:
Average sentence length: 10.2 words
Average syllables per sentence: 17.8 syllables
1. Paul speculated yesterday that the suspect from prison escaped.
2. Peter disclosed recently that the company sufficient funds generated.
3. Emma said in the afternoon that her parents the apartment rented.

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4. Chloe argued after dinner that the chairman the wrong figures displayed.
5. Jennifer suspected some time ago that the old professor the computer broke.
6. Yesterday lamented Susan that her son the baptism missed.
7. Recently learned Janet that the university her application rejected.
8. In the afternoon acknowledged David that her children to England moved.
9. After dinner maintained John that his father in French cuisine indulged.
10. Some time ago claimed Jim that his mother Spain liked.
*VF sentences:
Average sentence length: 9.8 words
Average syllables per sentence: 16.4 syllables
1. *Yesterday David with distinction from Harvard University graduated.
2. *Recently John the Boston Marathon in four hours ran.
3. *In the afternoon Emma a wonderful meal for her in-laws cooked.
4. *After dinner Chloe an old car with her savings bought.
5. *Some time ago Jennifer to New York with her husband travelled.
*VF-V2 sentences:
Average sentence length: 13.2 words
Average syllables per sentence: 22.4 syllables
1. *Because his son yesterday an instrument wanted, Jim talked with the music teacher.
2. *When his parents recently to Paris retired, Paul flew a lot to France.
3. *Because his children in the afternoon a calculator required, Peter called the electronics store.
4. *When her director after dinner confidential information divulged, Susan quit the department.
5. *Because her husband some time ago in Princeton taught, Janet declined the job transfer.

130

*V1-VF sentences:
Average sentence length: 14.4 words
Average syllables per sentence: 22.2 syllables
1. *Acquired David an extravagant watch when his partner yesterday a lot of money made.
2. *Went John to the cinema on his own because his favorite actress recently in a new film
starred.
3. *Discussed Jim the new CD when his friend after dinner the kids took.
4. *Stayed Emma at the hotel because her husband in the afternoon a boring conference attended.
5. *Knew Chloe Sydney when her daughter some time ago in Australia lived.
*V1 sentences:
Average sentence length: 10.6 words
Average syllables per sentence: 18.0 syllables
1. *Hired Paul yesterday two new chefs for his restaurant.
2. *Imitated Peter recently his best employee during the Christmas dinner.
3. *Transferred Jennifer in the afternoon three employees to a different office.
4. *Invited Susan after dinner some colleagues to her birthday party.
5. *Chatted Janet some time ago with her new students for a long time.
*V3 sentences:
Average sentence length: 9.2 words
Average syllables per sentence: 16.4 syllables
1. *Recently David consulted an accountant during a five-hour meeting.
2. *Yesterday John inspected the homework with increased rigor.
3. *In the afternoon Emma returned the library books to the stacks.

131

4. *After dinner Chloe smashed the guitar without any warning.
5. *Some time ago Jennifer filled the bucket with apples.
*V4 sentences:
Average sentence length: 9.8 words
Average syllables per sentence: 18.2 syllables
1. *Yesterday Jim the television show recorded with their new VCR.
2. *Recently Paul much furniture imported for her new weekend retreat.
3. *In the afternoon Peter his decision undermined with poignant arguments.
4. *After dinner Susan the envelope sealed with wax.
5. *Some time ago Janet the payments suspended for an indefinite period.

132

APPENDIX C

Debriefing Interview Questions
1a. During the first session of this experiment, did you notice any grammar patterns or
regularities for the sentences that you heard and repeated?

1b. If yes, please indicate what you believe you have noticed.

2. Do you think that the film clips or images affected your performance in any of the
experimental tasks? How so?

3. How did the content of the film clips and images make you feel during the experiment?
Please explain.

133

APPENDIX D

Film Clips and Images, Initial Emotional Induction
The following tables present information on the name and description of the film clips
(Carvalho et al., 2012) and images (Lang et al., 2008) shown to each treatment group during
Phase 2 (initial emotional induction) of the experiment. Subjective measurements, as reported
from the EMDB* and IAPS**, are also included.
Table D1
Practice Film Clip for Each Group, Initial Induction
Clip No.
6000

Name
Homemade footage 1

Content
Objects

Description
Moving objects on a table

Valence M (SD)
4.90 (1.82)

Arousal M (SD)
2.44 (2.23)

Valence M (SD)
6.70 (1.55)

Arousal M (SD)
5.82 (1.87)

7.15 (1.50)

5.99 (1.84)

6.11 (2.10)

5.63 (2.22)

6.48 (1.70)

6.00 (1.78)

6.54 (1.74)

6.11 (1.85)

Table D2
Practice Images for Each Group, Initial Induction
Slide No.
7003
7004

Description
Disk
Spoon

Valence M (SD)
5.00 (1.22)
5.04 (0.60)

Arousal M (SD)
3.07 (1.98)
2.00 (1.66)

Table D3
Positive Group Film Clips, Initial Induction
Clip No.
2000

Content

2002

Name
Underworld:
Evolution
9 Songs

2003

Killing Me Softly

Erotica

2004

Kama Sutra: The
Sensual Art of
Love Making
Diary of a
Nymphomaniac

2009

Description
Sex scene between a man
and a woman
Couple having sex in the
living room; she is
sitting on the sofa while
he is standing
Couple having bondage
sex near the fireplace
Couple having sex in the
arch position
Couple having sex on a
small sofa

134

Table D4
Positive Group Images, Initial Induction
Slide No.
4220
4225
4490
4597
4604
4607
4608
4609
4611
4640
4664
4670
5623
5910
7270
7279
7450
8021
8161
8501

Description
Erotic female
Erotic female
Erotic male
Romantic
Erotic couple
Erotic couple
Erotic couple
Couple
Erotic couple
Romance
Erotic couple
Erotic couple
Windsurfers
Fireworks
Ice cream
Alcohol
Cheeseburger
Skier
Hang glider
Money

Valence M (SD)
8.02 (1.93)
6.09 (1.82)
6.27 (1.95)
6.95 (1.65)
5.98 (1.76)
7.03 (1.84)
7.07 (1.66)
6.71 (1.67)
6.62 (1.82)
7.18 (1.97)
6.61 (2.23)
6.99 (1.73)
7.19 (1.44)
7.80 (1.23)
7.53 (1.73)
6.22 (1.92)
6.40 (2.01)
6.79 (1.44)
6.71 (1.64)
7.91 (1.66)

Arousal M (SD)
7.17 (2.69)
5.39 (2.38)
6.06 (2.42)
5.91 (1.86)
6.09 (1.87)
6.34 (2.16)
6.47 (1.96)
5.54 (2.05)
6.04 (2.11)
5.52 (2.28)
6.72 (2.08)
6.74 (2.03)
5.67 (2.32)
5.59 (2.55)
5.76 (2.21)
5.19 (2.09)
5.05 (2.22)
5.67 (2.37)
6.09 (2.24)
6.44 (2.29)

Table D5
Negative Group Film Clips, Initial Induction
Clip No.
1000
1001

Name
The Ruins

1002

Texas Chainsaw
Massacre: The
Beginning
Midnight Meat Train

1004
1008

Hostel 2
The Rest Stop

Content

Horror

Description
Amputation scene on top
of the ruins
Leatherface removing the
face of a victim

Valence M (SD)
2.04 (1.98)

Arousal M (SD)
7.11 (1.77)

1.68 (1.45)

7.45 (1.77)

Murderer removing the
eyes and teeth of a
victim
Cannibalism scene
Young woman shooting a
policeman in the head

1.67 (1.36)

7.72 (1.67)

2.07 (1.91)
1.94 (1.41)

6.88 (1.95)
6.53 (2.05)

135

Table D6
Negative Group Images, Initial Induction
Slide No.
2811
3000
3001
3010
3016
3017
3030
3102
3120
3130
3195
3350
3500
6022
6560
9040
9252
9325
9420
9904

Description
Gun
Mutilation
Headless body
Mutilation
Mutilation
Mutilation
Mutilation
Burn victim
Dead body
Mutilation
Stitches
Infant
Attack
Assault
Attack
Starving child
Dead body
Vomit
Soldier
Car accident

Valence M (SD)
2.17 (1.38)
1.45 (1.20)
1.62 (1.14)
1.79 (1.28)
1.90 (1.31)
2.45 (1.35)
1.91 (1.56)
1.40 (1.14)
1.56 (1.09)
1.58 (1.24)
2.06 (1.23)
1.88 (1.67)
2.21 (1.34)
2.14 (1.55)
2.16 (1.41)
1.67 (1.07)
1.98 (1.59)
1.89 (1.23)
2.31 (1.59)
2.39 (1.36)

