EXAMINING READING COMPREHENSION ACCOMMODATIONS FOR STUDENTS
WITH READING DIFFICULTIES: THE SIMPLE VIEW OF READING

Jessica Violet McKindles Hubbell

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

School Psychologyâ€”Doctor of Philosophy

2024

ABSTRACT

Educators often provide students with disabilities reading accommodations to help them

access content during instruction, but research has shown that not all students benefit from those

accommodations. Given the importance of content area instruction, there is a need for further

research on how to efficiently identify reading accommodations that are the most beneficial for

individual students given their unique needs. The current study applied an alternative treatments

single-case design approach to investigate the corresponding impact of two different reading

accommodation conditions (i.e., decoding accommodation, decoding + language comprehension

accommodations) on the comprehension of social studies text among six fourth-grade students

who were classified according to the simple view of reading as specifically in need of decoding

support. Results indicated that very few participants displayed clear benefits of either reading

accommodation condition. These findings suggest that it remains difficult to predict which

students benefit from accommodations and the conditions under which they benefit from them.

Related suggestions for future research that might meaningfully extend the present findings are

provided.

This Dissertation is dedicated to my family and
friends who have always believed in me.

TABLE OF CONTENTS

CHAPTER I: INTRODUCTION.......................................................................................... 1

CHAPTER II: LITERATURE REVIEW............................................................................. 5

CHAPTER III: METHODS.................................................................................................. 22

CHAPTER IV: RESULTS.................................................................................................... 47

CHAPTER V: DISCUSSION............................................................................................... 100

REFERENCES...................................................................................................................... 119

APPENDIX A: Procedure for Guardians to use before Every Session................................. 131

APPENDIX B: Example Passage.......................................................................................... 132

APPENDIX C: Procedure for How Vocabulary Words Were Chosen................................. 133

APPENDIX D: Procedure for How to Create the Content Words List................................. 134

APPENDIX E: Flyer for Study.............................................................................................. 135

APPENDIX F: Administering Computerized Assessments.................................................. 136

APPENDIX G: Reading Background Questions................................................................... 140

APPENDIX H: Scripted Protocols for Introduction and No Accommodation......................141

APPENDIX I: Scripted Protocols for No Accommodation................................................... 144

APPENDIX J: Scripted Protocols for Pre-Training...............................................................146

APPENDIX K: Scripted Protocols for Decoding.................................................................. 151

APPENDIX L: Scripted Protocols for Decoding + Language Comprehensionâ€¦â€¦............ 153

APPENDIX M: Example Schedule....................................................................................... 155

CHAPTER I: INTRODUCTION

Purpose

The purpose of the current study was to examine the effects of reading comprehension

accommodations for students with poor decoding skills on general comprehension of

informational texts. Many students have not met expected proficiency levels on content area

achievement tests (National Assessment of Educational Progress [NAEP], 2018, 2019, 2022a);

one reason may be that many students struggle with reading demands required during content

area instruction and testing. In general, accommodation supports have been used to assist

students in the classroom (Salvia et al., 2017); specifically, reading comprehension

accommodations have been found to be beneficial for many students (Bharadwaj & Lund, 2018;

Buzick & Stone, 2014; Reed et al., 2014; Wood et al., 2018). However, studies have also found

the effectiveness of a given accommodation varies considerably across individual students (Bolt

& Thurlow, 2007; Fuchs et al., 2005; Helwig et al., 2002). In the current study, we empirically

examined the potential for the simple view of reading to aid in the identification of reading

comprehension accommodations that improve a studentâ€™s comprehension of informational text.

This study correspondingly has the potential to improve the efficiency with which school teams

identify accommodations that are beneficial for individual students.

Background

At the middle school level, accessing printed text is crucial because teachers use

textbooks to guide their instruction and delivery of content (Bruhn & Hasselbring, 2013; Kulm et

al., 1999; Mastropieri & Scruggs, 2005). In social studies classes, a considerable amount of

independent reading and answering questions from a textbook is required (Scruggs &

Mastropieri, 2013). Therefore, being able to comprehend content area text is essential for

students.

According to the NAEP, on the content area assessments (i.e., social studies), the

majority of fourth and eighth-grade students were not meeting proficiency levels. For students in

fourth grade, twenty-four to thirty-eight percent of students scored at the proficient level or

above in social studies (NAEP, 2010), meaning that they were able to interpret information from

a variety of sources, including texts (NAEP, 2010). For eighth-grade students, fourteen to

twenty-two percent of students scored at the proficient level or above (NAEP, 2022a), meaning

that they were able to â€œcommunicate ideas about historical themes while citing evidence from

primary and secondary sourcesâ€ (NAEP, 2022a).

One of the reasons for low content area achievement scores may be that the instruction of

content area subjects is often conveyed through textbooks (Bruhn & Hasselbring, 2013). The

foundation of social studies instruction in middle school courses has long been textbooks

(Gewertz, 2012; Groves, 2016). Moreover, the reading levels of textbooks are usually more

advanced than the grade for which the books are designed (Jitendra et al., 2001). Students find

expository reading in textbooks difficult because the textbooks are typically written at levels

above what students, in general, can understand (Bulgren et al., 2013; Edmonds et al., 2009;

Saenz & Fuchs, 2002; Scruggs et al., 2010). When the text requires advanced reading skills,

students with low vocabulary and underdeveloped decoding and fluency skills are disadvantaged

in that subject area (Neuman et al., 2014; Tyree et al., 1994).

According to the NAEP, the majority of fourth and eighth-grade students were not

meeting proficient levels on the reading assessments. The NAEP reading assessment measures

reading comprehension by asking students to read grade-level passages and then answer

questions about the passage, which were then scored. For fourth-grade students, thirty-three

percent of students scored proficient or above on the reading assessment (NAEP, 2022b), which

means that they were able to apply their understanding of the text, draw conclusions, and make

an evaluation (NAEP, 2022b). For students in eighth grade, thirty-one percent of students scored

proficient or above (NAEP, 2022b), meaning that they could provide inferences about a text,

analyze text features, and substantiate judgments about the content (NAEP, 2022b). This

suggests many students are struggling to read proficiently.

For students with reading difficulties, a possible solution to the barrier of using complex

text for instruction is accommodations. Accommodations are used to help bridge the gap

between the studentâ€™s skills and the information they are trying to access, which often entails

changes to the mode or format of presentation of material to facilitate learning and measurement

(Nolet & McLaughlin, 2000; Salvia et al., 2017). An accommodation is intended to allow

students access to the general curriculum and to give them an opportunity to display their

knowledge without altering the curriculum or content standards being assessed (Elliott et al.,

2002).

Importance

One potential reason for varying findings of the effectiveness of reading comprehension

accommodations mentioned earlier might be related to the varying reading skills of students

using the accommodations. For example, many studies that examine students with learning

disabilities in general (and not specifically those with reading difficulties) show minimal positive

impact of reading accommodations (Elbaum et al., 2004; Schmitt et al., 2012). In studies that

focus on students with limited reading skills (i.e., poor decoders, and those with reading-based

learning disability), unique benefits of using reading accommodations are more apparent

(Fletcher et al., 2006; Helwig et al., 2002; Laitusis, 2010). It seems to be the case that students

with different types of reading skills may benefit from different accommodations.

Rationale

Taking into account studentsâ€™ specific reading difficulties in a systematic manner may

help improve accommodation recommendations. According to Fuchs and colleagues (2000a),

objective data sources can â€œsupplement teacher judgments to enhance accommodation decisionsâ€

(p. 83). Compared to teachers independently and subjectively choosing accommodations, studies

found that an objective and systematic manner of choosing accommodations resulted in a more

effective accommodation choice (Fuchs et al., 2000a; Fuchs et al., 2000b; McKevitt & Elliott,

2003).

The simple view of reading (SVR) may offer an effective framework to improve

accommodation decision-making that may be relatively easy to apply. According to this

framework, reading comprehension has two major components: decoding and language

comprehension (Gough & Tunmer, 1986). The ability to decode requires a completely different

skill set than that which is needed for language comprehension, which accordingly may require

different accommodations. However, empirical evidence is needed to determine if, indeed,

students benefit from accommodations that are particularly identified through the SVR.

CHAPTER II: LITERATURE REVIEW

Theoretical Framework

The simple view of reading (SVR) may offer guidance in matching specific studentsâ€™

reading difficulties to effective accommodations. According to this theory, there are two major

components of reading comprehension: decoding and language comprehension (Gough &

Tunmer, 1986). Reading comprehension (R) is considered the product of the variables of

decoding (D) and language comprehension (C) or R = D x C. Each contributing variable ranges

from 0 (no skills) to 1 (perfection). However, in practice, a reader would likely never fall in the

no skills (0) and/or perfect skills (1) categories. Therefore, it is helpful to think about the skills

on a continuum. For example, if a fourth-grade student attempts to read a passage from a college

medical textbook, they may be able to recognize many of the words but would likely grasp little

of the overall meaning. They may know it is about a certain system in the body but not

comprehend the specific information. In this example, the reader possesses the ability to decode

text but has insufficient language comprehension, leading to poor overall reading

comprehension. Another example would be a young child who is still learning to decode and can

only understand a childrenâ€™s book when it is read aloud. In this example, the reader has poor

decoding skills but sufficient language comprehension skills; therefore, without the support of

someone reading to them, they would not be able to comprehend the text. In both examples, the

readers have some skill in both decoding and language comprehension, but due to the degree of

skill and whether it is sufficient for the text presented, they struggle to comprehend text. Any

given studentâ€™s decoding and language comprehension skills can be considered to be at some

point on different continua that may or may not be sufficient for comprehending a given text

passage. The more recent SVR model has replaced the term decoding with word recognition.

Word recognition is the ability to read words in isolation (Adlof et al., 2006). More

specifically, â€œword recognition is the act of seeing a word and recognizing its pronunciation

immediately and without any conscious effortâ€ (Murray, 2016b, p. 30). The aspects required for

word recognition are phonological awareness, word decoding, and sight recognition. First,

phonological awareness is the ability to manipulate and break down sounds in language, such as

dividing a word into phonemes (individual sounds), syllables (large parts), and rhymes (whole

words; Murray, 2016b; Torgesen & Mathes, 2000). Next, word decoding is the â€œaccurate and fast

retrieval of the phonological code for written word formsâ€ (Verhoeven & Leeuwe, 2008, p. 407).

In other words, decoding is the ability to blend the letter sounds to read words (Murray, 2016b).

Finally, sight word recognition refers to accurately reading sight words, which are high-

frequency words that have â€œirregular spellings and cannot be perfectly decodedâ€ (Murray, 2016b,

p.36).

Language comprehension is the ability to interpret lexical information (i.e., semantic

information at the word level), sentences, and verbal communication (Gough & Tunmer, 1986;

Hoover & Gough, 1990). The aspects required for language comprehension are background

knowledge, language structures, comprehension monitoring, and vocabulary. First, background

knowledge is a specific subset of knowledge (e.g., facts about events, sayings, people, etc.) that

the reader needs to comprehend what is presented (Murray, 2016a). Second, language structure is

the relationship between the individual words and sentences in a written text (Murray, 2016a).

Next, it is important for students to continuously monitor their comprehension level of the

passage (Murray, 2016a). In other words, students should question themselves to determine

whether they understand the passage. Comprehension monitoring can also be referred to as

metacognition, which is the ability to think about, understand, and manage oneâ€™s learning

(Schraw & Dennison, 1994). Lastly, vocabulary is â€œthe knowledge of the meaning of words in a

textâ€ (Murray, 2016a, p.49). Vocabulary is one of the strongest predictors of language

comprehension, and ultimately, reading comprehension (Duncan et al., 2007) because if a person

does not know the meaning of the words being read, it is not possible to comprehend the

meaning of the overall passage.

By using the two main aspects of the SVR, students can be classified into four categories

(poor decoders, poor language comprehenders, mixed deficit, or no impairment). Poor decoders

have difficulty with phonological awareness (syllables and phonemes), decoding (alphabetic

principle and spelling-sound correspondences), and/or sight recognition (of familiar words) but

do not have language comprehension difficulties. Poor language comprehenders have difficulty

with background knowledge (facts and concepts), vocabulary, (breadth, precision, and links),

language structures (syntax and semantics), verbal reasoning (inference and metaphor), and/or

literacy knowledge (print concepts and genres), but do not have word recognition difficulties.

People with mixed deficits have poor decoding and poor language comprehension skills, while

people with no impairment have adequate to good decoding and language comprehension skills

(Catts & Kamhi, 2005; Foorman et al., 2017). Several studies have categorized students into the

SVR groups, and the studies reported a wide range of students in each category. The range for

poor decoders was from 14% to 33%, poor language comprehenders were from 31% to 52%, and

no impairment was from 33% to 54% (Cain et al., 2000; Catts et al., 2006; Giusto & Ehri, 2019;

Nation et al., 2004; Nation & Snowling, 1998). Students who scored low in both decoding and

language comprehension seemed to be eliminated from the studies before investigation.

Table 1

Simple View of Reading Categories

Category
Poor Decoders
Poor Language Comprehenders
Mixed Deficit
No Impairment

Decoding Skills
Poor
Adequate to Good
Poor
Adequate to Good

Language Comprehension Skills
Adequate to Good
Poor
Poor
Adequate to Good

Poor Decoders

There is a wealth of evidence showing the connection between decoding and reading

comprehension (Foorman et al., 2018; Nation & Snowling, 1998; Snowling, 2005; Stothard &

Hulme, 1995; Wang et al., 2019). Catts and colleagues (2006) found poor decoders scored low

on measures of phonological processing and scored well on measures of language

comprehension. Wang and colleagues (2019) sampled over 11,000 students between fifth grade

and tenth grade. Students were split between poor and average decoders and asked to complete a

reading comprehension assessment. Results showed poor decoding scores were associated with

low reading comprehension scores, which may demonstrate that decoding is an important aspect

of reading comprehension. Wood and colleagues (2018) also found that students with poor

decoding showed limited growth in reading comprehension compared to typical readers.

Poor Language Comprehenders

There is an abundance of evidence showing the connection between language

comprehension and reading comprehension (Cadime et al., 2017; Nation et al., 2004; Nation &

Snowling, 1998). According to Nation and Snowling (1998), there is a high correlation between

reading and language comprehension and a weaker correlation between language comprehension

and nonsense word reading. These results suggest that language comprehension and decoding are

two distinct aspects that make up reading comprehension.

Mixed Deficit

Students who are classified as having mixed deficits are considered to have difficulties

with both decoding and language comprehension (Catts et al., 2006). While poor decoders

should receive support focused on decoding and word-reading skills (Lovett et al., 2000) and

poor comprehenders support should focus on language knowledge and comprehension strategies

(Swanson & Deshler, 2003), students who have difficulties in both areas will likely need support

that focuses on decoding and language comprehension (Catts et al., 2006).