Arousal M (SD)
6.90 (2.22)
7.26 (2.10)
6.64 (2.54)
7.26 (1.86)
5.82 (2.44)
5.34 (2.39)
6.76 (2.10)
6.58 (2.69)
6.84 (2.36)
6.97 (2.07)
6.36 (2.25)
5.72 (2.23)
6.99 (2.19)
6.09 (2.47)
6.53 (2.42)
5.82 (2.15)
6.64 (2.33)
6.01 (2.54)
5.69 (2.28)
6.08 (2.06)

Table D7
Neutral Group Film Clips, Initial Induction
Clip No.
5000
5001
5002
5003
5004

Name

Content

Disney’s Earth

Scenery

Description
Desert and polar scenes
Mountains with ice
Polar scenes; ice moving
Waterfalls
Flowers and trees

136

Valence M (SD)
5.88 (1.99)
5.83 (1.67)
5.68 (1.70)
6.53 (1.73)
6.57 (1.56)

Arousal M (SD)
2.99 (2.25)
2.72 (2.03)
2.51 (1.86)
3.52 (2.12)
2.99 (1.82)

Table D8
Neutral Group Images, Initial Induction
Slide No.
7006
7009
7010
7011
7012
7013
7014
7016
7017
7018
7019
7020
7021
7025
7026
7030
7031
7036
7184
7185

Description
Bowl
Mug
Basket
Gas can
Rubber bands
Lightbulb
Scissors
Razor
Video
Screw
Tools
Fan
Whistle
Stool
Picnic table
Iron
Shoes
Shipyard
Abstract art
Abstract art

Valence M (SD)
4.88 (0.99)
4.93 (1.00)
4.94 (1.07)
4.52 (1.16)
4.98 (1.05)
4.20 (1.35)
5.15 (0.97)
4.76 (1.08)
5.18 (1.07)
4.81 (0.88)
5.20 (1.17)
4.97 (1.04)
5.21 (1.22)
4.63 (1.17)
5.38 (1.26)
4.69 (1.04)
4.52 (1.11)
4.88 (1.08)
4.84 (1.02)
4.97 (0.87)

Arousal M (SD)
2.33 (1.67)
3.01 (1.97)
1.76 (1.48)
3.81 (1.67)
3.00 (1.94)
4.11 (2.02)
3.25 (2.03)
3.40 (1.71)
3.12 (1.97)
3.91 (1.97)
3.36 (1.87)
2.17 (1.71)
4.17 (2.22)
2.71 (2.20)
2.63 (1.93)
2.99 (2.09)
2.03 (1.51)
3.32 (2.04)
3.66 (1.89)
2.64 (2.04)

*For the EMDB, both valence and arousal were measured on a 9-point Likert scale. Ratings
were from the overall sample size, N = 113 (75 females).
**For the IAPS, both valence and arousal were measured on a 9-point Likert scale. Ratings were
from the overall sample size, N = 100 (50 females).

137

APPENDIX E

Images, Exposure Phase
The following tables present information on the name and description of the images
(Lang et al., 2008) shown to each treatment group during Phase 3 (embedded stimuli within the
incidental learning task) of the experiment. Subjective measurements, as reported from the
IAPS**, are also included.
Table E1
Positive Group Images, Exposure Phase
Slide No.
1650
4250
4311
4626
4676
4681
4689
4694
4695
4697
4698
4800
4810
5626
5629
7280
7400
7402
7405
7451
7499
7508
8185
8186
8300
8341
8370
8490
8496
8531

Description
Jaguar
Attractive female
Erotic female
Wedding
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Hang glider
Hiker
Wines
Candy
Pastry
Cupcakes
Hamburger
Concert
Ferris wheel
Skydivers
Sky surfer
Pilot
Wing walker
Rafting
Rollercoaster
Waterslide
Sports car

Valence M (SD)
6.65 (2.25)
6.79 (2.05)
6.66 (1.76)
7.60 (1.66)
6.81 (1.67)
6.69 (1.82)
6.90 (1.55)
6.69 (1.70)
6.84 (1.53)
6.22 (1.76)
6.50 (1.67)
6.44 (2.22)
6.56 (2.09)
6.71 (2.06)
7.03 (1.55)
7.20 (1.80)
7.00 (1.64)
5.98 (2.04)
7.38 (1.73)
6.68 (2.11)
6.47 (1.57)
7.02 (1.46)
7.57 (1.52)
7.01 (1.57)
7.02 (1.60)
6.25 (1.86)
7.77 (1.29)
7.20 (2.35)
7.58 (1.63)
7.03 (1.50)

Arousal M (SD)
6.23 (1.99)
5.16 (2.76)
6.67 (2.19)
5.78 (2.42)
6.07 (2.22)
6.68 (1.70)
6.21 (1.74)
6.42 (2.08)
6.61 (1.88)
6.62 (1.69)
6.72 (1.72)
7.07 (1.78)
6.66 (2.14)
6.10 (2.19)
6.55 (2.11)
4.46 (2.38)
5.06 (2.23)
5.05 (2.12)
6.28 (2.16)
5.84 (2.03)
5.58 (2.16)
5.09 (2.11)
7.27 (2.08)
6.84 (2.01)
6.14 (2.21)
6.40 (2.27)
6.73 (2.24)
6.68 (1.97)
5.79 (2.26)
5.41 (2.15)

138

Table E2
Negative Group Images, Exposure Phase
Slide No.
2717
2800
2981
3015
3062
3064
3068
3071
3080
3110
3168
3191
3261
3266
3400
6021
6230
6231
6250
6312
6370
6550
6563
9183
9302
9326
9410
9635.1
9810
9921

Description
Drug addict
Sad child
Deer head
Accident
Mutilation
Mutilation
Mutilation
Mutilation
Mutilation
Burn victim
Mutilation
Battered female
Tumor
Injury
Severed hand
Assault
Aimed gun
Aimed gun
Aimed gun
Abduction
Attack
Attack
Attack
Hurt dog
Toilet
Vomit
Soldier
Man on fire
KKK rally
Fire

Valence M (SD)
2.58 (1.32)
1.78 (1.14)
2.76 (1.94)
1.52 (0.95)
1.87 (1.31)
1.45 (0.97)
1.80 (1.56)
1.88 (1.39)
1.48 (0.95)
1.79 (1.30)
1.56 (1.06)
1.95 (1.22)
1.82 (1.34)
1.56 (0.98)
2.35 (1.90)
2.21 (1.51)
2.37 (1.57)
2.49 (1.54)
2.83 (1.79)
2.48 (1.52)
2.70 (1.52)
2.73 (2.38)
1.77 (1.23)
1.69 (1.10)
2.32 (1.41)
2.21 (1.30)
1.51 (1.15)
1.90 (1.31)
2.09 (1.78)
2.04 (1.47)

Arousal M (SD)
5.70 (2.16)
5.49 (2.11)
5.97 (2.12)
5.90 (2.82)
5.78 (2.57)
6.41 (2.62)
6.77 (2.49)
6.86 (2.05)
7.22 (1.97)
6.70 (2.16)
6.00 (2.46)
5.95 (2.17)
5.75 (2.64)
6.79 (2.09)
6.91 (2.22)
6.06 (2.38)
7.35 (2.01)
6.82 (2.11)
6.54 (2.61)
6.37 (2.30)
6.44 (2.19)
7.09 (1.98)
6.85 (2.18)
6.58 (2.12)
5.58 (2.43)
5.89 (2.35)
7.07 (2.06)
6.54 (2.27)
6.62 (2.26)
6.52 (1.94)

139

Table E3
Neutral Group Images, Exposure Phase
Slide No.
7038
7043
7061
7062
7077
7080
7081
7090
7092
7100
7110
7130
7140
7150
7160
7161
7170
7175
7179
7180
7183
7186
7190
7205
7207
7217
7224
7233
7234
7235

Description
Shoes
Drill
Puzzle
Sewing
Stove
Fork
Luggage
Book
Scale
Fire hydrant
Hammer
Truck
Bus
Umbrella
Fabric
Pole
Lightbulb
Lamp
Rug
Neon building
Checkerboard
Abstract art
Clock
Scarves
Beads
Clothes rack
File cabinets
Plate
Ironing board
Chair

Valence M (SD)
4.82 (1.20)
5.17 (1.26)
5.40 (1.40)
5.27 (1.06)
5.12 (1.46)
5.27 (1.09)
5.36 (1.30)
5.19 (1.46)
4.05 (1.46)
5.24 (1.20)
4.55 (0.93)
4.77 (1.03)
5.50 (1.42)
4.72 (1.00)
5.02 (1.10)
4.98 (1.02)
5.14 (1.28)
4.87 (1.00)
5.06 (1.05)
4.73 (1.31)
5.58 (1.39)
4.63 (1.60)
5.55 (1.34)
5.56 (1.39)
5.15 (1.46)
4.82 (0.99)
4.45 (1.36)
5.09 (1.46)
4.23 (1.58)
4.96 (1.18)

Arousal M (SD)
3.01 (1.96)
3.68 (2.09)
3.66 (1.92)
3.40 (1.94)
4.61 (2.06)
2.32 (1.84)
3.96 (2.24)
2.61 (2.03)
4.38 (2.05)
2.89 (1.70)
2.27 (1.70)
3.35 (1.90)
2.92 (2.38)
2.61 (1.76)
3.07 (2.07)
2.98 (1.99)
3.21 (2.05)
1.72 (1.26)
2.88 (1.97)
3.43 (1.95)
3.78 (2.19)
3.60 (2.36)
3.84 (2.06)
2.93 (2.16)
3.57 (2.25)
2.43 (1.64)
2.81 (1.94)
2.77 (1.92)
2.96 (1.90)
2.83 (2.00)

**For the IAPS, both valence and arousal were measured on a 9-point Likert scale. Ratings were
from the overall sample size, N = 100 (50 females).