No Impairment

If students have adequate decoding and adequate language comprehension skills, they are

considered to have no impairment.

Accommodations

An instructional accommodation is an adaptation to the design or delivery of instruction

and associated materials in a way that does not change the amount of content or extent of

knowledge needed to meet grade-level standards (Ketterlin-Geller & Jamgochian, 2011). The

intent of instructional accommodations is for students to learn the same material and perform at

the same level as students who do not need the accommodations. Instructional accommodations

should support engagement with academic content and â€œnot alter the intended cognitive

complexity for the grade-level content standardâ€ (Ketterlin-Geller & Jamgochian, 2011, p. 134).

Instructional accommodations include changes in (a) scheduling of associated activities

(e.g., frequent breaks or on-task reminders); (b) instructional settings (e.g., preferred seating or

small group); (c) how students respond (e.g., orally or in written format); (d) the way content is

presented (e.g., text read aloud or in braille), and (e) equipment or materials students are allowed

to use (e.g., text-to-speech technology; Christensen et al., 2011; Lai & Berkeley, 2012). Many

students with learning disabilities and reading difficulties have trouble comprehending printed

text. Accommodations are provided to help some students access information through text.

Poor Decoders and Accommodations

According to the SVR, students identified as being poor decoders (e.g., having poor

decoding skills and average or above-average language comprehension skills) may experience

unique decoding-related barriers to the comprehension of written material; however, if these

barriers are removed, the individuals might better comprehend the written material. One way to

possibly remove the associated barrier may be to provide accommodations that decode text for

such students; a commonly used accommodation for students with disabilities is the read-aloud

accommodation (Bielinski et al., 2001; Witmer et al., 2018).

Read-Aloud Accommodation

The read-aloud accommodation utilizes oral presentation of materials that otherwise

would only have been available in written text. This accommodation can come in many different

forms. For example, meta-analyses completed on the effects of the read-aloud accommodation

included a variety of delivery methods, such as recorded human voice, video/audio recording,

reading pen, and text-to-speech (Buzick & Stone, 2014; Li, 2014; Wood et al., 2018). A survey

of middle school teachers found that 72 percent (344 of the 476 respondents) reported reading to

students aloud during instructional time (Ariail & Albright, 2005). However, only 16 percent of

the teachers reported reading aloud information/nonfiction books (Ariail & Albright, 2005). Due

to the limited number of teachers reading textbooks aloud, it may be beneficial to investigate

how schools could use one of the other forms of the read-aloud accommodation to help students

access instructional content. There has been an abundance of research on the effects of the read-

aloud accommodation for students with learning disabilities and reading difficulties, in which

most of the studies suggest positive findings (e.g., Bonifacci et al., 2022; Dolan et al., 2005;

Elkind et al., 1993; Sulaimon & Schaefer, 2023).

Many studies have examined the effect of the read-aloud accommodation for students

with disabilities while taking academic tests. Most indicate positive effects, although some do

not. For example, Bolt and Thurlow (2007) found positive results for students with disabilities;

specifically, the read-aloud accommodation had the greatest effect on difficult to read questions

on math assessments. Fletcher et al. (2006), Kosciolek and Ysseldyke (2000), Laitusis (2010),

and Weston (2002) all examined the read-aloud accommodation for students with reading

disabilities and identified gains as a result of receiving the read-aloud accommodations on

academic tests.

Helwig and colleagues (2002) found that elementary students with a learning disability

received higher scores on academic tests when using the read-aloud accommodation, but middle

school students with learning disabilities performed better when given the standard test. The

difference between the elementary and middle school studentsâ€™ results may be due to the math

teacher being the one to choose which students would benefit from the read-aloud

accommodation (Helwig et al., 2002). In elementary school, the math teacher is most likely also

the reading teacher, but this is not likely the case in middle school. Therefore, the elementary

school teachers may have had a better understanding of the studentâ€™s reading skills compared to

middle school teachers and, therefore more likely to correctly identify those with reading

difficulties who would benefit from the accommodation. The results of a study by Elbaum and

colleagues (2004) suggested the read-aloud accommodation resulted in no real difference in test

scores for students with disabilities. Specifically, out of all the students with disabilities in the

study, 17 percent had a boost in performance, 20 percent had impaired performance, and 63

percent experienced no difference when using the read-aloud accommodation in comparison to

their performance on a standard test with no accommodations (Elbaum et al., 2004).

One reason for the inconsistent results may be due to the participants having a variety of

different reading skill deficits that may not all be adequately addressed by the read-aloud

accommodation. For example, Elbaum and colleagues (2004) included students with disabilities,

regardless of reading ability, whereas Helwig and colleagues (2002) included students with

disabilities whom their math teacher had identified as potentially benefiting from the read-aloud

accommodation. This small distinction might explain why Helwig and colleagues (2002)

reported positive results for the read-aloud accommodation among elementary students, whereas

Elbaum and colleagues (2004) observed no performance difference. According to the SVR, only

those students with decoding difficulties would likely improve their reading comprehension by

having the text read aloud. Students with language comprehension difficulties would likely need

something different to facilitate reading comprehension.

Fletcher and colleagues (2006) examined how a package of accommodations affected

scores on reading assessments for students with dyslexia. Students were categorized into either

dyslexic or average reader groups as determined by the results of their Woodcock-Johnson III

Test of Achievement, Basic Reading cluster score. The Basic Reading cluster is the combination

of the letter-word identification and word attack (decoding nonsense words) subtests. Each of the

studentâ€™s vocabulary knowledge was considered average based on their Woodcock Language

Proficiency Battery- Revised Picture Vocabulary subtest scores. Students were randomly

assigned to the accommodated or standard version of the reading assessment. The package of

accommodations consisted of extending the test time across two days, and an adult read the

proper nouns and comprehension questions aloud. Results found the package of accommodations

had a strong positive effect on students with dyslexiaâ€™s reading comprehension scores but made

no difference for typical readers (Fletcher et al., 2006). Overall, this study suggested that

students with poor decoding skills may benefit from having written text read aloud. However, the

study only examined whether reading proper nouns and comprehension questions aloud, not the

whole passage, affected studentsâ€™ reading comprehension.

On the other hand, Meyer and Bouck (2014) found that text-to-speech accommodation

did not improve reading comprehension, which raises the question of whether it is effective for

everyone. In this study, the text-to-speech accommodation was provided via a computer program

that converted text on the screen to spoken words (Meyer & Bouck, 2014). Three students

participated in the multiple baseline across participants design study. Results showed that, for the

most part, using the text-to-speech accommodation did not improve reading comprehension.

However, there was one main limitation to this study: the reading comprehension measurement.

The six multiple-choice questions asked after each passage were taken from a book written by

Pauk (2010), but the technical adequacy of the comprehension measure had not been examined

prior to the study. This may have contributed to difficulties in establishing a stable baseline for

each participant, such that the difference between baseline and intervention phases could not be

detected. All the variation in student test scores may ultimately have reflected issues with

measurement rather than a lack of improvement associated with the accommodation. One

interesting finding from the study was that the student who had a positive trend during the

intervention phase was the student with the lowest score on the decoding assessment. This may

indicate that certain students could strongly benefit from the read-aloud accommodation. Future

research should aim to use reading comprehension measures with greater evidence for technical

adequacy.

Even though the majority of studies found positive results regarding the effectiveness of

the read-aloud accommodation, there were several studies that found conflicting results, which

may be due to the studies not taking studentsâ€™ individual reading skills into account. According

to the SVR, the students with poor decoding skills may benefit greatly from the read-aloud

accommodation compared to students with average decoding skills. It was anticipated that more

consistently positive effects from the read-aloud accommodation may be identified for students

with specific reading decoding difficulties.

Poor Language Comprehension and Accommodations

According to the SVR, students identified as being poor comprehenders (e.g., poor

language comprehension skills and average decoding skills) would experience barriers related to

language comprehension while reading; however, if the barriers were removed, the readers might

better comprehend the written materials. Unlike the straightforward option of reading aloud

materials to address decoding difficulties, identifying possible supports for language

comprehension is complex due to the number of components and associated integration work

required for language comprehension to occur (e.g., background knowledge, language structures,

comprehension monitoring, and vocabulary need to be adequate and applied in a sophisticated

manner to comprehend language). Within the empirical literature, vocabulary support and

comprehension monitoring represent some of the most commonly studied language-focused

supports for students with disabilities (Hawkins et al., 2010; Reed et al., 2014), and have the

potential to be provided as accommodations. Researchers have investigated using vocabulary

support and comprehension monitoring to accommodate studentsâ€™ comprehension of

instructional material. Typically, the associated research has not been framed as an investigation

of accommodations but rather as instruction or intervention more broadly defined. Associated

work was briefly reviewed in the following sections.

Vocabulary

Vocabulary support can be presented in many different forms (e.g., word definition,

vocabulary previewing) and typically involves the student receiving the definition of a particular

word. Researchers have studied the effects of vocabulary supports for all students, and the

overall results show a positive effect (Hawkins et al., 2010; Marzano et al., 2000; Reed et al.,

2014).

Several studies have examined the effect of vocabulary support for students with

disabilities; some indicated positive results, while others did not. For example, Hawkins and

colleagues (2010) found that students who received both listening and vocabulary previewing

scored higher on factual and inferential comprehension. Listening preview was presented by the

teacher reading a sentence aloud, and then the students repeating the sentence together.

Vocabulary previewing involved teachers pronouncing difficult words in a passage before the

students read the passage. Results found that levels of comprehension and vocabulary knowledge

were increased after including vocabulary reviewing (Hawkins et al., 2010). On the other hand,

Schmitt and colleagues (2012) found a reading pen with vocabulary function did not result in

improved comprehension scores. Based on the studies reviewed, students are most likely to

benefit from vocabulary support when they are required to use the support and when only the

most difficult words are defined.

Two reasons for the inconsistent results could be differences in when the definitions of

words were provided (e.g., before the passage or while reading the passage) and the difficulty

level of the defined words (e.g., difficult words or all words). For example, in Hawkins and

colleagues' (2010) study, the students only received the definitions of the words chosen by the

teacher, and these definitions were provided before they read the passage. On the other hand, in

the Schmitt and colleagues (2012) study, students had control over what words they wanted to be

defined and were given the definition while they were reading the text. As such, in the Schmitt

and colleagues (2012) study, students may not have actually used the reading pen function that

allowed for word definitions to be provided very frequently. These small distinctions may be the

reason Hawkins and colleagues (2010) found positive results for the vocabulary support, and

Schmitt and colleagues (2012) found no improvement. In general, studies have shown that

providing a definition of difficult vocabulary words can improve studentsâ€™ reading

comprehension and academic achievement, but the way definitions are presented and/or what

words are defined may predict whether the students will benefit.

Comprehension Monitoring

Comprehension monitoring is a strategy that is conceptualized as requiring meta-

cognitive skills, involving students questioning themselves to determine if the passages make

sense (Bharadwaj & Lund, 2018). By questioning and reflecting on what they are reading, it was

anticipated that they are more likely to understand the passage (Fletcher et al., 2006; Nation,

2005). There are various ways to potentially support these actions when students are reading

information, such as through repeated prompts that facilitate questioning and summarizing

activities (Guthrie et al., 2004). According to the National Reading Panel (2000), the

effectiveness of reading-comprehension monitoring for students with reading difficulties has

been well supported by research (Biancarosa & Snow, 2004; Block & Duffy, 2008; Edmond et

al., 2009; Guthrie et al., 2004; Marzano et al., 2000; Mastropieri et al., 2003).

Guthrie and colleagues (2004) found that when questioning and summarizing (i.e.,

comprehension monitoring) were included in a comprehension strategy package, students

performed better on reading comprehension assessments. Specifically, students were introduced

to concept-oriented reading instruction (CORI), which was designed to provide students with

multiple strategies to increase reading comprehension and academic achievement. The CORI

components included strategies, such as activating background knowledge, asking questions,

searching for information, summarizing, organizing paragraphs, and structuring stories. Students

who received the CORI, compared to the traditional instruction, scored significantly higher on

passage comprehension (Guthrie et al., 2004). However, the authors did not report whether

students with disabilities were included in the study. Therefore, future studies should examine

how reading comprehension strategies affect reading comprehension for students with

disabilities, specifically students who struggle with language comprehension.

Boardman and colleagues (2015) found using collaborative strategic reading (CSR) in

middle school science and social studies classes improved reading comprehension and access to

complex information text. CSR includes activating prior knowledge, fixing comprehension when

there is a misunderstanding, identifying the main ideas of short sections (i.e., get the gist),

developing questions, and reviewing main ideas.

These studies indicate that when students are taught comprehension monitoring strategies

and are supported while practicing, the students are more successful with reading

comprehension. However, very few studies examined comprehension monitoring strategies as

accommodations for instructional materials. If comprehension monitoring was presented as an

accommodation, it may similarly help students access the instructional information.

According to the SVR, students with poor language comprehension skills may

particularly benefit from both the vocabulary support and comprehension monitoring

accommodations. Vocabulary and comprehension monitoring are two aspects of language

comprehension, which may indicate that vocabulary support and comprehension monitoring will

especially benefit those with poor language comprehension skills. It was anticipated that students

with poor language comprehension skills would experience positive effects of the vocabulary

support and comprehension monitoring, whereas those with adequate language comprehension

skills may not benefit from the supports.

Identifying which Accommodations are most Effective for Individual Students

According to several studies, teachers are not particularly accurate in identifying which

students need support and which accommodations meet their needs; therefore, systematic

assessments have been developed to help teachers make decisions. For example, a study by

Fuchs and colleagues (2000b) examined how well teachersâ€™ accommodation decisions

corresponded with decisions based on the Dynamic Assessment of Test Accommodations

(DATA). The DATA involves systematic testing of various testing accommodation conditions

for each individual student to determine which accommodation combination results in the

highest score. According to the results, students who were identified and assigned an

accommodation using the DATA benefited more compared to the students who were identified

and provided accommodations using teacher recommendations. It was also found that the DATA

was more accurate than teachers in predicting which students would benefit from support (Fuchs

et al., 2000b). Similarly, McKevitt and Elliott (2003) and Fuchs and colleagues (2000a) found

that a systematic assessment was more helpful when identifying which accommodations were

most effective than the teacher-recommended accommodation.

Even though DATA may be a beneficial tool when making accommodation decisions, it

is unlikely to be used due to time and money. This assessment was designed to be administered

by teachers, and both the math and reading sections have several subtests. Since most teachers do

not have the time to administer this lengthy assessment to their students with learning

disabilities, they are more likely to assign accommodations during educational team meetings in

an informal and nonempirical manner (Fuchs et al., 2003). Also, many schools have limited

funds, and instead of buying a new assessment; it is anticipated to be more practical to use

information from previously administered assessments to help inform accommodation decision-

making.