140

APPENDIX F

Film Clips and Images, Secondary Emotional Induction
The following tables present information on the name and description of the film clips
(Carvalho et al., 2012) and images (Lang et al., 2008) shown to each treatment group during
Phase 3 (secondary emotional induction) of the experiment. Subjective measurements, as
reported from the EMDB* and IAPS**, are also included.
Table F1
Positive Group Film Clips, Secondary Induction
Clip No.
2001

2005

Name
Playboy’s Clip

2006

Kama Sutra: The
Sensual Art of
Love Making
9 Songs

2007

Monamour

2008

Diary of a
Nymphomaniac

Content

Erotica

Description
Couple having sex;
woman in astride
position while man is
standing
Couple having sex in the
variant yawning and
fixing nail positions
Couple engaging in oral
sex
Couple having oral sex
and intercourse
Couple having sex in the
missionary position

141

Valence M (SD)
6.32 (1.71)

Arousal M (SD)
6.06 (1.83)

6.51 (1.90)

5.83 (1.83)

6.40 (1.61)

5.89 (1.81)

6.58 (1.79)

6.10 (1.67)

6.46 (1.88)

5.51 (2.09)

Table F2
Positive Group Images, Secondary Induction
Slide No.
4232
4290
4520
4643
4650
4656
4658
4659
4660
4672
4680
4687
5950
7282
7289
7460
8030
8170
8178
8502

Description
Erotic female
Erotic female
Erotic male
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Erotic couple
Lightning
Cake
Food
French fries
Skier
Sailboat
Cliff diver
Money

Valence M (SD)
5.95 (2.53)
7.61 (2.56)
6.16 (1.54)
6.84 (1.54)
6.96 (1.54)
6.73 (1.94)
6.62 (1.89)
6.87 (1.99)
7.40 (1.36)
6.00 (2.04)
7.25 (1.83)
6.87 (1.51)
5.99 (2.07)
6.72 (1.48)
6.32 (2.00)
6.81 (2.08)
7.33 (1.76)
7.63 (1.34)
6.50 (2.00)
7.51 (1.72)

Arousal M (SD)
6.28 (2.31)
7.20 (2.63)
4.80 (2.25)
6.01 (2.00)
5.67 (2.14)
6.41 (2.19)
6.47 (2.14)
6.93 (2.07)
6.58 (1.88)
6.29 (2.37)
6.02 (2.27)
6.51 (2.10)
6.79 (1.98)
4.77 (2.08)
5.14 (2.51)
5.12 (2.49)
7.35 (2.02)
6.12 (2.30)
6.82 (2.33)
5.78 (2.49)

Table F3
Negative Group Film Clips, Secondary Induction
Clip No.
1003

Name
Hostel

1005

Midnight Meat Train

1006

Cannibal Holocaust

1007

Texas Chainsaw
Massacre: The
Beginning
Midnight Meat Train

1009

Content

Horror

Description
Victim being tortured on a
chair; fingers from his
hand are amputated
Woman inside a subway
car with bodies hanging
from the ceiling
Savage cannibal attack on
man with
dismemberment
Scared woman, hidden,
watching Leatherface
mutilate her boyfriend
Woman is attacked and
decapitated

142

Valence M (SD)
2.99 (2.00)

Arousal M (SD)
6.19 (2.20)

2.06 (1.48)

6.92 (1.74)

1.98 (1.50)

7.37 (1.88)

1.81 (1.43)

7.33 (1.91)

1.83 (1.24)

6.88 (1.70)

Table F4
Negative Group Images, Secondary Induction
Slide No.
3005.1
3053
3059
3060
3063
3069
3131
3170
3225
3530
6212
6243
6313
6520
6570
9075
9185
9405
9413
9940

Description
Open grave
Burn victim
Mutilation
Mutilation
Mutilation
Mutilation
Mutilation
Baby tumor
Mutilation
Attack
Soldier
Aimed gun
Attack
Attack
Suicide
Starving child
Dead dog
Sliced hand
Hanging
Explosion

Valence M (SD)
1.63 (1.19)
1.31 (0.97)
1.81 (1.24)
1.79 (1.56)
1.49 (0.96)
1.70 (1.41)
1.51 (0.97)
1.46 (1.01)
1.82 (1.22)
1.80 (1.32)
2.19 (1.49)
2.33 (1.49)
1.98 (1.38)
1.94 (1.27)
2.19 (1.72)
1.66 (1.10)
1.97 (1.16)
1.83 (1.17)
1.76 (1.08)
1.62 (1.20)

Arousal M (SD)
6.20 (2.54)
6.91 (2.57)
6.48 (2.32)
7.12 (2.09)
6.35 (2.60)
7.03 (2.41)
6.61 (2.34)
7.21 (1.99)
5.95 (2.46)
6.82 (2.09)
6.01 (2.44)
5.99 (2.23)
6.94 (2.23)
6.59 (2.08)
6.24 (2.16)
6.04 (2.40)
5.65 (2.35)
6.08 (2.40)
6.81 (2.09)
7.15 (2.24)

Table F5
Neutral Group Film Clips, Secondary Induction
Clip No.
5005
5006

Name

Content

5007

Disney’s Earth

Scenery

5008
5009

Description
Sandstorm and desert
Several takes of trees
Scenes of trees, waterfalls,
and sand
Scenes from a jungle;
mushrooms growing
Clouds swirling

143

Valence M (SD)
5.32 (1.06)
6.23 (1.63)

Arousal M (SD)
2.86 (1.97)
2.86 (2.17)

6.28 (1.57)

3.20 (2.36)

5.73 (1.54)

2.54 (1.95)

6.17 (1.44)

2.79 (1.80)

Table F6
Neutral Group Images, Secondary Induction
Slide No.
7032
7034
7035
7037
7040
7041
7044
7045
7046
7050
7052
7053
7055
7056
7057
7058
7059
7060
7187
7188

Description
Shoes
Hammer
Mug
Trains
Dust pan
Baskets
Scale
Zipper
Pill
Hair dryer
Clothespins
Candlestick
Lightbulb
Tool
Coffee cup
Dice
Keyring
Trash can
Abstract art
Abstract art

Valence M (SD)
4.82 (1.46)
4.95 (0.87)
4.98 (0.96)
4.81 (1.12)
4.69 (1.09)
4.99 (1.12)
4.69 (1.40)
4.97 (0.76)
4.18 (1.38)
4.93 (0.81)
5.33 (1.32)
5.22 (0.75)
4.90 (0.64)
5.07 (1.02)
5.35 (1.37)
5.29 (1.38)
4.93 (0.81)
4.43 (1.16)
5.07 (1.02)
5.50 (1.12)

Arousal M (SD)
3.18 (1.88)
3.06 (1.95)
2.66 (1.82)
3.71 (2.08)
2.69 (1.93)
2.60 (1.78)
3.94 (2.17)
3.32 (1.96)
4.14 (2.04)
2.75 (1.80)
3.01 (2.02)
2.95 (1.91)
3.02 (1.83)
3.07 (1.92)
3.39 (2.01)
3.98 (2.17)
2.73 (1.88)
2.55 (1.77)
2.30 (1.75)
4.28 (2.16)

*For the EMDB, both valence and arousal were measured on a 9-point Likert scale. Ratings
were from the overall sample size, N = 113 (75 females).
**For the IAPS, both valence and arousal were measured on a 9-point Likert scale. Ratings were
from the overall sample size, N = 100 (50 females).

144

APPENDIX G

Self-Assessment Manikins
The emotional self-assessment using the SAMs on a 9-point Likert scale (adapted from
Bradley and Lang (1994)). Note that the first row represents valence and the second row arousal.

Figure G1. SAM ratings for valence and arousal.

145

APPENDIX H

Written Background Questionnaire
Please answer the following background questions:
1. What is your sex (male/female)? ____________
2. What is your age? ____________
3. What is your native language? _________________________
4. Please list all of the foreign languages that you speak and the number of years of study:
a. _________________________; years studied __________
b. _________________________; years studied __________
c. _________________________; years studied __________
d. _________________________; years studied __________
5. What types of movies do you normally watch?
______________________________________________________________________________

Thank you for your time!