Considering the individual studentsâ€™ decoding and language comprehension skills may

ultimately help in more efficiently identifying the most effective accommodations. According to

the SVR, identifying studentsâ€™ specific reading comprehension subskills (i.e., decoding and

language comprehension) may help when choosing appropriate supports. One way to identify

skills the student struggles with is to examine existing reading test results, which highlight their

lack or possession of specific reading skills; this could then be used to select accommodations to

address the specific deficits. For example, when students are tested for special education status,

they typically take an extensive set of reading subtests, which includes considerable information

that may be used to categorize students based on the SVR (poor decoder, poor comprehender,

mixed deficit, or no impairment). In other words, the SVR may offer a framework for

appropriately and efficiently identifying which accommodations will be most effective for

individual students; however, it should be tested empirically to determine whether this

application holds.

Current Study

A limited number of studies have examined accommodation effects for students with

disabilities. The majority of these studies have examined how students with disabilities or

reading disabilities, in general, are affected by reading comprehension accommodations (Bolt &

Thurlow, 2007; Buzick & Stone, 2014; Fletcher et al., 2006; Hawkins et al., 2010; Helwig et al.,

2002; Kosciolek & Ysseldyke, 2000; Laitusis, 2010; Li, 2014; Marzano et al., 2000; Reed et al.,

2014; Weston, 2002; Wood et al., 2018). The SVR suggests that utilizing a studentâ€™s overall

reading ability will not provide sufficient information to determine which type of support the

student needs (Gough & Tunmer, 1986); more specific information is needed regarding the

studentâ€™s skill level to best understand how to potentially support the student.

An applied extension of the SVR would be that readers may benefit from different forms

of reading comprehension accommodations (i.e., read-aloud, vocabulary, and comprehension

monitoring) depending on their reading skills (i.e., poor decoders, poor language comprehension,

and mixed deficit; Murray, 2016a). Students with poor decoding skills will likely benefit from

the read-aloud accommodation because it removes the need to decode, thus allowing the student

access to written text. Students with poor language comprehension may specifically benefit from

vocabulary and comprehension monitoring accommodations. Students with mixed deficits may

specifically benefit from the read-aloud, vocabulary, and comprehension monitoring

accommodations.

The SVR may be a good framework to help identify appropriate accommodations, but

there is a need for empirical examination of this applied extension. The current study represents a

preliminary exploration to investigate one group of readers (i.e., poor decoders) regarding

whether different accommodation conditions affect their general comprehension of information

texts. If it is found that students in the poor decoding group benefit from the decoding support

alone and do not benefit from the additional support, it may offer support that the SVR offers

guidance for more efficient assignment of accommodations to individual students.

Research Questions

1. To what extent does the use of the read-aloud accommodation affect general

comprehension of text-based material for students with word decoding difficulties?

Hypothesis: Students with poor decoding skills will benefit from the read-aloud

accommodation.

2. To what extent does the read-aloud accommodation, vocabulary support, and

comprehension monitoring affect general comprehension of text-based material for

students with word decoding difficulties?

Hypothesis: Students with poor decoding skills will experience a similar but no

greater benefit from the combination of the read-aloud accommodation,

vocabulary support, and comprehension monitoring compared to the read-aloud

accommodation independently.

CHAPTER III: METHODS

A single-case research design, specifically an adapted alternating treatment design, was

applied to examine the effects of two different accommodation conditions for participants with

poor decoding skills and adequate language comprehension skills.

Participants

To be eligible, participants needed to (a) have a guardian report that they were entering

the fourth grade in the fall or enrolled in the fourth grade, (b) have a guardian report that they

struggled with reading, (c) pass a technology check (see Pre-Experimental Procedures section for

more details), and (d) demonstrate poor decoding skills, average listening comprehension skills,

and average working memory skills based on pre-testing (see below for pre-testing eligibility).

Table 2 summarizes participant demographics. Pseudonyms were used in place of the

participantâ€™s actual names to protect their rights to privacy and confidentiality. Two participants

did not complete the study due to family vacations and busy summer schedules. Both

participants started the alternating treatment phase, but neither completed the treatment phase.

Results for these participants were not reported.

Pre-Testing Eligibility Criteria

To qualify for participation in the study, individuals were required to have achieved a

score of 1 or more standard deviations (SD) below the grade-level mean on the Woodcock

Reading Mastery Test, Third Edition (WRMT-III) word attack subtests, and also to have scored

more than 0.5 SD below the age-level mean on the WRMT-III listening comprehension subtest.

These criteria were chosen in order to identify those participants who represented â€œpoor

decodersâ€ according to the simple view of reading (SVR) conceptualization of reading

difficulties, which defines poor decoders as having below-average decoding skills and average to

above-average language comprehension skills (Gough & Tunmer, 1986). Grade-level norms

were applied when scoring the word attack subtest because students are typically taught how to

decode words in school, and therefore, their decoding skills should be relatively similar

compared to their same-grade peers. On the other hand, age-level norms were applied when

scoring the listening comprehension subtest because students are not typically taught listening

comprehension skills in school, and therefore, their listening comprehension skills should be

relatively similar compared to same-age peers regardless of their grade. These criteria are also

similar to other studies that categorized students according to the SVR (e.g., Catts et al., 2006;

Giusto & Ehri, 2019). In addition, to be eligible, a participant needed to score higher than 2 SD

below the age-level mean on the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-

V) digit span subtest. This was to ensure results were not inadvertently influenced by a

participantâ€™s particularly low working memory, which could otherwise hinder the ability to

detect the potential effects of the accommodation conditions on reading comprehension.

Working memory is considered a prerequisite ability for language comprehension, and as such, it

was important to exclude those for whom working memory was extremely low.

James. James was a 9-year-old 4th grader from Michigan whose guardian reported that he

struggled with sounding out words. James earned a standard score of 76 on the word attack

subtest of WRMT-III and a standard score of 113 on the listening comprehension subtest of

WRMT-III. He earned a scaled score of 6 on the digit span subtest of WISC-V.

Robert. Robert was a 10-year-old 4th grader from Georgia whose guardian reported that

he struggled with reading fluency. Robert earned a standard score of 76 on the word attack

subtest of WRMT-III and a standard score of 155 on the listening comprehension subtest of

WRMT-III. He earned a scaled score of 8 on the digit span subtest of WISC-V.

John. John was a 9-year-old 4th grader from New Jersey whose guardian reported that he

struggled with decoding. John earned a standard score of 76 on the word attack subtest of

WRMT-III and a standard score of 95 on the listening comprehension subtest of WRMT-III. He

earned a scaled score of 8 on the digit span subtest of WISC-V.

William. William was a 10-year-old 4th grader from Michigan whose guardian reported

that he struggled with sounding out words and reading comprehension. William earned a

standard score of 76 on the word attack subtest of WRMT-III and a standard score of 99 on the

listening comprehension subtest of WRMT-III. He earned a scaled score of 12 on the digit span

subtest of WISC-V.

Matthew. Matthew was a 10-year-old 4th grader from Michigan whose guardian reported

that he struggled with reading fluency and decoding. Matthew earned a standard score of 80 on

the word attack subtest of WRMT-III and a standard score of 100 on the listening comprehension

subtest of WRMT-III. He earned a scaled score of 6 on the digit span subtest of WISC-V.

Mary. Mary was an 8-year-old from Michigan. She started participating in the current

study in the summer when she was between the 3rd and 4th grade. Maryâ€™s guardian reported that

she struggled with sounding out words. Mary earned a standard score of 78 on the word attack

subtest of WRMT-III and a standard score of 94 on the listening comprehension subtest of

WRMT-III. She earned a scaled score of 9 on the digit span subtest of WISC-V.

Susan. Susan was a 10-year-old 4th grader from Michigan whose guardian reported that

she struggled with sounding out words. Susan earned a standard score of 61 on the word attack

subtest of WRMT-III and a standard score of 100 on the listening comprehension subtest of

WRMT-III. She earned a scaled score of 7 on the digit span subtest of WISC-V.

Table 2

Participantsâ€™ Characteristics

Sex

State

Race

Asian

Participant

Age Grade

9
10
9
10
10
8
10

James
Robert
John

Male
Male Caucasian
Male Caucasian
William Male Caucasian
Matthew Male Caucasian
Female Caucasian
Female Caucasian

Digit
Span3
4th
6
4th
8
4th
8
4th
12
4th
6
3rd
9
4th
7
Note: 1 = pre-testing measure, WRMT-III word attack task, the participantsâ€™ standard score
was reported. The average score range is between 90 and 110. The cutoff score for eligibility
was 84 or below. 2 = pre-testing measure, WRMT-III listening comprehension task, the
participantsâ€™ standard score was reported. The average score range is between 90 and 110. The
cutoff score for eligibility was 92 or higher. 3 = pre-testing measure, WISC-V digit span
subtest, the participantsâ€™ scaled score was reported. Average score range is 8 to 12. The cutoff
score for eligibility was 4 or higher.

Listening
Comp2
113
115
95
99
100
94
100

Word
Attack1
76
76
76
76
80
78
61

MI
GA
NJ
MI
MI
MI
MI

Mary
Susan

Setting

Research activities occurred via Zoom during a time identified by the participantâ€™s

guardian to be appropriate. Within each individual participantâ€™s experience, the researcher aimed

to ensure that the day and time of the research activities were consistent across all meetings. The

researcher worked with the guardian at the beginning of the first meeting to help the participant

find a quiet place with reliable internet for each meeting. The researcher also worked with the

guardian if computer-related troubleshooting was needed throughout the study. The guardian and

researcher created a procedure that the guardian used before every meeting to ensure that

everything was set up at the agreed upon meeting time (See Appendix A for a procedure outline).

The researcher administered the reading passages and reading comprehension measures

individually to each participant.

Materials

The main materials for this study included expository reading passages and reading

comprehension accommodations; all materials were accessed by the participants via Zoom when

meeting with the researcher.

Expository Reading Passages

Reading passages that provided information on various social studies topics were selected

from those made available on the website edHelper (https://www.edhelper.com/) and converted

into Google Documents. Each passage was similar in length (i.e., 290-300 words) and focused on

only one specific topic (e.g., Black Americans in the Civil War; See Appendix B for an example

passage). All passages had a Flesch-Kincaid reading grade level score between 7.00 and 7.60.

The use of text at a reading level much higher than the participantsâ€™ current grade level was used

because the majority of textbooks used in schools are written at a reading level much higher than

the intended grade (Jitendra et al., 2001). Based on the state standards for social studies

instruction in Alabama, California, Colorado, Michigan, New York, and Texas, in first grade

through fourth grade, students are taught about the rights and responsibilities of citizens in the

USA, significant individuals and events in their communities and nationally, geographical

features of the earth, and the history of their state (Alabama State Department of Education,

2010; California State Board of Education, 2000; Colorado Department of Education, 2014;

Michigan Department of Education, 2019; New York State of Education Department, 2019;

Texas Education Agency, 2020). The history of the United States of America is taught in fifth

grade, and the history of the Western Hemisphere is taught in sixth grade (Alabama State

Department of Education, 2010; California State Board of Education, 2000; Colorado

Department of Education, 2014; Michigan Department of Education, 2019; New York State of

Education Department, 2019; Texas Education Agency, 2020). Therefore, to avoid using content

in which participants may have already had considerable background knowledge and/or content

that they may have learned about in school, passages about the history of the Americas were

selected. This was intended to help eliminate any effects on reading comprehension that may

have been due to school-based instruction rather than the accommodation conditions. Thirty

passages were created, and the order of these passages was randomly assigned for each

participant. Participants read between twenty-two and twenty-six passages throughout the study.

Reading Comprehension Accommodation Technology

Participants either read the expository reading passages in a silent independent manner

(no accommodation condition) or with the support of various reading comprehension

accommodation technologies and supports, including the read-aloud accommodation, vocabulary

support, and/or comprehension monitoring, which are further described below.

Read-Aloud Accommodation. For the current study, Natural Reader, an online text-to-

speech software, was used as the read-aloud accommodation (NaturalReader, n.d.).

Vocabulary Support. For the current study, vocabulary support materials included an

additional document tab that displayed a list of vocabulary words from the passage and the

corresponding definitions. In addition, passages used in this condition were adapted versions in

which pre-selected vocabulary words were highlighted with blue font (See Appendix C for how

vocabulary words were chosen).

Comprehension Monitoring. For the current study, the comprehension monitoring

support included adaptations of the passages such that a pause sign was embedded in the given

passage; the pause sign was the signal for the participant to summarize the passage verbally.

Independent and Dependent Variables

The independent variable for this study was reading accommodation status (e.g., no

accommodation condition, decoding condition, and decoding + language comprehension

condition). Each phase of the study had at least one condition. Specifically, within the baseline

phase, all sessions were administered under the no accommodation condition, within the

treatment comparison phase, sessions were administered in an alternating fashion under no

accommodation conditions, decoding conditions, and decoding + language comprehension

conditions, and within the best accommodation phase, all sessions were administered under

either decoding conditions or decoding + language comprehension conditions. The no

accommodation condition consisted of participants reading passages independently and silently.

The decoding condition consisted of using the read-aloud accommodation. The decoding +

language comprehension condition consisted of using the read-aloud, vocabulary support, and

comprehension monitoring accommodations. All the conditions are described in more detail in

the procedures section below.

The primary dependent variable for this study was the percentage of content words

recalled. To verify these results, the number of words recalled was also measured. The measures

were derived from participant responses to the recall reading comprehension prompt (â€œNow that

you have read about _______ (title of the passage), please tell me all about what you just read.

Try to tell me everything you can. Begin.â€) that was presented after participants read the given

reading passage under the respective condition.

Percentage of Content Words Recalled Measure

The percentage of content words recalled measure was the number of distinct content

words recalled (i.e., proper nouns, common nouns, verbs, adjectives, and adverbs) that were

either an exact match or an exact match with a different tense to a word in the passage divided by

the total number of distinct content words in the passage (i.e., proper nouns, common nouns,

verbs, adjectives, and adverbs). The percentage of content words recalled measure was adapted

from Fuchs and colleagues (1988). See Appendix D for specific steps to create the content words

lists necessary to calculate this score (i.e., content words recalled and content words in the

passage). Past studies have measured the technical adequacy of the percentage of content words

recalled measure and found the test-retest reliability ranged from .27-.69, and interrater

reliability ranged from 92%-99% (Good & Kaminski, 2010). As for the validity, the correlation

of the percentage of content words recalled with performance on two comprehension subtests on

the Stanford Achievement Test, 7th edition (Gardner et al., 1983) was .67 (Fuchs et al., 1988).

As noted earlier, the passages used for the current study were selected specifically for the study,

and so technical adequacy information for this measure as applied in the current study using the

selected passages was unknown, apart from the pilot information and inter-rater reliability

information presented in sections below.

Number of Words Recalled Measure

The number of words recalled measure was a direct count of the number of words the

participant said while recalling the passage. Any word spoken was counted, but non-word sounds

(e.g., â€˜um,â€™ â€˜uhâ€™) were not counted. Contractions were counted as two words. If the participant

mispronounced a word but the word was close enough to recognize, the word was counted. Past

studies have measured the technical adequacy of the number of words recalled measure and

found the test-retest reliability to be .72 (Friedman & Miyake, 2005). As for validity, correlations

of total words recalled with performance on comprehension subtests of two standardized reading

measures (i.e., GRADE and TerraNova) ranged from .39 to .51 (Riedel, 2007). It is important to

note that although the same score calculations were used in the current study, the passages for

the current study were selected specifically for the study, so technical adequacy for the number

of words recalled measure using these passages was unknown. However, strict passage selection

criteria were used to help promote technical adequacy. More specifically, all passages were

selected due to meeting the Flesch-Kincaid reading grade level score between 7.00 and 7.60.

Also, the passages focused on social studies content associated with what students typically learn

in fifth and sixth grade to prevent potential confounding with background knowledge of the

participating students (who had not yet entered 5th grade). Additional information on piloting and

inter-scorer reliability for the selected passages was provided in the sections below.

Pilot

To help offer evidence that the selected reading comprehension measures, when applied

to new passages, could be anticipated to show stability over time for individual participants, the

measures were piloted using recall information from four participants involved in a pilot study

(who were not participants in the main study). The pilot participants were asked to read five

passages in a silent independent manner and recall what they read. All passages were read in one

sitting. The pilot data showed some evidence of stability over time for individual participants

(See Figure 1).

Figure 1

Pilot Data: Percentage of Content Words Recalled

Experimental Design

The primary researcher used an adapted alternating treatment design that consisted of

three phases: baseline, treatment comparison, and best accommodation (Gast & Ledford, 2014).

In the treatment comparison phase for this study, participants read passages across two treatment

conditions (i.e., decoding condition and decoding + language comprehension condition) and one

comparison condition (i.e., no accommodation condition). Prior to any data collection, a random

number sequence tool through Microsoft Excel was used to order the three conditions across

twelve sessions separately for each participant for the treatment comparison phase. Each session

involved the participant reading and recalling one passage under the designated condition. After

a sequence was created, it was determined whether it met the requirements for the study, and if it

did not, another sequence was created until one met the requirements for each participant. If the

sequence met the requirements, then this sequence was applied to a participant in the treatment

comparison phase. The requirements were that the two reading accommodation conditions were

administered for a total of five sessions each, the no accommodation condition was administered

for two sessions, and no more than two consecutive sessions of the same condition occurred

within the sequence. See the hypothetical table in Table 3. Once the condition sequence for an

individual student was determined, the corresponding accommodation technologies described

earlier (i.e., embedded pause sign, vocabulary words selected and highlighted with blue font,

etc.) were applied to the passages that had been randomly assigned for that student in the

corresponding sessions.

Table 3

Hypothetical Condition Sequence During the Alternating Treatment Phase

Sessions

A
B
C
D

D NA LC LC NA D D LC D
LC LC D
D NA D LC LC D LC
D LC NA LC D
LC NA D
D NA LC LC LC D
D D LC NA D LC NA D D LC LC LC
Note: D = Decoding condition; LC = Decoding + Language Comprehension condition; NA =
No Accommodation condition; Yes = the sequence met the criteria; No = the sequence did not
meet the criteria

LC D

Met Criteria
Yes
Yes
No
No

A baseline phase was conducted until the percentage of content words recalled scores

showed stability and provided a solid baseline to use as a comparison for the treatment

comparison phase (Wolery et al., 2018). During the baseline phase, the measurement of reading

comprehension served as a control to establish the level of reading comprehension before the

accommodation conditions were introduced (Gast & Ledford, 2018). At a minimum, there were

five no accommodation condition sessions administered during the baseline phase. Prior to the

commencement of the alternating treatment phase for each participant, the last three data points

for the percentage of content words recalled measure showed either a stable or decreasing trend.

After baseline, but prior to the treatment comparison phase, participants completed pre-

training; where they were exposed to all three accommodations. The pre-training was done to

ensure that participants were comfortable with using the accommodations. Without this step, a

participant's lack of comfort or skill in using the accommodation(s) could have severely affected

the ability to detect potentially strong positive effects of the accommodation(s).

The second phase, or the treatment comparison phase, consisted of alternating between

the two accommodation conditions to compare the relative efficiency of the conditions.

Additionally, in this phase, two sessions that included no accommodation were completed in

order to help confirm that any potential change in reading comprehension scores was due to the

accommodations and not a practice effect.

The third phase, or the best accommodation phase, consisted of the participant receiving

the accommodation condition that resulted in the highest percentage of content words recalled

score during the treatment comparison phase. The purpose of the best accommodation phase was

to mitigate multitreatment interference, a type of threat to internal validity. Multitreatment

interference occurs when one condition influences performance during another condition

(Wolery et al., 2018). This threat to internal validity typically happens during the treatment

comparison phase in the form of a rapid alteration effect (Wolery et al., 2018), which was when

performance was affected by rapidly changing conditions (Hains & Baer, 1989). The best

accommodation phase consisted of five sessions.

Procedures

Pre-Experimental Procedures

After Institutional Review Board approval, flyers (See Appendix E) were sent to reading

disability organizations, groups for parents of children with reading disabilities, local teachers,

and various businesses in order to recruit possible participants. Guardians who contacted the

primary researcher were sent a consent form and were asked about their childâ€™s reading

background.

The reading background questions were used as the first step in screening participants for

the study. Based on the reading background questions, a participant was selected if their guardian

reported that their child struggled with reading. Before administering the assessments, the

researcher met with the guardian(s) and child via Zoom to discuss the study and determine if

they passed a technology check. This check involved exploring whether the participantâ€™s internet

speed was sufficient for adequate data collection (e.g., lack of substantial video and/or sound lag,

lack of Zoom connection issues, etc.). If related concerns were identified, the researcher initially

worked to troubleshoot the issues with the family, but if the connection could not be improved,

the participant would be discontinued from the study. No participants were discontinued due to

computer issues in the study. Chosen participants were administered pre-test measures to

determine if they met the specific criteria described in the participants section.

After a participant met the criteria, they began the study. When participants completed

their pre-tests, they were sent a Scholastic gift card regardless of being chosen for the study.

Participants not chosen for the study were also sent reading resources such as suggested reading

interventions and techniques.

Measures Used to Determine Eligibility and Category (i.e., Pre-testing). The

following measures were used to determine eligibility and to categorize participants based on the

SVR conceptualization of reading difficulties.

Reading Background Questions. To screen participants for the study, each guardian was

asked questions about their childâ€™s reading background. The questions were, â€œDoes your child

struggle in reading? If so, do you know what they struggle with while reading?â€ (See Appendix

G). To be eligible, a guardian had to indicate â€œyesâ€ that their child struggled in reading. The

guardianâ€™s answer to the second question was used to determine the nature of the childâ€™s

difficulties.

Reading Eligibility Tests. The computerized versions of the tests were administered

online by a doctoral-level school psychology intern and used to determine eligibility for the

study (See Appendix F for information on administering computerized versions of Pearson

assessments). The reliability and validity evidence presented below for each subtest represents

evidence for the in-person test format; reliability and validity for the online computerized

versions have not been published. However, some initial research has suggested that there was

no significant difference between scores acquired in-person and virtually on cognitive and

achievement assessments (Hamner et al., 2021; Wright, 2020).

Woodcock Reading Mastery Tests, Third Edition (WRMT-III) Word Attack Subtest. To

measure decoding, the WRMT-III word attack task was administered. The measure required

participants to read nonsense words; this exercise was designed to specifically test phonological

and structural analysis skills (Woodcock, 2011). Indicators of reliability for alternative-form,

test-retest, and interrater agreement have been found to be .74 or higher (Woodcock, 2011). With

respect to validity, the WRMT-III word attack subtest correlates with the Woodcock-Johnson

Tests of Achievement word attack subtest at .55 (Woodcock, 2011) and the Expressive

Vocabulary Test (Williams, 2007) at .73 (Woodcock, 2011).

Woodcock Reading Mastery Tests, Third Edition (WRMT-III) Listening

Comprehension Subtest. The WRMT-III listening comprehension task measured the

participantsâ€™ ability to comprehend spoken language. A recording of the passages was played to

the participants, and the examiner requested that they answer associated questions about the

passages (Woodcock, 2011). This task measured both literal and inferential comprehension

skills. Measures of reliability for alternative-form, test-retest, and interrater agreement have been

found to be .74 or higher (Woodcock, 2011). With respect to validity, correlations between the

WRMT-III listening comprehension subtest and WLPB-R listening comprehension subtest have

been found to be .74, which was relatively high (Day, 2017). The listening comprehension

subtest was used as a proxy for measuring participantsâ€™ language comprehension skills.

Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V) Digit Span Subtest.

The WISC-V digit span task measured the participantsâ€™ working memory. The examiner read a

sequence of numbers, and the participants were asked to recall the numbers in the same order,

reverse order, and ascending order (Wechsler, 2014). Measures of reliability for split test and

test-retest have been found to be .79 or higher (Wechsler et al., 2014). With respect to validity, a

correlation between the WISC-V digit span subtest and the WISC-IV digit span subtest has been

found to be .65 (Wechsler et al., 2014). Also, the correlation between the WISC-V digit span

subtest and Wechsler Adult Intelligence Scale Fourth Edition (WAIS-IV) digit span subtest has

been found to be .80 (Wechsler et al., 2014).

General Procedures

Scripted protocols were used to ensure all participants received the same training and

instructions for each session during the different phases (See Appendix H-L). The protocols

introduced the procedures of the sessions, including instructions for each step of the session.

Participants did not receive feedback on their performance during the sessions, and dialogue was

restricted to general comments before and after the session. These general comments included

rapport-building topics, such as their favorite school activities, books, sports, television shows,

etc. During all study phases, if participants asked for assistance with technology, the researcher

provided assistance. However, no assistance was provided if it was deemed to potentially

compromise the reading comprehension measurement. For example, if a participant forgot how

to activate the read-aloud, the researcher walked the participant through the correct steps.

However, if the participant queried whether they forgot anything in their recall, the researcher

said, â€œjust try your best.â€

All sessions were video recorded via Zoom, and all participantsâ€™ recalls were transcribed

based on the video recording. To evaluate treatment integrity, a trained observer monitored

procedural implementation for at least 20% of sessions across all phases (Horner et al., 2005)

using the treatment integrity checklist (See Appendix I-L). Treatment integrity was calculated by

dividing the number of items marked as done correctly on the checklist by the total number of

items on the checklist and then multiplying by one hundred to yield a percentage (see Data

Analysis section; Gast & Ledford, 2014). The primary researcher was the only one to implement

the conditions.

A schedule was created for each participant and included one or two meetings per week

with two or three sessions per meeting (see Appendix M for an example schedule). Some

families needed an adapted schedule to participate in the study, so changes that resulted in more

or fewer sessions per meeting were made. For example, a few families desired fewer meetings,

so they had four sessions per meeting.

At the start of every meeting, the researcher referenced the participantâ€™s passage schedule

and pulled up the correct passage on the computer. The researcher read the title of the passage

and walked the participant through the appropriate steps to activate the reading

accommodation(s) that needed to be activated for the given condition (if any). After the

participant finished reading the passage, the researcher stopped sharing the screen and provided

the prompt associated with the two reading comprehension measures.

Participants who were chosen were sent additional Scholastic gift cards after baseline, in

the middle, and at the end of the study. After the last session, the researcher met with the family

to go over the participantâ€™s results, and the researcher suggested reading resources that the

participant might find helpful.

Baseline

At the start of each no accommodation condition session, a passage was displayed on the

computer screen, and the participant was told to begin reading independently and silently. If

participants started to read passages aloud during the baseline phase, they were immediately

reminded to read the passages silently. A scripted protocol was used for all no accommodation

condition sessions (See Appendix H-I).

Pre-training

Participants were shown how to use all three accommodations. Specifically, the

researcher used explicit instruction, including modeling and guiding, to teach the participant how

to use all the accommodations. For example, the researcher demonstrated how to use the

accommodation(s) and then walked the participant through how to use the accommodation(s)

step by step (see Appendix J for scripted protocol). After the participant finished reading the

passage, they were told to recall what they read.

Treatment Comparison

During the treatment comparison phase, participants alternated between the two reading

comprehension accommodation conditions and a no accommodation condition.

Decoding Condition. The researcher directed the participant to activate the read-aloud

accommodation. The participant clicked on the blue â€œNâ€ at the top right corner of the screen and

then the play button. They were also told to tell the researcher when they were done listening to

the passage. If the participant did not start the reader, they were instructed to listen to the passage

instead of reading independently. A scripted protocol was used for all decoding condition

sessions (See Appendix K).

Decoding + Language Comprehension Condition. The researcher directed the

participant to use all three of the accommodations: read-aloud accommodation, vocabulary

support, and comprehension monitoring. The researcher first directed the participant to right-

click on the word â€œvocabularyâ€ in blue under the title of the passage and â€œopen linkâ€ to open

another tab. Then, the participant was directed to open the read-aloud and listen to the

definitions. To open the read-aloud, the participant clicked on the blue â€œNâ€ at the top right of the

screen and then the play button. If the participant did not click on the word vocabulary and/or did

not listen to all the definitions, they were instructed to listen to all definitions before listening to

the passage.

After listening to the definitions, the participant was told to go back to the passage tab

and press play to listen to the passage. The researcher reminded the participant to pause the

reader when they got to the pause sign and then tell the researcher in their own words what they

have read. After listening to the participant summarize, the researcher told the participant to

continue listening to the passage and say when they were done. If a participant skipped the pause

sign, they were told to go back and complete it before continuing to read the passage. A scripted

protocol was used for all decoding + language comprehension condition sessions (See Appendix

L).

No Accommodation Condition. At the start of each no accommodation condition

session, a passage was displayed on the computer screen, and the participant was told to begin

reading independently and silently. A scripted protocol was used for all no accommodation

condition sessions (See Appendix I).

Best Accommodation

During the best accommodation phase, participants used the reading comprehension

accommodation condition that resulted in the highest reading comprehension score based on the

percentage of content words recalled measure. The percent of non-overlapping data formula (See

Data Analysis section for more information) was applied to the percentage of content words

recalled measure during the treatment comparison phase to determine the best accommodation

condition. A scripted protocol was used for all best accommodation phase sessions (See

Appendix K-L).

Interscorer Agreement

Scorer Training

In order to reduce the potential for bias, it was deemed necessary to train a secondary

scorer for the reading comprehension measures who was blind to the condition under which the

given measures were administered and the participant to whom the passage was administered.