146

APPENDIX I

Verbal Reports
Table I1
Noticed Verb Patters or Grammatical Regularities, Comparison Group
Subject Report
401

I noticed that they were complete sentences, they had a subject and subjectpredicate. It was kind of mixed up but it kind of reminded me of Spanish, how
sometimes you have to change the order of things…but I couldn’t really figure out
what the order was. Maybe the time was first, then the person, then action.
Sometimes action, then the person…it was weird.

402

I tried to [formulate a rule]. I was looking at a lot of past-tense stuff…other than
that, I really wasn’t getting much.

403

I don’t know if I can put it into words. Just the verbs and all the placement of
them…I understood it as the opposite of regular English grammatical rules. For
example, we would say, “he left in the afternoon.” And here I found, “in the
afternoon left…” Something like that, the placement of the verbs and sometimes the
pronouns as well.

404

Some of them, the tenses, I would try to listen to. And the placement of the verb in
relation to the noun. But, I never really had anything super solid…I was finding
some patterns, but I wouldn’t say that I had a rule.

405

I was trying to figure out some sort of pattern and I felt like there were stints where I
would get three in a row. And I’m like, “maybe there’s an adjective that follows a
noun half-way through the sentence.” But then something would break it, so
anytime I tried to figure out something, there would be a sentence that would
completely throw it off.

406

Yeah, I noticed that sentences we would speak in English, just the structure was a
little backwards. So, just the way you would formulate a sentence would have other
words, like descriptor words, for words we would normally say after that…so it
would have verbs at the end instead of where we would normally put them. So, just
the same sentences we would speak, just in a different order.

407

Yes, there’s two rules that I kind of distilled out. The one that I’m fairly confident
with was that if it sounds like proper syntax in English, then it’s probably wrong.
The other one, and I’m not certain about this one, was this format that was, “timeverb-person-everything else.” So like, “yesterday went David to the store.” There
were a few other ones, but I can’t crystalize them right now in my head.

147

Table I1 (cont’d)
Subject Report
408

I felt like the action would come before the name or before the subject of the
sentence. So it would be, “received Carly,” or something like that. I thought that
might be one of the syntax rules for this new language. It [also] seemed like an
inverted English sentence.

409

Not really. Maybe subconsciously, but I wasn’t really trying to come up with a rule.

410

I felt like they were switched…so the verb was changed to go behind a word, or
before. I feel like it was before. So, “the market she went.” That’s what I always
noticed. So it was after, I guess. I noticed that most of the sentences didn’t start
with a name. If they did, it was second or at the end. If it didn’t start with a name, it
was in the second, like run-on sentence, or later in the sentence.

411

I noticed they would switch verbs and nouns around. Like, they would first
say…instead of saying, “Janet ran,” they would say, “ran Janet,” or something like
that…that was my basis for determining if something was grammatical, was if it
didn’t make sense in English.

412

It appeared that the subject of the sentence was flipped…when you have a
conversation about something, you address what the subject is and then say what
you are doing to it. The new sentences, it seemed like it was flipped, where it had
the action, then told you what happened or what the subject was after the action.

413

Yeah, it seemed like the sentences were flipped backwards. It would be one part of
the sentence like, “Janet went to the store, comma, to get a bottle of water.” It
would switch it around, “To get a bottle of water, Janet went to the store,” or
something like that.

414

I thought I noticed that maybe the verb was coming before the noun, but I really
don’t know.

415

No, I did not, which is why I think my percentages were low for both the times
[posttests].

416

I started to notice that the time went first…that was the main one I noticed.

417

It seemed like the noun came before the verb…so the sentences were mixed up.

418

No.

419

Yeah, it was just a little goofy…one rule was, something that should have been at
the middle or the end of the sentence was at the beginning of it.

420

I wasn’t really focusing on the grammatical setting of it…I honestly couldn’t pick
out any rule.

148

Table I1 (cont’d)
Subject Report
421

It seemed that the verb came before the subject, unless it had an object. So, like,
“ran Jim” or “Jim to the store ran.” The object came between the subject and verb,
if there was an object.

422

Yes…the time, or the setting, or the underlying where, what or when, and then the
verb, and then the subject, and then the object. That’s the structure I was looking
for.

423

I noticed that the ends of the sentences were all past tense, a lot. Or, if the sentence
was broken up in half by a comma, then the part before the comma would end in a
past tense.

424

The verbs and the nouns were flipped around. Sometimes the verbs came before
and sometimes the nouns came before, but it was a noun from the end of the
sentence. Sometimes the noun that would have been at the end of the sentence was
at the beginning of the sentence.

425

It was kind of like Yoda talk and everything was backwards.

426

I couldn’t identify a specific set of rules.

427

I kind of started basing it off of where the verb was, but that might just be something
that I made up. If it was in the middle of the sentence, I counted it as grammatically
correct if it had already been acted and told what the subject was being acted on.

428

The verb was in front of the name, maybe. I don’t know.

429

Yes. You switch the verb and the subject in the sentence from how you do in proper
English.

430

It had something to do about time phrases…where you place them in the sentence.
That was the only rule that seemed to exist…[but] I wasn’t sure.

149

Table I2
Noticed Verb Patterns or Grammatical Regularities, Positive Group
Subject Report
101

I tried to, and I think it was the verb went towards the beginning, I think…I was
trying to find a rule, but I don’t think that I got one.

102

I know there was like, the noun and the verb and that stuff was switched up a little
bit. So, those were some of the cues that I could figure out.

103

Yeah, I think I found at least one. Like, putting a verb before someone’s name, like,
“delivered Karen the envelope.” That’s the big one that I noticed.

104

Yes, it was like the subject and verb were messed up (flipped). The verb came first,
before the subject, instead of the other way around like it normally is [in English].

105

It kind of reminded me of how Yoda speaks, from Star Wars. If there was ever a
time or a place, the place would be stated first…uh, no, it would be time and then
place. So, “recently, something, something, John did eat” or “John ate something.”
And the last part would be preposition-subject. Like, time-subject-preposition, I
think. I don’t know, it was a weird way.

106

Yes. I thought that the sentences should say the verb that they were doing first, then
their name. If it was talking about someone else they knew, then it would say their
name, or who they were, then it would describe something and then say the verb.
Also, I wasn’t sure if this part of the rule was right, but in the beginning it would
say, “after dinner washed Jane the dishes,” or something like that. I wasn’t sure if
the “after dinner” had to come first, so I assumed that it did have to come first.
Also, the whole “after dinner” thing, or “sometimes,” or whatever timing…if they
were talking about someone else, too, then it would say, “her children after dinner
the games played.” So, it would put their name, then the time, then describing the
thing, and then the action.

107

Yeah…you could tell where the verbs and the…you can tell that it’s not regular
English. So the person does the action in the second part of the sentence and then
the first part of the sentence you’re describing…I really don’t know.

108

I noticed that a lot of the times it would be that the subject came after the verb,
which I know is different from English. It would be like, “yesterday cooked Jim the
meal.” I kept noticing that as a repeating pattern.

109

Yes. So, I feel like what the grammar rule was…is that in the sentence, you would
say the noun before the verb…like, “Joe to the park walked.”

110

I definitely noticed that if it was a two-part sentence, both parts of the sentence were
scrambled up…not in the correct grammatical order [according to] regular English.

150

Table I2 (cont’d)
Subject Report
111

Yeah…normally, we would say, “Kevin jumped,” but in the [new] language it
would be, “jumped Kevin.” And I think there was something with the accuracy of
the time because sometimes it would be like “yesterday” and sometimes it was “a
long time ago.” It was more vague.

112

I thought I did. I felt like there could be a comma in everything, the way that the
sentence started. It starts with the end and the beginning is after that, separated by a
comma. I could recognize a pattern. It’s hard to articulate what it actually is.

113

There definitely was some word order. It would be like some point in time. Maybe
a subject…ends with a verb. Sometimes there were two verbs. A first phrase and a
second phrase…but it was quite different from English.

114

Kind of. None that I could pinpoint exactly, but I could definitely tell it was
following some sort of rule.

115

I was trying to figure out the verb stuff. The verb thing, I think I was picking
out…they verbs were coming before in the sentences, like, “because Janet talked, a
new paper she wrote.” It was almost like things were reversed.

116

Yeah. They would switch the nouns and the verbs, it looked like…just the word
grammar pattern.

117

I didn’t notice an explicit rule. I did notice a pattern…with the noun and verb
order…but nothing that I could express.

118

I noticed…it wouldn’t say “to the,” “in,” all those words that you use to complete a
sentence…it would skip those and be like, “Sally door to calf.” It would skip,
“Sally walked to the door.” That’s what I was looking for.

119

Yeah, it was just a matter of switching the verb and the noun, as compared to our
language.

120

I noticed that most of the time, they were two-claused. There was a first part and a
second part of the sentence. The first part introduced the subject of the sentence and
the second part almost qualified what was happening in the second part.