Scoring by this individual was then compared to the primary researcherâ€™s scores to examine the

inter-scorer agreement. High levels of interscorer agreement help to control for threats to internal

validity in single-case research design (Ledford et al., 2018). Training of the blind secondary

scorer included providing the scorer with a verbal and visual overview of the two measures (i.e.,

the percentage of content words recalled and the number of words recalled) and giving the scorer

several opportunities to practice scoring measures completed by the pilot participants. The

secondary scorer was expected to show strong accuracy with scoring the measures prior to

starting to score the actual measures collected during the study. Specifically, the secondary

scorer needed a 90% agreement or higher with the anchor scorer (i.e., the primary researcher) on

four consecutive passages. For each administered passage, the number of agreements was

divided by the number of agreements plus the number of disagreements and then multiplied by

one hundred.

(

# ð‘œð‘“ ð´ð‘”ð‘Ÿð‘’ð‘’ð‘šð‘’ð‘›ð‘¡ð‘
(# ð‘œð‘“ ð´ð‘”ð‘Ÿð‘’ð‘’ð‘šð‘’ð‘›ð‘¡ð‘ + # ð‘œð‘“ ð·ð‘–ð‘ ð‘Žð‘”ð‘Ÿð‘’ð‘’ð‘šð‘’ð‘›ð‘¡ð‘ )

) ð‘‹ 100

For example, if scorer 1 counted 10 content words in the participantâ€™s recall and scorer 2 counted

9 content words, then the number of agreements (9) was divided by the number of agreements

(9) plus the number of disagreements (1) and then multiplied by one hundred ((9 Ã· (9 +

1)) Ã— 100 = 90).

During the experimental component of the study, the anchor scorer scored all the

passages, and the secondary scorer scored 96% of the passages. Anytime more than a 10%

difference occurred on a single passage between the anchor scorer and a secondary scorer then

the scorers double-checked their response to determine if any clear mistakes were made. If no

clear mistakes were made, then the scorers met to discuss their responses and come to an

agreement.

Interscorer Reliability for Participant Data

It was critical to establish a strong interscorer reliability after the baseline and treatment

comparison phases to ensure decisions made at the end of each phase were made based on

reliable data. The anchor scores were the scores reported and used to analyze the data, while the

secondary scorerâ€™s scores were used to check whether the anchor scores were reliable.

The intraclass correlation coefficient (ICC) was used to calculate interscorer reliability.

The ICC was calculated to estimate the overall reliability between the anchor scorer and the

secondary scorer. The two-way mixed-effects model was used when calculating the ICC because

the anchor scorer and secondary scorer were the only scorers of interest (Koo & Li, 2016).

During the baseline phase, the ICC value indicated excellent reliability between the anchor

scorer and secondary scorer for the percentage of content words recalled measure [ICC=0.986

with a 95% confidence interval of 0.961 to 0.994 (F(42,42) = 95.754, p<.001)] and there was

perfect reliability between the anchor scorer and secondary scorer for the number of words

recalled measure. During the alternating treatment phase, the ICC value indicated excellent

reliability between the anchor scorer and secondary scorer on the percentage of content words

recalled measure [ICC=0.993 with a 95% confidence interval of 0.985 to 0.997 (F(82, 82) =

194.294, p<.001)] and perfect reliability between the anchor scorer and secondary scorer on the

number of words recalled measure. When considering all data during the experimental portion of

the study, the ICC value indicated excellent reliability between the anchor scorer and secondary

scorer on the percentage of content words recalled measure [ICC=0.986 with a 95% confidence

interval of 0.966 to 0.992 (F(125, 125) = 178.564, p<.001)] and perfect reliability between the

anchor scorer and secondary scorer on the number of words recalled measure. Based on the ICC

analysis, the decisions to move to the treatment comparison phase and the best accommodation

condition decisions were based on reliable information.

Procedural Fidelity

Procedural fidelity is important in single-case design studies because the independent

variables are applied over time (Ledford & Gast, 2018). Measuring procedural fidelity is also

important because if the treatment were administered incorrectly, then the results would have

been based on inaccurate information. To promote procedural fidelity, scripted protocols were

used to ensure all participants received the same training and all sessions had standardized

administration scripts (Appendix H-L). Checklists corresponding with the scripted protocols

were created to allow the research assistant to observe and indicate the extent to which the

primary researcher followed the scripted protocols. After the completion of the checklist, the

percentage of items completed correctly was calculated.

To establish procedural fidelity, the research assistant watched the video recording of the

session and completed the fidelity checklist for each selected session. Specifically, procedural

fidelity was calculated by dividing the number of items marked as correctly completed on the

checklist by the total number of items on the checklist and then multiplying by one hundred to

yield a percentage (Gast & Ledford, 2014):

Procedural Fidelity Training

(

# ð‘ð‘œð‘Ÿð‘Ÿð‘’ð‘ð‘¡ ð‘–ð‘¡ð‘’ð‘šð‘
ð‘¡ð‘œð‘¡ð‘Žð‘™ # ð‘œð‘“ ð‘–ð‘¡ð‘’ð‘šð‘

) ð‘‹ 100

During the procedural fidelity training, an independent research assistant was trained to

observe the sessions to determine if they were administered with fidelity until they met a specific

criterion level of performance on the no accommodation, pre-training, decoding condition, and

decoding + language comprehension condition. The research assistant was expected to show

strong accuracy in calculating procedural fidelity (i.e., 100%) prior to starting to score actual

implementation videos. The training entailed an overview of the phases, along with watching

implementation videos and calculating fidelity based on checklists. Artificial videos created by

the primary researcher and videos from the pilot study were used as practice videos for the

research assistant. The research assistantâ€™s ability to accurately determine whether the sessions

were administered with fidelity during the training sessions was calculated using the same

agreement formula used in the scorer training section above. For example, if the primary

researcher gave a session 9/10 based on the checklist and the research assistant gave the session a

10/10 based on the checklist, then the number of agreements (9) was divided by the number of

agreements (9) plus the number of disagreements (1) and then multiplied by one hundred ((9 Ã·

(9 + 1)) Ã— 100 = 90). When compared to the primary researcher, the research assistant was

able to calculate the procedural fidelity with 100% accuracy during procedural fidelity training.

Procedural Fidelity for Participant Data

In case adjustments were needed, the research assistant watched the videos of the early

sessions for each phase within a week of implementation. This allowed the primary researcher to

make corrections early if any were needed. Besides the early sessions, sessions from each phase

were randomly selected for procedural fidelity checks and were conducted for at least 20% of the

sessions within the baseline phase, the session within the pre-training phase (where participants

were taught how to use the accommodations), 20% of the sessions within the treatment

comparison phase, and 20% of the sessions within the best accommodation phase. The

procedural fidelity ranged from 99% to 100% across all phases.

Data Analysis

To evaluate the effectiveness of the different accommodation conditions, three

approaches were used: an examination of the visual analysis, percent of non-overlapping data,

and Wilcoxon Signed-rank test. Visual analysis was used to provide an in-depth evaluation of

data within and across all participants and variables (Kazdin, 2011). For the primary dependent

variable (i.e., percentage of content words recalled), the data were inspected visually within each

phase and corresponding conditions to identify (a) trend (i.e., overall direction of data path); (b)

stability (i.e., variability of the data); (c) level (magnitude of the data; Ledford & Gast, 2018). A

between condition analysis was used to examine the immediacy of effect, overlap, consistency of

data patterns, or sudden changes in level (Ledford & Gast, 2018). The split-middle technique

was used to determine the trend (i.e., increase, decrease, no trend). The stability was defined as at

least 80% of the data falling within a 20% range of the median level of all data points in each

condition (Gast & Spriggs, 2010). The level was measured by calculating the median level for

each condition and comparing it across phases.

To assess the results of the alternating treatment design the percent of non-overlapping

data (PND) for the treatment comparison phase were examined (Scruggs et al., 1987).

Specifically, participant performance during the reading comprehension accommodation

conditions in the treatment comparison phase was compared to their performance during the no

accommodation condition in the baseline phase. Each accommodation condition was separately

compared to the baseline phase. PND was calculated by counting the number of sessions an

accommodation condition was superior to the highest baseline data point and dividing by the

total number of accommodation condition sessions (Parker & Hagan-Burke, 2007). For example,

if the decoding condition had three out of five sessions that were superior to the highest baseline

data point, PND would be:

3
5

Ã— 100 = 60%

The PND was also used to determine the best accommodation condition for the best

accommodation phase.

The nonparametric Wilcoxon Signed-rank test (Wilcoxon, 1992) was used to determine if

there were significant differences between conditions. Specifically, each participantâ€™s data were

treated as an individual case of ordinal data (i.e., within student), and the medians of each

accommodation condition during the alternating treatment phase were compared to the no

accommodation conditions in the baseline phase. The best accommodation phase was compared

to the adjacent accommodation condition during the alternating treatment phase and the baseline

phase. Statistical Package for Social Sciences (SPSS version 28) was used to run the Wilcoxon

Signed-rank Test and to calculate the significance. Using SPSS, a test statistic and its

significance were calculated. An effect size was then calculated using the formula ð‘Ÿ =

ð‘§

âˆšð‘

with N

representing the total number of samples. An effect size larger than 0.5 may be interpreted as

large, medium when between 0.3 and 0.5, and small when it is less than 0.3 (Cohen, 1969).

CHAPTER IV: RESULTS

This study examined the effects of reading accommodations on reading comprehension

for students with decoding difficulties. After independently reading expository reading passages

in a baseline phase, participants alternated between the decoding condition (i.e., read-aloud

accommodation) and the decoding + language comprehension condition (i.e., read-aloud

accommodation, vocabulary support, and comprehension monitoring) in the alternating treatment

phase. The researcher examined reading comprehension scores to determine the extent to which

(a) the use of the read-aloud accommodation affected general comprehension of text-based

material for students with word decoding difficulties, and (b) the use of the read-aloud

accommodation, vocabulary support, and comprehension monitoring affected general

comprehension of text-based material for students with word decoding difficulties.

Four main findings of the study were: (a) the difference between the decoding condition

and baseline phase was not associated with a statistically significant effect for any participants;

(b) two out of the seven participants displayed a positive statistically significant difference

between the decoding + language comprehension condition and the baseline phase; (c) the visual

differences between the decoding condition and baseline phase were inconsistent, and the

majority of participants showed no visual difference between the scores in the no

accommodation and decoding condition; and (d) the visual differences between the decoding +

language comprehension condition and baseline phase were inconsistent, and the visual

difference between the scores in the no accommodation condition and decoding + language

comprehension condition were inconsistent.

James

James participated in a total of 23 sessions over 11 meetings with no treatment

interruptions. James actively participated in each session, and sessions occurred as originally

planned. James had one to three sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 2 represents Jamesâ€™ percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 3

displays the data across meetings. The data were displayed both across sessions and across

meetings to determine whether James experienced any practice effects within meetings more

accurately. Table 4 represents a data analysis summary of Jamesâ€™ percentage of content words

recalled for each condition during the three phases. During the baseline phase, Jamesâ€™ percentage

of content words recalled ranged from 9.6% to 20.7% (Median Level=12.9%). During meetings

two and three, James had a slightly increased percentage of content words recalled during the

second session. Baseline data were considered stable, in that 83% of the data points fell within

the 20% of the median (Gast & Spriggs, 2010). Trend estimation using the split-middle

technique indicated an increasing trend (White & Haring, 1980). To control for the variable trend

present across the third, fourth, and fifth baseline data points, a sixth baseline passage was

administered. Following this administration, the last three baseline data points showed a visually

stable trend (See Figure 2).

During the alternating treatment phase, Jamesâ€™ percentage of content words recalled in

the decoding + language comprehension condition immediately increased (21.3%) compared to

his performance in the last session of baseline (14.0%). Jamesâ€™ percentage of content words

recalled for the decoding + language comprehension condition during the alternating treatment

phase ranged from 14.7% to 21.3% (Median Level = 18.1%). Only the ninth meeting had two

sessions of the decoding + language comprehension condition, and James had a lower percentage

of content words recalled during the second session. Data were considered stable in that 80% of

the data points fell within 20% of the median (Gast & Spriggs, 2010). Using the split-middle

technique, Jamesâ€™ data exhibited a decreasing trend (White & Haring, 1980).

During the alternating treatment phase, Jamesâ€™ first percentage of content words recalled

in the decoding condition slightly decreased (13.3%) compared to his performance in the last

session of baseline (14.0%). Jamesâ€™ percentage of content words recalled for the decoding

condition during the alternating treatment phase ranged from 13.1% to 23.3% (Median Level =

20.9%). Only the sixth meeting had two sessions of the decoding condition, and James had a

higher percentage of content words recalled during the second session. Data were considered

stable in that 80% of the data points fell within the 20% of the median (Gast & Spriggs, 2010).

The split-middle technique rendered an increasing trend (White & Haring, 1980).

Using the split-middle technique, Jamesâ€™ no accommodation condition data exhibited an

increasing trend (White & Haring, 1980). Visually, there seemed to be only a small difference

between the scores in the no accommodation condition and the two reading accommodation

conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding condition was identified as the best accommodation

condition and used for the best accommodation phase. During the best accommodation phase,

Jamesâ€™ first percentage of content words recalled decreased (14.6%) compared to his

performance in the last session of the decoding condition in the alternating treatment phase

(20.9%). With the exception of the highest score in the best accommodation phase (28.7%), all

the other data points in the phase overlapped with the decoding condition in the alternating

treatment phase. During the best accommodation phase, Jamesâ€™ first percentage of content words

recalled slightly increased (14.6%) compared to his performance in the last session of the

baseline phase (14.0%). With the exception of the highest score (28.7) in the best

accommodation phase, the other data points in the phase overlapped with the baseline phase.

Visual inspection of Jamesâ€™ data during the best accommodation phase with the decoding

condition revealed data ranging from 12.3% to 28.7% (Median Level = 14.6%). Data were

considered variable, as only 60% of the data points fell within 20% of the median (Gast &

Spriggs, 2010). Trend estimation using the split-method technique indicated an increasing trend

(White & Haring, 1980).

Overall, visually there was no clear data separation between the reading comprehension

conditions and the baseline phase.

Figure 2

Jamesâ€™ Percentage of Total Content Words Recalled (Sessions)

Figure 3

Jamesâ€™ Percentage of Total Content Words Recalled (Meetings)

Table 4

Data Analysis Summary of Jamesâ€™ Percentage of Total Content Words Recalled

Measure

Range
Median
Trend
Stability

Baseline

Decoding +
Languagea
9.6-20.7% 14.7-21.3% 13.1-23.3%
18.1%

Decodingb

12.9%

Increasing Decreasing

Stable

20.9%
Increasing
Stable

No
Accommodationc
17.6-18.6%
18.1%
Increasing
Stable

Best
Accommodation
12.3-28.7%
14.6%
Increasing
Variable

Note: a = decoding + language comprehension condition; b = decoding condition; c = no
accommodation condition

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. One score in the decoding + language comprehension condition was

higher than the highest score in the baseline phase (1
5

Ã— 100 = 20%). Three scores in the

decoding condition were higher than the highest score in the baseline phase ( 3
5

Ã— 100 = 60%).

Therefore, the decoding condition was chosen for the best accommodation condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled. For the

Wilcoxon signed-rank test and sign test, it is required to have an equal number of data points in

the two conditions being compared. Therefore, sessions two through six were used for the

baseline phase because the last three baseline data points show a stable trend, which indicates

that the participant was able to move on to the next phase.

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the difference scores were approximately symmetrically distributed, as assessed by a

histogram with a superimposed normal curve, a Wilcoxon signed-rank test was conducted. James

had a higher percentage of content words recalled during the decoding + language

comprehension condition in the alternating treatment phase (Mdn = 18.1%) than during the

baseline phase (Mdn = 14.0%). The median difference produced (Mdn = 4.9%) was not

statistically significant (z = -1.8; p = .08). The effect size of treatment was calculated (z = -1.8, N

= 10, r = -.6) and demonstrated a large effect. Table 5 illustrates the results of the Wilcoxon

signed-rank test.

Table 5

Jamesâ€™ Wilcoxon Signed-Rank Test Results for the Decoding + Language Comprehension

Condition vs. Baseline Phase

Test Statistica

Median Difference
Z
Asymp. Sig.c (Two-Tailed)

Decoding + Language Comprehension vs. Baseline
% of Content Words Recalledb
4.9%
-1.8
.08

Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c = asymptotic
significance

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. James had a higher

percentage of content words recalled during the decoding condition in the treatment comparison

phase (Mdn = 20.9%) than during the baseline phase (Mdn = 14.0%). The produced median

difference (Mdn = 6.2%) was not statistically significant (p = .06). Table 6 illustrates the results

of the sign test.

Table 6

Jamesâ€™ Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
6.2%
.06

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. James had a slightly higher

percentage of content words recalled during the best accommodation phase (Mdn = 14.6%) than

during the baseline phase (Mdn = 14.0%). The median difference produced (Mdn = 4.4%) did

not elicit a statistically significant difference (p = 1.00). Table 7 illustrates the results of the sign

test.

Table 7

Jamesâ€™ Sign Test Results for the Best Accommodation Phase vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.d (Two-Tailed)

Best Accommodation vs. Baseline
% of Content Words Recalledb
4.4
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Jamesâ€™ Overall Data Analysis Summary

Table 8 represents a data analysis summary of Jamesâ€™ Wilcoxon signed-rank test and sign

test for the percentage of content words recalled and the number of words recalled. Additional

analyses were run for the number of words recalled. As presented below, there were no major

differences in the scores James obtained for the percentage of words recalled and the number of

words recalled.

Table 8

Data Analysis Summary of Jamesâ€™ Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

Exact. Sig.a
(Two-Tailed)

Asymp. Sig.b
(Two-Tailed)

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

6.2

4.9

Decoding + LC vs.
Baselinee
Decoding vs. Baselinef
Best Accomm vs.
Decodingg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding + language comprehension condition vs. baseline; f = decoding vs.
baseline; g = best accommodation vs baseline

1.00

-1.8

.38

.08

.06

-9

.14

The primary outcome of Jamesâ€™ results indicated no difference between the baseline and

the reading comprehension accommodation conditions. Specifically, based on the visual

analysis, there was no clear data separation between the reading comprehension conditions and

the baseline phase. The accommodation scores during the alternating treatment phase displayed

no difference visually when compared to the two no accommodation session scores within that

phase. Based on the PND, Jamesâ€™ best accommodation was the decoding condition. Neither

accommodation condition displayed a significant improvement over the baseline phase.

Although slight differences were found between the reading comprehension conditions and the

baseline phase, the hypothesized pattern did not emerge in either condition.

Robert

Robert participated in a total of 23 sessions over 10 meetings with no treatment

interruptions. Robert actively participated in each session, and sessions occurred as originally

planned. Robert had one to four sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 4 presents Robertâ€™s percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 5

displays the data across meetings. The data were displayed both across sessions and across

meetings to more accurately determine whether Robert experienced any practice effects within

meetings. Table 9 represents a data analytic summary of Robertâ€™s percentage of content words

recalled for each condition during the three phases. During the baseline phase, Robertâ€™s

percentage of content words recalled ranged from 5.8% to 14.6% (Median Level = 9.3%).

During meeting two, Robert had a slightly increased percentage of content words recalled during

the second session. Baseline data were variable, as only 50% of the data points fell within the

20% of the median (Gast & Spriggs, 2010). Trend estimation using the split-middle technique

indicated an increasing trend (White & Haring, 1980). To control for the increasing trend across

the third, fourth, and fifth baseline data points, a sixth baseline passage was administered.

Following this administration, the last three baseline data points showed a visually decreasing

trend (see Figure 4).

During the alternating treatment phase, Robertâ€™s percentage of content words recalled in

the decoding + language comprehension condition immediately increased (7.7%) compared to

his performance in the last session of baseline (5.8%). Robertâ€™s percentage of content words

recalled for the decoding + language comprehension condition during the alternating treatment

phase ranged from 7.7% to 16.9% (median level = 13.3%). The fifth and seventh meeting had

two sessions of the decoding + language comprehension condition, and Robert had a higher

percentage of content words recalled during the second session. Data were considered variable,

as only 60% of the data points fell within 20% of the median (Gast & Spriggs, 2010). Using the

split-middle technique, Robertâ€™s data exhibited an increasing trend (White & Haring, 1980).

During the alternating treatment phase, Robertâ€™s first percentage of content words

recalled in the decoding condition slightly decreased (6.8%) compared to his performance in the

last session of baseline (5.8%). Robertâ€™s percentage of content words recalled for the decoding

condition during the alternating treatment phase ranged from 6.8% to 17.4% (Median Level =

13.3%). Only the sixth meeting had two sessions of the decoding condition, and Robert had a

higher percentage of content words recalled during the second session. Data were considered

variable, as only 60% of the data points fell within the 20% of the median (Gast & Spriggs,

2010). The split-middle technique rendered an increasing trend (White & Haring, 1980).

Using the split-middle technique, Robertâ€™s no accommodation condition data exhibited

an increasing trend (White & Haring, 1980). Visually there seems to be only a small difference

between the scores in the no accommodation condition and the two reading accommodation

conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding + language comprehension condition was identified as

the best accommodation condition and used for the best accommodation phase. During the best

accommodation phase, Robertâ€™s first percentage of content words recalled decreased (11.7%)

compared to his performance in the last session of the decoding + language comprehension

condition in the alternating treatment phase (13.3%). All of the data points in the phase

overlapped with the decoding + language comprehension condition in the alternating treatment

phase. During the best accommodation phase, Robertâ€™s first percentage of content words recalled

increased (11.7%) compared to his performance in the last session of the baseline phase (5.8%).

All the data points in the best accommodation phase overlapped with the baseline phase. Visual

inspection of Robertâ€™s data during the best accommodation phase with the decoding + language

comprehension condition revealed data ranging from 7.8% to 11.7% (Median Level = 9.6%).

Data were considered variable, as only 60% of the data points fell within 20% of the median

(Gast & Spriggs, 2010). Trend estimation using the split-method technique indicated a trend of

zero (White & Haring, 1980).

Overall, visually there was no clear data separation between the reading comprehension

conditions and the baseline phase.

Figure 4

Robertâ€™s Percentage of Total Content Words Recalled (Sessions)

Figure 5

Robertâ€™s Percentage of Total Content Words Recalled (Meetings)

Table 9

Data Analysis Summary of Robertâ€™s Percentage of Total Content Words Recalled

Measure Baseline

Decodingb

No
Accommodationc
8.9%-14.1%

Best
Accommodation
7.8%-11.7%

Range

6.8%-
5.8%-
17.4%
14.6%
13.3%
9.3%
Median
Increasing
Trend
Increasing
Stability Variable
Variable
Note: a = decoding + language comprehension condition; b = decoding condition; c = no
accommodation condition

11.5%
Increasing
Variable

9.6%
None
Variable

Decoding +
Languagea
7.7%-
16.9%
13.3%
Increasing
Variable

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. One score in the decoding condition was higher than the highest score in

the baseline phase (1
5

Ã— 100 = 20%). In the decoding + language comprehension condition, two

scores were higher than the highest score in the baseline phase ( 2
5

Ã— 100 = 40%). Therefore,

the decoding + language comprehension condition was chosen for the best accommodation

condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled. For the

Wilcoxon signed-rank test and sign test, it is required to have an equal number of data points in

the two conditions being compared. Therefore, sessions two through six were used for the

baseline condition because the last three baseline data points show a decreasing trend which

indicates that the participant was able to move on to the next phase.

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the distribution of differences was not symmetrically shaped, a sign test was conducted.

Robert had a higher percentage of content words recalled during the decoding + language

comprehension condition in the alternating treatment phase (Mdn = 13.3%) than during the

baseline phase (Mdn = 8.9%). The median difference produced (Mdn = 2.7%) was not

statistically significant (p = .38). Table 10 illustrates the results of the sign test.

Table 10

Robertâ€™s Sign Test Results for the Decoding + Language Comprehension Condition vs. Baseline

Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding + Language Comprehension vs. Baseline
% of Content Words Recalledb
2.7
.38

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. Robert had a higher

percentage of content words recalled during the decoding condition in the treatment comparison

phase (Mdn = 13.3%) than during the baseline phase (Mdn = 8.9%). The produced median

difference (Mdn = 2.4%) was not statistically significant (p = 1.00). Table 11 illustrates the

results of the sign test.

Table 11

Robertâ€™s Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
2.4
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the difference

scores were approximately symmetrically distributed, as assessed by a histogram with a

superimposed normal curve, a Wilcoxon signed-rank test was conducted. Robert had a slightly

higher percentage of content words recalled during the best accommodation phase (Mdn = 9.6%)

than during the baseline phase (Mdn = 8.9%). The median difference produced (Mdn = -.07%)

did not elicit a statistically significant difference (z = -.14; p = .89). The effect size of treatment

was calculated (z = -.14, N = 10, r = -.04), highlighting a medium effect. Table 12 illustrates the

results of the Wilcoxon signed-rank test.

Table 12

Robertâ€™s Wilcoxon-Signed Rank Test Results for the Best Accommodation Phase vs. Baseline

Phase

Test Statistica

Mean Difference
Z
Asymp. Sig.c (Two-Tailed)

Best Accommodation vs. Baseline
% of Words Recalledb
-.07
-.14
.89

Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c = asymptotic
significance

Robertâ€™s Overall Data Analysis Summary

Table 13 represents a data analysis summary of Robertâ€™s Wilcoxon signed-rank test and

sign test for the percentage of content words recalled and the number of words recalled. Follow-

up analyses were run for the number of words recalled. As shown below, there were no major

differences in the scores Robert obtained for the percentage of content words recalled and the

number of words recalled.

Table 13

Data Analysis Summary of Robertâ€™s Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

% of
Wordsc

# of
Wordsd

Exact. Sig.a (Two-
Tailed)

% of
Wordsc

# of
Wordsd

Asymp. Sig.b (Two-
Tailed)

% of
Wordsc

# of
Wordsd

2.4

.38

2.7

.06

Decoding + LC vs.
Baselinee
Decoding vs.
Baselinef
Best Accomm vs.
Baselineg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding + language comprehension condition vs. baseline; f = decoding vs.
baseline; g = best accommodation vs. baseline

1.00

-.07

.13

.89

.50

The primary outcome of Robertâ€™s results indicated no difference between the baseline

and the reading comprehension accommodation conditions. Specifically, based on the visual

analysis, there was no clear data separation between the reading comprehension conditions and

the baseline phase. The accommodation scores during the alternating treatment phase displayed

no difference visually when compared to the two no accommodation session scores within that

phase. Based on the PND, Robertâ€™s best accommodation condition was the decoding + language

comprehension condition. Neither accommodation condition displayed a significant

improvement over the baseline phase. Although slight differences were found between the

reading comprehension conditions and the baseline phase, the hypothesized pattern did not

emerge for either condition.

John

John participated in a total of 23 sessions over 12 meetings with no treatment

interruptions. John actively participated in each session, and sessions occurred as originally

planned. John had one to three sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 6 represents Johnâ€™s percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 7

displays the data across meetings. The data were displayed both across sessions and across

meetings to more accurately determine whether John experienced any practice effects within

meetings. Table 14 represents a data analysis summary of Johnâ€™s percentage of content words

recalled for each condition during the three phases. During the baseline phase, Johnâ€™s percentage

of content words recalled ranged from 2.4% to 10.2% (Median Level= 6.4%). During meetings

two and four, John had a lower percentage of content words recalled during the session. Baseline

data were considered variable, as only 50% of the data points fell within the 20% of the median

(Gast & Spriggs, 2010). Trend estimation using the split-middle technique indicated an

increasing trend (White & Haring, 1980). To control for the increasing trend present across the

third, fourth, and fifth baseline data points, a sixth baseline passage was administered. Following

this administration, the last three baseline data points showed a visually decreasing trend (See

Figure 6).

During the alternating treatment phase, Johnâ€™s percentage of content words recalled in the

decoding condition increased (8.7%) compared to his performance in the last session of baseline

(7.5%). Johnâ€™s percentage of content words recalled for the decoding condition during the

alternating treatment phase ranged from 8.7% to 23.6% (Median Level = 20.9%). Data were

considered stable in that 80% of the data points fell within 20% of the median (Gast & Spriggs,

2010). Using the split-middle technique, Johnâ€™s data exhibited an increasing trend (White &

Haring, 1980).

During the alternating treatment phase, Johnâ€™s first percentage of content words recalled

in the decoding + language comprehension condition slightly increased (15.7%) compared to his

performance in the last session of baseline (7.5%). Johnâ€™s percentage of content words recalled

for the decoding + language comprehension condition during the alternating treatment phase

ranged from 15.7% to 31.7% (Median Level = 23.2%). Only the ninth meeting had two sessions

of the decoding + language comprehension condition, and John had a higher percentage of

content words recalled during the second session. Data were considered variable, as only 60% of

the data points fell within the 20% of the median (Gast & Spriggs, 2010). The split-middle

technique rendered an increasing trend (White & Haring, 1980).

Using the split-middle technique, Johnâ€™s no accommodation condition data exhibited an

increasing trend (White & Haring, 1980). Visually, the no accommodation condition seemed to

be lower compared to the two reading comprehension conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding + language comprehension condition was identified as

the best accommodation condition and used for the best accommodation phase. During the best

accommodation phase, Johnâ€™s first percentage of content words recalled slightly decreased

(24.6%) compared to his performance in the last session of the decoding + language

comprehension condition in the alternating treatment phase (26.9%). All the data points in the

phase overlapped with the decoding + language comprehension condition in the alternating

treatment phase. During the best accommodation phase, Johnâ€™s first percentage of content words

recalled increased (24.6%) compared to his performance in the last session of the baseline phase

(7.5%). All the data points in the best accommodation phase were higher than the baseline phase.