121

I would look for mixed-up, or words that didn’t necessarily go in order. I guess the
key of the sentence structure would be towards the end. Like, the main subject of
the sentence.

122

No.

151

Table I2 (cont’d)
Subject Report
123

I don’t really know how to explain it, but when I would hear the
sentences…sometimes I would re-arrange them to how I thought they should be.
The last two parts of the sentences seemed to be switched. If the sentence was in
English, like, “Sarah went to the store,” then it [this new language] would be like,
“Sarah to the store went.” If there were two parts to the sentence…I felt like they
were [also] in that form…both parts.

124

The only rule that I could decipher was that the normal way sentences would go [in
English], that that wasn’t the [new] language. That’s the only rule I picked up on.

125

Not specifically, no.

126

The verb was switched. That’s what I thought it was. They switched the verb with
the person.

127

If there are two verbs, they have to be reversed…with the noun they’re acting on.

128

It seems like sometimes the verb has to come before the subject…sometimes it
would be the opposite.

129

I didn’t at first, but then I noticed that the verb was coming before the noun in the
first part of the sentence. [The noun was] a person’s name.

130

I kind of noticed a pattern between the verb and subject of the sentence. [Also], if
there were two clauses, there was one rule for the first part and one rule for the
second. In the first part, it seemed that the verb always came before the subject. In
the second part, it was how we would normally say the sentence [in English] or it
was the same as the first part. But, I couldn’t figure it out.

152

Table I3
Noticed Verb Patterns or Grammatical Regularities, Negative Group
Subject Report
201

I didn’t notice it as much the first time, but listening to it again now I did notice
some rules. Like verbs coming before nouns as opposed to vice versa with English.
One thing I did notice both times was weird placement of prepositional phrases…it
was jarring hearing prepositional phrases thrown into different places.

202

I didn’t really pick up on any rules…nothing that I could put into words.

203

Yes, it seemed like the verbs went before a noun. So, instead of the “subject
performs this verb,” the verb comes before the subject.

204

Sometimes it was the way the words were said…sometimes the beginning of the
sentence would be switched up and the end would be OK. Sometimes the beginning
would be OK and the end would be switched up.

205

In certain situations, the verb would come before the noun or at the beginning of the
sentence, and then in other cases it came at the end of the sentence…that’s the main
thing that I noticed, the order of the subject-verb.

206

I don’t think I really paid attention that much when I first did it…I don’t think I was
looking for anything. At the time I knew I was listening to weird sentences. But I
did hear a lot of the sentences where the action words were at the end…but I don’t
know. Today I was thinking that maybe it could have been actions words in the
middle of the sentence or at the beginning. Or when there are two parts to a
sentence, the rule could have been different, but I don’t know.

207

No. For me, at least, it took me a lot of focus to not rearrange them [the
sentences]…sometimes I wanted to put the words in what I think of as grammatical
[English] order. So, I didn’t have rules, per se, that I was developing.

208

No, not until after you told me that they were grammatically correct. Then I tried to
remember back and figure out a rule. But when I was just repeating them, it was
gibberish to me.

209

Kind of. I noticed in some sentences, a word would be in the middle instead of the
beginning…like, if I said, “I ran to the store,” it would be like, “the store ran I.”

210

No.

211

There was a lot of inverted word order, sometimes twice in a sentence. You would
start with a prepositional phrase and then, it was kind of opposite of American
syntax, English syntax…you would put the indirect object before the word used to
address that part of speech. The subject and predicate were often separated from
each other. The way that I could tell things weren’t a part of this proper grammar
was that they were just in a natural word order [to English].

153

Table I3 (cont’d)
Subject Report
212

I felt like I did at certain points, and as it went on and I heard more sentences, I
questioned the rules that I thought I picked up on…I would listen to the end of the
sentence to see if it was verb, if they were putting a verb at the end of the sentence,
versus if they were talking about what they did at the end of the sentence. Like if
they said, “at the table,” versus “table” then like “sitting at.”

213

It sounded as if the time or place…was at the beginning of the sentence. So, that’s
what I tried to base one of the rules on.

214

N/A

215

Sort of, but not anything to a high level…not anything structured or what I could put
into words.

216

Not really when I was repeating them back because I was just so focused on getting
it right.

217

Yeah…I think in most sentences it wouldn’t be a simple subject-verb, in that order.

218

They’d say the verb before the subject. That’s the only rule I got out of it.

219

Yeah, I noticed a lot of it…was very backwards…like, “yesterday, blank, someone
did something later,” as opposed to, “Maria did this.”

220

That the verb was at the end. So, it would be like, “she store goed,” or something
like that.

221

I think the sentences never started with nouns…at the very least, the sentences never
started with names. [Also] every fragment of the sentences was scrambled in some
way. So, with some of these tests, if I noticed that the second half of the sentence
made sense in the English language, then I’d be like, “ok, it didn’t make sense [in
the new language].”

222

It seemed like the time was listed first, and then a noun or an adjective would be
right after it.

223

Not really, no.

224

I just noticed that they seemed to be flipped. Like, “if Jennifer was talking,” “talked
Jennifer about whatever.” It seemed backwards, the placing of the words.

225

I could tell that it was switched…the subject was after the action of the sentence.
Like, “to Paris John went” instead of, “John went to Paris.”

226

I thought that it either had something to do with the time, like, “before dinner” or
“yesterday.” I thought the time had to come before the subject and then the action.
Or, I thought that it ended with the action.

154

Table I3 (cont’d)
Subject Report
227

Yeah…if the words were out of order [as compared to English], then that’s one way
I determined if it was grammatical.

228

N/A

229

I kind of guessed that one of the rules might have been if one word was switched
around with another word.

230

Yeah…something like they would have feeling first, like the action the guy did.
Like, “Jack was upset about getting fired from his job,” it would be like, “upset after
getting fired from his job was Jack.” Something like that.

155

Table I4
Noticed Verb Patterns or Grammatical Regularities, Neutral Group
Subject Report
301

I think what I started picking up was that the action word came after the object, so
after the noun. There was a distinct order in which you’d say the person and you’re
looking for what they did, but where they did it came first, and then what they did
was coming next.

302

The chronological order of things…when you’re including a “day” of some sort,
like a “yesterday” or a “during this time” was always misplaced in the sentence a
little bit. That was one thing that I noticed. Nouns, specifically people, were often
misplaced. Just hardly, but enough for you to realize it.

303

If it ended in a location or ended in a verb, then that was my rule.

304

The only thing I did notice was that a lot of the things were flipped or backwards. I
knew that if it sounded too “good” it probably was not a rule. Things that sounded
more confusing to me was how I was indicating whether it was part of the new
grammar or not.

305

I think today I tried to figure out…that the verb comes after the timeframe, maybe.
That’s kind of what I put together today [Session 2]. When I was saying them, I
could definitely feel a rhythm…there were some that were similar, with the back
half of the sentences, but I couldn’t figure it out from there.

306

I don’t think I came up with any rules, no.

307

No, not really.

308

Just where the verb was placed. I feel like the verb can often be placed at the end of
the sentence, instead of after the subject.

309

No.

310

I think the verb was in front of the subject. If you swapped it around, it would make
sense [in English]. But the structure was different. I don’t think I could pick out a
specific rule, though.

311

Yeah. A lot of them had the action before the name. So, “acquired Jennifer,” when
you would normally say, “Jennifer acquired.” So I think that’s one of the rules…it
was also flipped around…like Chinese…their structure is different than ours, but it
still makes sense.

312

The two things that stuck out to me were the verb comes before the subject…so it
would be like, “drank Paul yesterday.” I’m not sure about this one, but it would be
something with the prepositions, like “after dinner” or “yesterday.” Like,
“yesterday drank Paul” and then there’s some that said, “drank Paul yesterday.”

156

Table I4 (cont’d)
Subject Report
313

Not initially.

314

Yeah, a lot of times the past part of the sentence would come before the first part of
the sentence. The antecedent would come last, if that makes any sense. I didn’t
know if it was all the time or if it was specifically for action sentences, but I noticed
that.

315

I think generally the noun after the verb was before the verb, that kind of thing. So
instead of, “I ate pizza,” it was like, “pizza ate Jan.” It was out of order from the
English way.

316

It’s almost like listening to Yoda, where everything is backwards. It was pretty
clear to me that if it sounded like normal English, it was almost certainly incorrect.

317

If you had a sentence or a phrase, the verb could be in the first part of the phrase,
like, “John went to the store.” But if there was a comma or another clause after that,
it felt like if you immediately put another verb, like, “John to the store went,” then
you had another verb right after that, it just felt wrong for some reason.

318

The first time I noticed a pattern…it seems to start with a time signifier, like
“yesterday” or “in the morning.” Then it goes subject-object-verb and a
prepositional phrase.

319

Yeah, I noticed that some things were backwards. Like, a verb and a noun were
flipped. And usually at the end…words were put backwards, like, “this is a cat,” it
would be like, “this cat is.”