Visual inspection of Johnâ€™s data during the best accommodation phase with the decoding +

language comprehension condition revealed data ranging from 17.5% to 24.6% (Median Level =

20.0%). During the ninth meeting in the best accommodation phase, John had a lower of

percentage of content words recalled during the second session. Data were considered stable in

that 80% of the data points fell within 20% of the median (Gast & Spriggs, 2010). Trend

estimation using the split-method technique indicated an increasing trend (White & Haring,

1980).

Overall, visually there was clear data separation between the reading comprehension

conditions and the baseline phase.

Figure 6

Johnâ€™s Percentage of Total Content Words Recalled (Sessions)

Figure 7

Johnâ€™s Percentage of Total Content Words Recalled (Meetings)

Table 14

Data Analysis Summary of Johnâ€™s Percentage of Total Content Words Recalled

Measure

Baseline

Decodinga

Range

2.4%-10.2% 8.7%-23.6%

No
Accommodationc
10.2%-12.8%

Best
Accommodation
17.5%-24.6

6.4%
Increasing
Variable

Median
Trend
Stability
Note: a = decoding condition; b = decoding + language comprehension condition; c = no
accommodation condition

11.5%
Increasing
Stable

20.9%
Increasing
Stable

20%
Increasing
Stable

Decoding +
Languageb
15.7%-
31.7%
23.2%
Increasing
Variable

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. Four scores in the decoding condition were higher than the highest score

in the baseline phase ( 4
5

Ã— 100 = 80%). Five scores in the decoding + language comprehension

condition were higher than the highest score in the baseline phase (5
5

Ã— 100 =

100%). Therefore, the decoding + language comprehension condition was chosen for the best

accommodation condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled. For the

Wilcoxon signed-rank test and sign test, it is required to have an equal number of data points in

the two conditions being compared. Therefore, sessions two through six were used for the

baseline phase because the last three baseline data points show a decreasing trend which

indicates that the participant was able to move on to the next phase.

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. John had a higher

percentage of content words recalled during the decoding condition in the alternating treatment

phase (Mdn = 21.0%) than during the baseline phase (Mdn = 7.5%). The median difference

produced (Mdn = 15.0%) was not statistically significant (p = .06). Table 15 illustrates the results

of the sign test.

Table 15

Johnâ€™s Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
15
.06

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the difference scores were approximately symmetrically distributed, as assessed by a

histogram with a superimposed normal curse, a Wilcoxon signed-rank test was conducted. John

had a higher percentage of content words recalled during the decoding + language

comprehension condition in the treatment comparison phase (Mdn = 23.2%) than during the

baseline phase (Mdn = 7.5%). The produced median difference (Mdn = 18.3%) was statistically

significant (z = -2.02, p = .04). The effect size of treatment was calculated (z = -2.02, N = 10, r =

-.64), which demonstrates a large effect. Table 16 illustrates the results of the Wilcoxon signed-

rank test.

Table 16

Johnâ€™s Wilcoxon Signed-Rank Test Results for the Decoding + Language Comprehension

Condition vs. Baseline Phase

Test Statistica

Decoding + Language Comprehension vs. Baseline
% of Content Words Recalledb
18.3
-2.02
.04

Mean Difference
Z
Asymp. Sig.c (Two-Tailed)
Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c =
asymptotic significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the difference

scores were approximately symmetrically distributed, as assessed by a histogram with a

superimposed normal curve, a Wilcoxon singed-rank test was conducted. John had a higher

percentage of content words recalled during the best accommodation phase (Mdn = 20.0%) than

during the baseline phase (Mdn = 7.5%). The median difference (Mdn = 15.7%) elicited a

statistically significant difference (z = -2.0, p = .04). The effect size of treatment was calculated

(z = -2.0, N = 10, r = -.63), suggesting a large effect. Table 17 illustrates the results of the

Wilcoxon signed-rank test.

Table 17

Johnâ€™s Wilcoxon Signed-Rank Test Results for the Best Accommodation Phase vs. Baseline

Phase

Test Statistica

Median Difference
Z
Asymp. Sig.c (Two-Tailed)

Best Accommodation vs. Baseline
% of Words Recalledb
15.7
-2.02
.04

Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c = asymptotic
significance

Johnâ€™s Overall Data Analysis Summary

Table 18 represents a data analysis summary of Johnâ€™s Wilcoxon signed-rank test and

sign test for the percentage of content words recalled and the number of words recalled.

Additional analyses were run for the number of words recalled. As presented below, there was

one difference in the scores John obtained for the percentage of content words recalled, and the

number of words recalled measure. Specifically, there was a significant difference between the

best accommodation phrase and the baseline phase for the percentage of content words recalled

but not for the number of words recalled.

Table 18

Data Analysis Summary of Johnâ€™s Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

% of
Wordsc
14.9

# of
Wordsd
62

Exact. Sig.a
(Two-Tailed)
# of
Wordsd
.06

% of
Wordsc
.06

Asymp. Sig.b (Two-
Tailed)

% of
Wordsc
--

# of
Wordsd
--

18.3

Decoding vs. Baselinee
Decoding + LC vs.
Baselinef
Best Accomm vs.
Baselineg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding vs. baseline; f = decoding + language comprehension condition vs.
baseline; g = best accommodation vs. baseline

15.71

.06

.04

The primary outcome of Johnâ€™s results indicated a disparity between the baseline and the

reading comprehension accommodation conditions. Specifically, based on the visual analysis,

there was clear data separation between the reading comprehension conditions and the baseline

phase. There was a visual difference when comparing the decoding + language comprehension

condition to the two no accommodation session scores within the alternating treatment phase for

both reading comprehension measures. Based on the PND, Johnâ€™s best accommodation condition

was the decoding + language comprehension condition. The decoding + language

comprehension condition displayed a significant improvement over the baseline phase for both

reading comprehension measures. To some degree there seems to be positive effects of the

decoding condition, which supports the first hypothesis. However, it looks as if the decoding +

language comprehension condition may have been even more effective, which does not support

the second hypothesis.

William

William participated in a total of 26 sessions over 13 meetings with no treatment

interruptions. William actively participated in each session, and sessions occurred as originally

planned. William had one to three sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 8 represents Williamâ€™s percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 9

displays the data across meetings. The data were displayed both across sessions and across

meetings to more accurately determine whether William experienced any practice effects within

meetings. Table 19 represents a data analysis summary of Williamâ€™s percentage of content words

recalled for each condition during the three phases. During the baseline phase, Williamâ€™s

percentage of content words recalled ranged from 6.1% to 20.9% (Median Level=12.2%).

During meetings two and five, William had a decreased percentage of content words recalled

during the second session. However, during meetings three and four, William had an increased

percentage of content words recalled during the second session. Baseline data were considered

variable, as only 55% of the data points fell within the 20% of the median (Gast & Spriggs,

2010). Trend estimation using the split-middle technique indicated an increasing trend (White &

Haring, 1980). To control for the increasing trend present across the third, fourth, and fifth

baseline data points, sixth through ninth baseline passages were administered. Following this

administration, the last three baseline data points showed a visually decreasing trend (See Figure

8).

During the alternating treatment phase, Williamâ€™s percentage of content words recalled in

the decoding condition increased (19.0%) compared to his performance in the last session of

baseline (11.5%). Williamâ€™s percentage of content words recalled for the decoding condition

during the alternating treatment phase ranged from 14.3% to 20.4% (Median Level = 15.8%).

Data were considered variable, as only 60% of the data points fell within 20% of the median

(Gast & Spriggs, 2010). Using the split-middle technique, Williamâ€™s data exhibited a decreasing

trend (White & Haring, 1980).

During the alternating treatment phase, Williamâ€™s first percentage of content words

recalled in the decoding + language comprehension condition slightly increased (14.7%)

compared to his performance in the last session of baseline (11.5%). Williamâ€™s percentage of

content words recalled for the decoding + language comprehension condition during the

alternating treatment phase ranged from 8.3% to 21.7% (Median Level = 10.8%). The ninth

meeting had two sessions of the decoding + language comprehension condition, and William had

a lower percentage of content words recalled during the second session. Data were considered

variable, as only 40% of the data points fell within the 20% of the median (Gast & Spriggs,

2010). The split-middle technique rendered an increasing trend (White & Haring, 1980).

Using the split-middle technique, Williamâ€™s no accommodation condition data exhibited

a decreasing trend (White & Haring, 1980). Visually there seems to be only a small difference

between the scores in the no accommodation condition and the two reading accommodation

conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding + language comprehension condition was identified as

the best accommodation condition and used for the best accommodation phase. During the best

accommodation phase, Williamâ€™s first percentage of content words recalled decreased (13.8%)

compared to his performance in the last session of the decoding + language comprehension

condition in the alternating treatment phase (21.7%). All the data points in the best

accommodation phase overlapped with the decoding + language comprehension condition in the

alternating treatment phase. During the best accommodation phase, Williamâ€™s first percentage of

content words recalled increased (13.8%) compared to his performance in the last session of the

baseline phase (11.5%). All the data points in the best accommodation phase overlapped with the

baseline phase. Visual inspection of Williamâ€™s data during the best accommodation phase with

the decoding + language comprehension condition revealed results ranging from 7.6% to 17.2%

(Median Level = 12.7%). During the twelfth meeting, William had a lower percentage of content

words recalled during the second session. During the thirteenth meeting, William had a higher

percentage of content words recalled during the second session. Data were considered variable,

as only 40% of the data points fell within 20% of the median (Gast & Spriggs, 2010). Trend

estimation using the split-method technique indicated an increasing trend (White & Haring,

1980).

Overall, visually there was no clear data separation between the reading comprehend

condition and the baseline phrase.

Figure 8

Williamâ€™s Percentage of Total Content Words Recalled (Sessions)

Figure 9

Williamâ€™s Percentage of Total Content Words Recalled (Meetings)

Table 19

Data Analysis Summary of Williamâ€™s Percentage of Total Content Words Recalled

Measure

Baseline

Decodinga

Range

6.1%-20.9%

14.3%-
20.4%
15.8%

Decoding +
Languageb
8.3%-21.7%

No
Accommodationc
15.5%-21.4%

Best
Accommodation
7.6%-17.2%

12.2%

Median
Trend
Stability
Note: a = decoding condition; b = decoding + language comprehension condition; c = no
accommodation condition

Increasing Decreasing
Variable
Variable

18.4%
Decreasing
Stable

10.78%
Increasing
Variable

12.7%
Increasing
Variable

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. No scores in the decoding condition were higher than the highest score in

the baseline phase ( 0
5

Ã— 100 = 0%). One score in the decoding + language comprehension

condition was higher than the highest score in the baseline phase (1
5

Ã— 100 = 20%). Therefore,

the decoding + language comprehension condition was chosen as the best accommodation

condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled. For the

Wilcoxon signed-rank test and sign test, it is required to have an equal number of data points in

the two conditions being compared. Therefore, sessions five through nine were used for the

baseline phase because the last three baseline data points show a decreasing trend which

indicates that the participant was able to move on to the next phase.

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. William had a higher

percentage of content words recalled during the decoding condition in the alternating treatment

phase (Mdn = 15.8%) than during the baseline phase (Mdn = 12.2%). The median difference

produced (Mdn = 2.9%) was not statistically significant (p = 1.00). Table 20 illustrates the results

of the sign test.

Table 20

Williamâ€™s Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
2.9
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the distribution of differences was not symmetrically shaped, a sign test was conducted.

William had a lower percentage of content words recalled during the decoding + language

comprehension condition in the treatment comparison phase (Mdn = 10.8%) than during the

baseline phase (Mdn = 12.2%). The produced median difference (Mdn = -2.1%) was not

statistically significant (p = 1.00). Table 21 illustrates the results of the sign test.

Table 21

Williamâ€™s Sign Test Results for the Decoding + Language Comprehension Condition vs.

Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding + Language Comprehension vs. Baseline
% of Content Words Recalledb
-2.1
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. William had a slightly

higher percentage of content words recalled during the best accommodation phase (Mdn =

12.7%) than during the baseline phase (Mdn = 12.2%). The median difference produced (Mdn =

4.2%) did not elicit a statistically significant difference (p = 1.00). Table 22 illustrates the results

of the sign test.

Table 22

Williamâ€™s Sign Test Results for the Best Accommodation Phase vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Best Accommodation vs. Baseline
% of Content Words Recalledb
-4.2
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Williamâ€™s Overall Data Analysis Summary

Table 23 represents a data analysis summary of Williamâ€™s Wilcoxon signed-rank test and

sign test for the percentage of content words recalled and the number of words recalled. Follow-

up analyses were conducted on the number of words recalled. As seen below, there were no

major differences in the scores William obtained for the percentage of content words recalled

and the number of words recalled.

Table 23

Data Analysis Summary of Williamâ€™s Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

Exact. Sig.a
(Two-Tailed)

Asymp. Sig.b (Two-
Tailed)

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

2.9

-2.1

1.00

Decoding vs.
Baselinee
Decoding + LC vs.
Baselinef
Best Accomm vs.
Baselineg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding vs. baseline; f = decoding + language comprehension condition vs.
baseline; g = best accommodation vs. baseline

-4.22

1.00

-10

The primary outcome of Williamâ€™s results indicated no difference between the baseline

and the reading comprehension accommodation conditions. Specifically, based on the visual

analysis, there was no clear data separation between the reading comprehend condition and the

baseline phrase. The accommodation scores during the alternating treatment phase displayed no

difference visually when compared to the two no accommodation session scores within that

phase. Based on the PND, Williamâ€™s best accommodation condition was the decoding +

language comprehension condition. Neither accommodation condition displayed a significant

improvement over the baseline phase. Although slight differences were found between reading

comprehension conditions and the baseline phase, the hypothesized pattern did not emerge for

either condition.

Matthew

Matthew participated in a total of 22 sessions over 8 meetings with no treatment

interruptions. Matthew actively participated in each session, and sessions occurred as originally

planned. Matthew had one to five sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 10 represents Matthewâ€™s percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 11

displays the data across meetings. The data were displayed both across sessions and across

meetings to more accurately determine whether Matthew experienced any practice effects within

meetings. Table 24 represents a data analysis summary of Matthewâ€™s percentage of content

words recalled for each condition during the three phases. During the baseline phase, Matthewâ€™s

percentage of content words recalled ranged from 1.8% to 9.7% (Median Level = 3.5%). During

meetings one and two, Matthew had a decreased percentage of content words recalled during the

second session. Baseline data were considered variable, as only 40% of the data points fell

within 20% of the median (Gast & Spriggs, 2010). Trend estimation using the split-middle

technique indicated a decreasing trend (White & Haring, 1980).

During the alternating treatment phase, Matthewâ€™s percentage of content words recalled

in the decoding condition immediately increased (26.2%) compared to his performance in the

last session of baseline (2.5%). Matthewâ€™s percentage of content words recalled for the decoding

condition during the alternating treatment phase ranged from 11.1% to 26.2% (Median Level =

17.8%). Only the fourth meeting had two sessions of the decoding condition, and Matthew had a

higher percentage of content words recalled during the second session. Data were considered

variable, as only 40% of the data points fell within 20% of the median (Gast & Spriggs, 2010).