320

It seemed like the verb was at the end of a lot of the sentences. So, she would say a
bunch of things and the last word would be “arrived” or “lived.” So, that was the
general rule I was using.

321

Yeah, the verb always came before the subject.

322

It seemed like the sentence never started with its subject. I think it started with
time…and then it would move onto the subject, and then where it happened, and I
think the action was generally last.

323

I think it was something like the verbs were in different places, like, before the
pronouns or the names a lot of times.

324

Yeah…do you know how you have a preposition between the person and the object?
It was reversed. So, it was the object, preposition, and then the person.

157

Table I4 (cont’d)
Subject Report
325

It seemed like if there was a clause that preceded the main part of the sentence, the
verb and the object switched places. So, the verb always came after the object of the
verb. And then in the main clause, I think, the verb always preceded the person
doing the verb.

326

I felt like the second verb was in the past tense, or moved to a different place than it
would in a regular English sentence.

327

I don’t think so. No.

328

Yes. I feel like a lot of them used more of a passive voice-type grammar rule, where
it was the action, then the person, and then the stuff afterwards.

329

The verb would come before the subject sometimes. It would say, “walked Ashley
to blah, blah, blah,” rather than, “Ashley walked to…” That was the big thing that I
noticed.

330

It seemed like the subject was coming at the end of the sentence or in parts where
whatever action the subject was doing would come before the introduction of the
subject.

158

APPENDIX J

Impacts from Film Clips and Images
Table J1
Impacts from Film Clips and Images, Positive Group
Subject Report
101

I don’t think so…because by the time I had to start saying stuff, I was focusing on
that.

102

Maybe at the very beginning, but I think I just kind of got used to them…they just
became a part of the test.

103

I don’t think so…it’s hard to affect me in that way, but maybe they did.

104

No, I don’t think so.

105

No, they were just annoying. It was like, “really?”

106

A little bit. Sometimes, I could just ignore them and then focus on the words. But
sometimes they would pop up at a certain time when I was trying to think about
something, then it showed me, and threw me off a little bit…because the images
were very “out there,” so it wasn’t something I was expecting to see.

107

Sort of. Some of the clips were really long, so they distracted me. Sometimes I’m
trying to remember what was said and then suddenly there is a clip or an image, and
I’m like, “oh, OK.” So, I didn’t really remember what was going on before.

108

Yeah, they were definitely distracting. There were a few times where I would be in
the zone and then one of them would pop up and I would forget about what I was
going to write down…I mean it was kind of strange and it was definitely distracting.

109

Yeah. I think during the first part, I’d be trying to say one of the sentences, and it
would come up and distract me a little bit. And sometimes I would forget what I
was supposed to be saying. But I don’t think it had a heavy impact, just a little
distracting. The content…I wouldn’t say was positive for me. I would say it caught
me by surprise. It was like, “whoa!”

110

I think so. Some, when they would pop up randomly, it would avert my attention
from what I was doing and I had to regroup and focus my attention on the task.

111

Probably. It was distracting. They would randomly come up and sometimes they
wouldn’t, so I was wanting to look at them because I wasn’t sure what I was doing,
and I was also trying to think of these sentences, and it was just confusing…I was
definitely shocked by the film clips and not expecting it, so I was a little off-kilter.

159

Table J1 (cont’d)
Subject Report
112

I’d say they were distracting…it was harder to listen to what was going on. You
would want to look at that [images] over listening to what was being said.

113

Yes. Sometimes it was distracting. It would just break the focus…it’s like you’re
trying to repeat something, you’re trying to hear something and repeat it, and
something pops up and you’re like, “oh, what was I thinking of? And did I repeat it
correctly or not?”

114

Maybe a little bit because it got in the way…it was annoying. I just didn’t feel like
seeing it. I was trying to listen and that popped up and I’d be like, “ah, OK.” [I also
felt] irritated, because it’s pretty much like porn and I kind of think porn is gross.

115

Yes…when you’re really trying to concentrate, the last thing you expect to see is
naked people. You’re trying really hard not to pay attention to it, but at the same
time you’re like, “God, what did that girl just say to me over the thing? I just saw
some naked dude. Like, weird.” It definitely threw me for a loop. I don’t think it
completely deterred me from learning, but it was definitely a distraction.

116

I don’t think so.

117

I do feel that there was a bit of, not necessarily a distraction, but it changed my level
of attention away from the task to what was being presented on the screen. So I
would definitely say there was something there with that.

118

I don’t. I was actually kind of confused when I was watching all of those clips.

119

No, I don’t think so. It made it more interesting…but I don’t think it affected how I
took in the information.

120

I don’t think so. I was so focused on memorizing the actual sentences, that was all I
was thinking about really.

121

Yeah, probably…it would just make you lose your train of thought a little bit.
Especially because some of them popped up when we were repeating the sentences.
That really threw me off because it was already hard enough trying to remember
what they said.

122

Yeah, I think they distracted me some. I would have trouble remembering the next
sentence, or the sentence after that more. I think [that the content] got me to a more
aroused state sometimes, and made it harder to concentrate.

123

Yeah, it threw me off sometimes…although if they were cupcakes, it was weird, if
there were images of food, I felt like I got through it more easily…because I really
like food. But the other things…I was like, “what’s going on?” And I would stop
thinking about what I was trying to do.

160

Table J1 (cont’d)
Subject Report
124

Not really. They may have confused me a bit, but not a lot.

125

When random images would pop up…I wasn’t expecting that and I kind of forgot
what I was thinking, how I was processing the information. So, yeah, a little bit.

126

No.

127

Probably distracting…just distracting and aroused.

128

Some of them were distracting. Probably [had an effect], but not to a high level of
degree. They [also] made me feel uncomfortable…it was hard to focus, but I tried.

129

No, [but the] content made me feel uncomfortable.

130

Not really. Maybe a little bit. If it was saying it [a sentence from the exposure set]
and then an image would appear while I was trying to say something, it would
maybe affect me more…trying to repeat the sentence back exactly like I heard
it…being able to remember it.

161

Table J2
Impacts from Film Clips and Images, Negative Group
Subject Report
201

I think definitely yes. Because I’m not very susceptible to those sorts of
things…they don’t bother me very much. But it was just so much that I ended up
getting overwhelmed. I would get nervous, like, “OK, what’s going to come up
next?!” It definitely affected my ability to focus on the language portion of the task.

202

They kind of made me paranoid in the second session, right now. I was wondering
if they were going to pop up or not, like in the first one [session]. I didn’t really
remember a ton of the sentences that were being stated…it was more of the
graphics.

203

I think they threw me off and made me more confused. I was less focused on what I
was trying to do.

204

I watch True Crime and I look at crime scene photos…I watch all that kind of stuff,
horror movies…so “eh.”

205

I don’t think they affected my performance, no. They definitely were not fun to
watch…but no, I don’t think they affected my performance with the tasks at all.

206

No. I don’t even remember them.

207

Yeah. I wasn’t expecting it at times and so it would throw me off a little bit…the
images were a little more violent than I had anticipated, so that surprised me a little
bit and threw my thought process off.

208

Yes, I felt like they were distracting when you would have to listen, and then all of a
sudden something would pop up, and it would throw me off, like, “ohh!” Then I
would forget what I had just heard before. So, yeah I think it did affect me.

209

Yes, they distracted me a little bit. Especially when I was repeating back sentences,
I would get distracted and forget what it said.

210

Yes. First I was getting pretty frustrated trying to say the sentences back, and then
those images made me even more frustrated. They were just so graphic. It was hard
to put my mind back on the task after seeing something like that.

211

I think they did. Over time I kind of got used to them…but, there was one point
where I had to force myself to keep looking at the images because that was what I
was supposed to do, and I just wanted to look away. But I just had to distance
myself emotionally from that so I could focus on the sentences…it was definitely
distracting. It’s upsetting.

212

I don’t think so…I think I kind of got used to if after a while, so it wasn’t affecting
me too much.

162

Table J2 (cont’d)
Subject Report
213

Extremely…I didn’t think the images would be that bad, but to me they were
very…it really affected my emotions. So, especially when listening to [the
sentences] and they would pop up, I would forget almost instantly what was just
read to me. So, that affected it a lot.

214

N/A

215

Not when I first started watching it, but when I was trying to think, I was looking at
the screen and then something would pop up. It would draw my attention away
from what I was thinking about…I lost track of what I was thinking of. I couldn’t
retain the sentence and it was all messed up.

216

Yeah, I think so, because I was like, “uh, ok…” (nervous laughter). Especially
when I pressed the space bar and an image popped up. So, yeah, I think it kind of
affected you because when you’re sad with anything, you’re not going to care as
much or pay attention. So that affected it, definitely. [I felt] sad and not really that
excited to do the task…I didn’t really have much motivation to figure the sentences
out.

217

It was almost like when I was doing the test, it was easier because it was a break
from that…I was clearly not feeling as good after seeing it [the negative stimuli]. It
was almost more enjoyable, I felt relaxed to be doing the problems [on the
immediate posttest]. [After viewing the content] I felt very sad, anxious,
uncomfortable.

218

Yeah, they kind of made me lose my train of thought. [They made me] kind of
cringy and distracted, I guess.

219

Yeah, because I was distracted by it, it kind of caused me to think more on that than
on what I was exactly saying. I think it caused arousal in a certain way that may
have potentially caused me to remember some things a little better. Because I
noticed being back in here, my heart started beating a little faster again, like,
subconsciously…I think maybe it helped a little, which is weird.

220

I think it affect [me] when they showed the picture while I was trying to repeat [the
sentence]. I would look at the screen and then I would be like, “oh shoot, what did
they say?” [The content] was gross. I didn’t like it at all…I didn’t want to look at it
at all.

221

Yeah, it did. On the first part, they distracted me. And for this part, two weeks
later, my memory was very hazy on a lot of the grammatical things…the thing I
took away from the test two weeks ago was the images and not really the grammar
structures. I [felt] distressed. I didn’t like looking at them.

163

Table J2 (cont’d)
Subject Report
222

Yeah, I think so some times, because you’re like, “oh, what’s that,” and then it gets
you off track. [I was] not necessarily [affected by the content] because I watch a lot
of horror movies and disturbing images, so I’m used to it. So, probably not as much
as it should have.

223

There was one time when I got distracted and totally forgot the sentence. But, I got
used to it after three clips. So, maybe at first, but definitely not towards the end…I
don’t think I felt too distressed…things like that usually don’t bother me like some
people.

224

Yes, but not in a good way. When the person was speaking, you’re trying to think
about that. And when the image popped up, my brain went to that image versus
trying to think about the structure of the sentence and what she was saying. Some
[images] definitely made me feel more uncomfortable than others, but I think the
biggest thing is is that they were distracting.

225

I’d say so, just because they were distracting. It’s hard to ignore [the explicit
images and film clips]. It kind of puts you on edge. [They] were disturbing and put
me in a different mood.

226

I don’t think so. No.

227

Yes, sometimes. Sometimes I would just want to look at the clip for a
second…some of them flashed and some of them were kind of gory with a lot of
blood. So, then I was thinking, “ooh, that’s gross,” instead of thinking about the
sentence structure.

228

N/A

229

Definitely. When I saw an image, it totally threw me off and I totally forgot the
sentence that I was supposed to repeat. Some [of the images] were pretty disturbing.

230

At first, no, but when I had to repeat the sentences…it was weird, but I thought
when I saw the picture, it helped me to remember the sentence more. It was really
weird. For the first ten minutes…I felt all scrambled inside. I’ve seen a lot of
horror movies since I was little, so it was fine, it was just when it was all at once, I
was like, “ok, oooh.”

164

Table J3
Impacts from Film Clips and Images, Neutral Group
Subject Report
301

I don’t think so. I didn’t really pay attention to them because I was trying to recall
what I was hearing. So, if anything they kind of gave me an extra second to try to
recall. But they didn’t distract me from what I was doing.

302

Possibly. They may have jolted my memory a bit. I’m super ADD, so when I saw
that stuff, it made me think away from the sentences. Especially when I recited
them, it was like a, “whoa, wait a second” kind of thing. So, I would say they
impacted me.

303

The first time I was getting kind of sleepy because they were somewhat calming
images, like the sky and the desert. I’m already a little tired, so when you throw this
in there I’m watching something that makes me real peaceful. I felt like I could
have been more alert, so it probably hurt me a little bit.

304

Not really, except that I would be thinking of that image as the last thing in my
head. Like, “that thing is called a hammer and that thing is a nail.” But no, it didn’t
really affect anything in terms of learning the grammar or the language.

305

No comment recorded.

306

I think waiting, because they were in between the recording and me repeating them
[the sentences]. So, I guess having to wait affected how well I did, even though it
was only a second.

307

It might have distracted me a little bit, but that’s about it…it might have relaxed me
a little bit.

308

Not particularly, no. They weren’t really disturbing images. They were just
random…it felt completely unrelated [to the incidental learning task].

309

No…I didn’t understand them. Maybe they were a bit distracting, but overall I
don’t think they affected much.

310

Probably not. They were pretty relaxing, so it was kind of chill.

311

I don’t think so. I think that they made me feel…they put me in a calm mood. I
don’t think it affected what I chose. I just feel like it affected how quickly I chose.

312

No.

313

I think they were a little distracting. Sometimes I would get distracted by the fact of
wondering if that was something I needed to pay attention to or remember, or if it
was just there to play interference…the content wasn’t distracting, it was just the
presence of.

165

Table J3 (cont’d)
Subject Report
314

Yeah, probably. Just like it was more calm afterwards…I think it helped keep my
focus.

315

I think it made me forget the sentences. I would get distracted and forget what I had
to repeat.

316

No.

317

No, it was mostly just like, “this is a flower…ok, I really don’t care.” That was
basically how I was thinking of it.

318

It might have confused me a little before I started.

319

Not that I know of. I don’t think it had a conscious effect on me.

320

A couple of times I couldn’t repeat what I was trying to say because it distracted me
and I forgot what I just heard. So, I guess yeah, a little bit.

321

No. I can barely remember [the film clips and images]. Nothing too effective.

322

I don’t think so. They definitely put me at ease at the beginning with the longer
clips of all the nature and things like that. But, I don’t think they affected me during
the study at all.

323

I don’t think so. If it came right afterwards, it would kind of distract me. But other
than that, I don’t think they had a huge impact.

324

No.

325

Not consciously, at least. A lot of pictures that I had were calming outdoor scenes,
so maybe I was more relaxed.

326

No, I didn’t find those to influence me.

327

Sometimes they did just because I would remember something and I would put the
clip with the image and I would remember it better.

328

Not really.

329

No.

330

Yep. If the clip popped up at a certain point when I was trying to remember
something, it would kind of throw me off. [The content] made me tired…it made
me very tired. I was trying not to fall asleep.

166

APPENDIX K

Exploratory Factor Analysis Structure Matrices
Table K1
Summary of Exploratory Factor Analysis Results for the BFAS Questionnaire (N = 120)
Item
Q5. I believe in the importance of art.
Q19. I see beauty in things that others might not notice.
Q17. I need a creative outlet.
Q2. I seldom notice the emotional aspects of paintings and
pictures. (R)
Q13. I do not like poetry. (R)
Q7. I love to reflect on things.
Q14. I avoid philosophical discussions. (R)
Q4. I enjoy the beauty of nature.
Q10. I get deeply immersed in music.
Q3. I have difficulty understanding abstract ideas. (R)
Q8. I can handle a lot of information.
Q9. I like to solve complex problems.
Q6. I formulate ideas clearly.
Q1. I am quick to understand things.
Q18. I have a rich vocabulary.
Q12. I learn things slowly. (R)
Q15. I think quickly.
Q11. I seldom daydream. (R)
Q16. I seldom get lost in thought. (R)
Eigenvalues
% of variance
α

Rotated Factor Loadings
Openness
Intellect
Escapism
.77
.64
.63
.58
.57
.56
.50
.48
.46
.77
.65
.64
.61
.53
.51
.50

5.02
26.39
.81

2.54
13.37
.79

.92
.64
1.54
8.11
.75

Note. All negatively-worded items (R) were reversed to the affirmative for this analysis. One
item, Q20 (I do not avoid difficult reading material), was removed to increase the reliability of
the subscale intellect.

167

Table K2
Summary of Exploratory Factor Analysis Results for the REI Questionnaire (N = 120)
Item
Q8. I believe in trusting my hunches.
Q5. Using my gut feelings usually works well for me in figuring out
problems in my life.
Q10. I hardly ever go wrong when I listen to my deepest gut feelings
to find an answer.
Q2. I suspect my hunches are inaccurate as often as they are accurate.
(R)
Q1. I like to rely on my intuitive impressions.
Q4. I don't have a very good sense of intuition. (R)
Q12. I trust my initial feelings about people.
Q13. If I were to rely on my gut feelings, I would often make
mistakes. (R)
Q3. I can usually feel when a person is right or wrong, even if I can't
explain how I know.
Q6. My snap judgments are probably not as good as most people's. (R)
Q17. I don’t think it is a good idea to rely on one’s intuition for
important decisions. (R)
Q20. I think it is foolish to make important decisions based on
feelings. (R)
Q11. I would not want to depend on anyone who described himself or
herself as intuitive. (R)
Q15. I generally don’t depend on my feelings to help me make
decisions. (R)
Q9. I don't like situations in which I have to rely on intuition. (R)
Q14. Intuition can be a very useful way to solve problems.
Eigenvalues
% of variance
α

Rotated Factor Loadings
Intuitive
General
Ability
Intuition
.73
.72
.68
.67
.67
.66
.65
.61
.58
.42
.75
.74
.65
.52

5.92
37.00
.87

.50
.47
1.89
11.83
.74

Note. All negatively-worded items (R) were reversed to the affirmative for this analysis. The
following items were removed to eliminate issues of multicollinearity: Q7 (I tend to use my heart
as a guide for my actions); Q16 (I often go by my instincts when deciding a course of action);
Q18 (When it comes to trusting people, I can usually rely on my gut feelings); and Q19 (I think
there are times when one should rely on one’s intuition).

168

Table K3
Summary of Exploratory Factor Analysis Results for the TEIQue-SF Questionnaire (N = 120)
Item

Q13. Those close to me complain I don’t treat them right. (R)
Q12. Generally, I have a gloomy perspective on most things. (R)
Q18. I normally find it difficult to keep myself motivated. (R)
Q4. I usually find it difficult to regulate my emotions. (R)
Q20. On the whole, I’m pleased with my life.
Q5. I generally don’t find life enjoyable. (R)
Q24. I believe I’m full of personal strengths.
Q9. I feel that I have a number of good qualities.
Q22. I get involved in things I later wish I could get out of. (R)
Q8. Many times, I can’t figure out what emotion I'm feeling. (R)
Q19. I’m usually able to find ways to control my emotions when
I want to.
Q7. I tend to change my mind frequently. (R)
Q16. I find it difficult to show affection to those close to me. (R)
Q23. I often pause and think about my feelings.
Q1. Expressing my emotions with words is not a problem for me.
Q28. I find it difficult to bond well with those close to me. (R)
Q2. I find it difficult to see things from another’s viewpoint. (R)
Q29. Generally, I’m able to adapt to new environments.
Q15. On the whole, I’m able to deal with stress.
Q17. I’m normally able to “get into someone’s shoes” and
experience their emotions.
Q14. I find it difficult to adjust life according to the
circumstances. (R)
Q6. I can deal effectively with people.
Q27. I generally believe that things will work out fine in my life.
Q3. On the whole, I’m a highly motivated person.
Eigenvalues
% of variance
α

Rotated Factor Loadings
Emotional
Emotion
Stress
Self-Reg.
Towards
Mgmt.
Others
.67
.66
.64
.63
.59
.58
.56
.56
.53
.52
.50

.67
.57
.56
.55
.42
.74
.66
.56
.55

6.80
28.33
.86

2.22
9.26
.69

.52
.51
.50
2.16
9.01
.78

Note. All negatively-worded items (R) were reversed to the affirmative for this analysis. The
following items were removed to eliminate issues of multicollinearity: Q10 (I find it difficult to
stand up for my rights); Q11 (I’m able to influence the way other people feel); Q21 (I would
describe myself as a good negotiator); Q25 (I tend to “back down” even if I know I’m right);
Q26 (I don’t seem to have any power at all over other people’s feelings); and Q30 (Others
admire me for being relaxed).

169

Table K4
Summary of Exploratory Factor Analysis Results for the FLCAS Questionnaire (N = 120)
Item
Q1. I never feel sure of myself when speaking in foreign language class.
Q24. I feel self-conscious speaking a foreign language in front of others.
Q18. I feel confident when I speak in foreign language class. (R)
Q4. It frightens me when I don’t understand what the teacher is saying in
the foreign language.
Q25. Language class moves so quickly I worry about getting left behind.
Q28. When I’m going to language class, I feel very sure and relaxed. (R)
Q32. I would probably feel comfortable around native speakers of the
foreign language. (R)
Q23. I feel that other students speak the foreign language better than I do.
Q2. I don’t worry about making mistakes in class. (R)
Q14. I wouldn’t be nervous speaking a foreign language with native
speakers. (R)
Q10. I worry about the consequences of failing my foreign language class.
Q30. I feel overwhelmed by the number of rules you have to learn to speak
a foreign language.
Q17. I often feel like not going to my language class.
Q16. Even if I am well prepared for language class, I feel anxious about it.
Q26. I feel tense and nervous in my language class than other classes.
Q31. I’m afraid other students will laugh when I speak a foreign language.
Q19. I’m afraid my language teacher is ready to correct my every mistake.
Q12. In language class, I can get so nervous I forget things I know.
Q15. I get upset when I don’t understand what the teacher is correcting.
Q21. The more I study for a language test, the more confused I get.
Q5. It wouldn’t bother me at all to take more foreign language classes. (R)
Eigenvalues
% of variance
α

Rotated Factor Loadings
FLA
General
Anxiety
.80
.73
.71
.68
.67
.63
.59
.59
.56
.55
.53
.53

8.47
40.31
.89

.71
.68
.68
.68
.65
.61
.53
.45
.41
1.62
7.73
.84

Note. All negatively-worded items (R) were reversed to the affirmative for this analysis. The
following items were removed to eliminate issues of multicollinearity: Q3 (I tremble when I’m
going to be called on in language class); Q6 (During language class, I think about things that
have nothing to do with the course); Q7 (I think other students are better at languages than I am);
Q8 (I’m usually at ease during tests in my language class); Q9 (I panic when I have to speak
without preparation in language class); Q11 (I don’t understand why people get upset over
foreign language classes); Q13 (It embarrasses me to volunteer answers in language class); Q20
(My heart pounds when I’m to be called on in language class); Q22 (I don’t feel pressure to
prepare well for language class); Q27 (I get nervous speaking in my language class); Q29 (I get
nervous when I don’t understand every word the language teacher says); and Q33 (I get nervous
when the language teacher asks questions I haven’t prepared in advance).

170

Table K5
Summary of Exploratory Factor Analysis Results for the UPPS Questionnaire (N = 120)
Item
Q37. I usually think carefully before doing anything.
Q28. I usually make up my mind through careful reasoning.
Q24. I tend to follow a rational, “sensible” approach.
Q42. Before making up my mind, I consider all the
advantages and disadvantages.
Q6. My thinking is usually careful and purposeful.
Q13. I like to stop and think things over before I do them.
Q29. I am a cautious person.
Q35. Before I get into a new situation I like to find out what
to expect from it.
Q10. I am not one of those people who blurt out things
without thinking.
Q20. I don't like to start a project until I know exactly how
to proceed.
Q34. I sometimes like doing things that are a bit
frightening.
Q18. I quite enjoy taking risks.
Q26. I welcome new and exciting experiences and
sensations, even if they’re a little frightening and
unconventional.
Q39. I would enjoy the sensation of skiing very fast down a
high mountain slope.
Q21. I would enjoy parachute jumping.
Q3. I generally seek new and exciting experiences and
sensations.
Q31. I would like to learn to fly an airplane.
Q8. I’ll try anything once.
Q45. I would enjoy fast driving.
Q15. I would enjoy water skiing.
Q38. In the heat of an argument, I will often say things that
I later regret.
Q33. I often make matters worse because I act without
thinking when I am upset.
Q44. Sometimes I do things on impulse that I later regret.
Q22. When I am upset I often act without thinking.
Q30. It is hard for me to resist acting on my feelings.
Q27. When I feel rejected, I often say things I later regret.
Q2. I have trouble controlling my impulses.

171

Rotated Factor Loadings
Premed. Sensation Urgency (Lack)
Seeking
Persev.
.89
.81
.73
.73
.73
.62
.62
.58
.47
.43
.87
.84
.76

.70
.68
.68
.55
.52
.50
.47
.78
.76
.74
.70
.66
.62
.60

Table K5 (cont’d)
Item
Q14. When I feel bad, I will often do things I later regret in
order to make myself feel better now.
Q19. Sometimes when I feel bad, I can't seem to stop what I
am doing even though it is making me feel worse.
Q5. I have trouble resisting my cravings (for food,
cigarettes, etc.).
Q12. I often get involved in things I later wish I could get
out of.
Q23. I finish what I start.
Q36. Once I start a project, I almost always finish it.
Q32. I’m a productive person who always gets the job
done.
Q7. I tend to give up easily. (R)
Q4. I generally like to see things through to the end.
Q17. I concentrate easily.
Q9. Unfinished tasks really bother me.
Eigenvalues
% of variance
α

Rotated Factor Loadings
Premed. Sensation Urgency (Lack)
Seeking
Persev.
.53
.47
.45
.45
-.89
-.82
-.66
-.61
-.56
-.43
9.35
24.60
.88

5.25
13.80
.87

3.22
8.47
.87

2.03
5.33
.83

Note. All negatively-worded items (R) were reversed to the affirmative for this analysis. The
following items were removed to eliminate issues of multicollinearity: Q1 (I have a reserved and
cautious attitude toward life); Q11 (I like sports and games in which you have to choose your
next move very quickly); Q16 (Once I get going on something I hate to stop); Q25 (I’m pretty
good about pacing myself so as to get things done on time); Q40 (There are so many little jobs
that need to be done that I sometimes just ignore them all); Q41 (I am always able to keep my
feelings under control); and Q43 (I would like to go scuba diving).

172

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