Using the split-middle technique, Matthewâ€™s data exhibited a decreasing trend (White & Haring,

1980).

During the alternating treatment phase, Matthewâ€™s first percentage of content words

recalled in the decoding + language comprehension condition increased (15.9%) compared to

his performance in the last session of baseline (2.5%). Matthewâ€™s percentage of content words

recalled for the decoding + language comprehension condition during the alternating treatment

phase ranged from 2.9% to 15.9% (Median Level = 5.6%). During the fifth meeting there was

two sessions of the decoding + language comprehension condition, and Matthew had a higher

percentage of content words of recalled during the second session. However, during the sixth

meeting he had a lower percentage of content words of recalled during the second session. Data

were considered variable, as only 40% of the data points fell within 20% of the median (Gast &

Spriggs, 2010). The split-middle technique rendered a decreasing trend (White & Haring, 1980).

Using the split-middle technique, Matthewâ€™s no accommodation condition data exhibited

no trend (White & Haring, 1980). Visually, the no accommodation condition seemed to be

slightly lower compared to the two reading accommodation conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding condition was identified as the best accommodation

condition and used for the best accommodation phase. During the best accommodation phase,

Matthewâ€™s first percentage of content words recalled decreased (11.2%) compared to his

performance in the last session of the decoding condition in the alternating treatment phase

(14.5%). With the exception of the highest score in the best accommodation phase (11.2%), all

the other data points in the phase were lower than all the scores in the decoding conditions in the

alternating treatment phase. During the best accommodation phase, Matthewâ€™s first percentage of

content words recalled increased (11.2%) compared to his performance in the last session of the

baseline phase (2.6%). With the exception of the lowest two scores (5.8 and 6.2) in the best

accommodation phase, the other data points in the phase are higher than the scores in the

baseline phase. Visual inspection of Matthewâ€™s data during the best accommodation phase with

the decoding condition revealed data ranging from 5.8% to 11.2% (Median Level = 10.2%). Data

were considered variable, as only 60% of the data points fell within 20% of the median (Gast &

Spriggs, 2010). Trend estimation using the split-method technique indicated a decreasing trend

(White & Haring, 1980).

Overall, visually there was clear data separation between the decoding condition and the

baseline phase, but there no clear data separation between the decoding + language

comprehension condition and the baseline phase.

Figure 10

Matthewâ€™s Percentage of Total Content Words Recalled (Sessions)

Figure 11

Matthewâ€™s Percentage of Total Content Words Recalled (Meetings)

Table 24

Data Analysis Summary of Matthewâ€™s Percentage of Total Content Words Recalled

Measure

Baseline

Decodinga

Decoding +
Languageb
2.9%-15.9%

No
Accommodationc
3.1%-3.3%

Best
Accommodation
5.8%-11.2%

3.5%

Range

1.8%-9.7%

11.1%-
26.2%
17.8%
Decreasing Decreasing Decreasing
Variable
Variable

Median
Trend
Stability
Note: a = decoding condition; b = decoding + language comprehension condition; c = no
accommodation condition

3.2%
None
Stable

Variable

5.6%

10.2%
Decreasing
Variable

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. Two scores in the decoding + language comprehension condition were

higher than the highest score in the baseline phase (2
5

Ã— 100 = 40%). Five scores in the

decoding condition were higher than the highest score in the baseline phase ( 5
5

Ã— 100 =

100%). Therefore, the decoding condition was chosen for the best accommodation condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled.

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. Matthew had a higher

percentage of content words recalled during the decoding condition in the treatment comparison

phase (Mdn = 17.8%) than during the baseline phase (Mdn = 2.5%). The produced median

difference (Mdn = 13.6%) was not statistically significant (p = .06). Table 25 illustrates the

results of the sign test.

Table 25

Matthewâ€™s Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
13.6
.06

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the difference scores were approximately symmetrically distributed, as assessed by a

histogram with a superimposed normal curve, a Wilcoxon signed-rank test was conducted.

Matthew had a higher percentage of content words recalled during the decoding + language

comprehension condition in the alternating treatment phase (Mdn = 5.6%) than during the

baseline phase (Mdn = 2.5%). The median difference (Mdn = 3.8%) was not statistically

significant (z = -1.76; p = .08). The effect size of treatment was calculated (z = -1.76, N = 10, r =

-.56), highlighting a large effect. Table 26 illustrates the results of the Wilcoxon signed-rank test.

Table 26

Matthewâ€™s Wilcoxon Signed-Rank Test Results for the Decoding + Language Comprehension

Condition vs. Baseline Phase

Test Statistica

Mean Difference
Z
Asymp. Sig.c (Two-Tailed)

Decoding + Language Comprehension vs.
Baseline
% of Content Words Recalledb
3.8
-1.76
.08

Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c = asymptotic
significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. Matthew had a higher

percentage of content words recalled during the best accommodation phase (Mdn = 10.2%) than

during the baseline phase (Mdn = 2.5%). The median difference produced (Mdn = 4.0%) did not

elicit a statistically significant difference (p = .06). Table 27 illustrates the results of the sign test.

Table 27

Matthewâ€™s Sign Test Results for the Best Accommodation Phase vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Best Accommodation vs. Baseline
% of Content Words Recalledb
4.0
.06

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Matthewâ€™s Overall Data Analysis Summary

Table 28 represents a data analysis summary of Matthewâ€™s Wilcoxon signed-rank test and

sign test for the percentage of content words recalled and the number of words recalled. Follow-

up analyses were conducted on the number of words recalled. As seen below, there were no

major differences in the scores Matthew obtained for the percentage of content words recalled or

the number of words recalled.

Table 28

Data Analysis Summary of Matthewâ€™s Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

Exact. Sig.a
(Two-Tailed)

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

Asymp. Sig.b (Two-
Tailed)

% of
Wordsc

# of
Wordsd

3.8

.06

13.6

Decoding vs.
Baselinee
Decoding + LC vs.
Baselinef
Best Accomm vs.
Baselineg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding vs. baseline; f = decoding + language comprehension condition vs.
baseline; g = best accommodation vs. baseline

1.00

4.03

.08

.06

.23

The primary outcome of Matthewâ€™s results indicated some disparity between the baseline

and the reading comprehension accommodation conditions. Specifically, based on the visual

analysis, there was clear data separation between the decoding condition and the baseline phase,

but there was no clear data separation between the decoding + language comprehension

condition and the baseline phase. The accommodation scores during the alternating treatment

phase displayed no difference visually when compared to the two no accommodation session

scores within that phase. Based on the PND, Matthewâ€™s best accommodation was the decoding

condition. Neither accommodation condition displayed a significant improvement over the

baseline phase. To some degree there seems to be positive effects of the decoding condition,

which supports the first hypothesis. However, minimal differences were found between the

decoding + language comprehension condition and the baseline phase, the hypothesized pattern

did not emerge for the second hypothesis.

Mary

Mary participated in a total of 22 sessions over 10 meetings with no treatment

interruptions. Mary actively participated in each session, and sessions occurred as originally

planned. Mary had one to three sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 12 represents Maryâ€™s percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 13

displays the data across meetings. The data were displayed both across sessions and across

meetings to more accurately determine whether Mary experienced any practice effects within

meetings. Table 29 represents a data analysis summary of Maryâ€™s percentage of content words

recalled for each condition during the three phases. During the baseline phase, Maryâ€™s

percentage of content words recalled ranged from 4.4% to 8.7% (Median Level = 5.0%). During

meetings two and three, Mary had a slightly increased percentage of content words recalled

during the second session. Baseline data were considered variable, as only 60% of the data points

fell within 20% of the median (Gast & Spriggs, 2010). Trend estimation using the split-middle

technique indicated a decreasing trend (White & Haring, 1980).

During the alternating treatment phase, Maryâ€™s percentage of content words recalled in

the decoding + language comprehension condition immediately increased (9.5%) compared to

her performance in the last session of baseline (5.0%). Maryâ€™s percentage of content words

recalled for the decoding + language comprehension condition during the alternating treatment

phase ranged from 8.3% to 12.1% (Median Level = 9.8%). During meeting four, Mary had a

slightly increased percentage of content words recalled during the second session. During

meeting six, Mary had a slightly decreased percentage of content words recalled during the

second session. Data were considered stable in that 80% of the data points fell within 20% of the

median (Gast & Spriggs, 2010). Using the split-middle technique, Maryâ€™s data exhibited a

decreasing trend (White & Haring, 1980).

During the alternating treatment phase, Maryâ€™s first percentage of content words recalled

in the decoding condition slightly decreased (4.4%) compared to her performance in the last

session of baseline (5.0%). Maryâ€™s percentage of content words recalled for the decoding

condition during the alternating treatment phase ranged from 4.4% to 15.7% (Median Level =

13.3%). Only the fifth meeting had two sessions of the decoding condition, and Mary had a

higher percentage of content words recalled during the second session. Data were considered

variable, as only 60% of the data points fell within 20% of the median (Gast & Spriggs, 2010).

The split-middle technique rendered an increasing trend (White & Haring, 1980).

Using the split-middle technique, Maryâ€™s data no accommodation condition exhibited no

trend (White & Haring, 1980). Visually there seems to be only a small difference between the

scores in the no accommodation condition and the two reading accommodation conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding + language comprehension condition was identified as

the best accommodation condition and used for the best accommodation phase. During the best

accommodation phase, Maryâ€™s first percentage of content words recalled decreased (7.6%)

compared to her performance in the last session of the decoding + language comprehension

condition in the alternating treatment phase (10.6%). With the exception of the highest score in

the best accommodation phase (14.7%), all the other data points in the phase overlapped with the

decoding condition in the alternating treatment phase. During the best accommodation phase,

Maryâ€™s first percentage of content words recalled increased (7.8%) compared to her performance

in the last session of the baseline phase (5.0%). With the exception of the highest score (14.7) in

the best accommodation phase, the other data points in the phase overlapped with the baseline

phase. Visual inspection of Maryâ€™s data during the best accommodation phase with the decoding

+ language comprehension condition revealed data ranging from 4.2% to 14.7% (Median Level

= 7.6%). Data were considered variable, as only 60% of the data points fell within 20% of the

median (Gast & Spriggs, 2010). Trend estimation using the split-method technique indicated a

decreasing trend (White & Haring, 1980).

Overall, visually there was no clear data separation between the reading comprehension

conditions and the baseline phrase.

Figure 12

Maryâ€™s Percentage of Total Content Words Recalled (Sessions)

Figure 13

Maryâ€™s Percentage of Total Content Words Recalled (Meetings)

Table 29

Data Analysis Summary of Maryâ€™s Percentage of Total Content Words Recalled

Measure Baseline

Decoding +
Languagea
4.4%-8.7% 8.3%-12.1%

Range

No
Accommodationc
6.5%-7.1%

Best
Accommodation
4.2%-14.7%

9.8%

5.0%

7.6%
Median
Decreasing
Trend Decreasing Decreasing
Stability Variable
Variable
Note: a = decoding + language comprehension condition; b = decoding condition; c = no
accommodation condition

6.8%
None
Stable

Stable

Decodingb

4.4%-
15.7%
13.3%
Increasing
Variable

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. Three scores in the decoding condition were higher than the highest score

in the baseline phase (3
5

Ã— 100 = 60%). Four scores in the decoding + language comprehension

condition were higher than the highest score in the baseline phase ( 4
5

Ã— 100 = 80%).

Therefore, the decoding + language comprehension condition was chosen for the best

accommodation condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled.

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the difference scores were approximately symmetrically distributed, as assessed by a

histogram with a superimposed normal curve, a Wilcoxon signed-rank test was conducted. Mary

had a higher percentage of content words recalled during the decoding + language

comprehension condition in the alternating treatment phase (Mdn = 9.8%) than during the

baseline phase (Mdn = 5.0%). The median difference produced (Mdn = 3.4%) was statistically

significant (z = -2.02; p = .04). The effect size of treatment was calculated (z = -2.02, N = 10, r =

-.64), highlighting a large effect. Table 30 illustrates the results of the Wilcoxon signed-rank test.

Table 30

Maryâ€™s Wilcoxon Signed-Rank Test Results for the Decoding + Language Comprehension

Condition vs. Baseline Phase

Test Statistica

Mean Difference
Z
Asymp. Sig.c (Two-Tailed)

Decoding + Language Comprehension vs.
Baseline
% of Words Recalledb
3.4
-2.02
.04

Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c = asymptotic
significance

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. Mary had a higher

percentage of content words recalled during the decoding condition in the treatment comparison

phase (Mdn = 13.3%) than during the baseline phase (Mdn = 5.0%). The produced median

difference (Mdn = 8.3%) was not statistically significant (p = 1.00). Table 31 illustrates the

results of the sign test.

Table 31

Maryâ€™s Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.d (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
8.3
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. Mary had a slightly higher

percentage of content words recalled during the best accommodation phase (Mdn = 7.6%) than

during the baseline phase (Mdn = 5.0%). The median difference produced (Mdn = 2.9%) did not

elicit a statistically significant difference (p = 1.00). Table 32 illustrates the results of the sign

test.

Table 32

Maryâ€™s Sign Test Results for the Best Accommodation Phase vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.c (Two-Tailed)

Best Accommodation vs Baseline
% of Content Words Recalledb
2.9
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Maryâ€™s Overall Data Analysis Summary

Table 33 represents a data analysis summary of Maryâ€™s Wilcoxon signed-rank test and

sign test for the percentage of content words recalled and the number of words recalled. Follow-

up analyses were conducted on the number of words recalled. As presented below, there was one

difference in the scores Mary obtained for the percentage of content words recalled and the

number of words recalled measures. There was a significant difference between the decoding +

language comprehension condition and the baseline phrase for the percentage of content words

recalled, but there was no significant difference for the number of words recalled.

Table 33

Data Analysis Summary of Maryâ€™s Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

Exact. Sig.a
(Two-Tailed)

Asymp. Sig.b (Two-
Tailed)

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

% of
Wordsc

# of
Wordsd

8.3

0.0

3.4

Decoding + LC vs.
Baselinee
Decoding vs. Baselinef
Best Accomm vs.
Baselineg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding + language comprehension condition vs. baseline; f = decoding vs.
baseline; g = best accommodation vs. baseline

-1.89

1.00

-11

.38

.04

.89

The primary outcome of Maryâ€™s results indicated a disparity between the baseline and the

reading comprehension accommodation conditions. Specifically, based on the visual analysis,

there was no clear data separation between the reading comprehension conditions and the

baseline phrase. The decoding + language comprehension condition scores during the alternating

treatment phase displayed a difference visually when compared to the two no accommodation

session scores within that phase. Based on the PND, Maryâ€™s best accommodation was the

decoding + language comprehension condition. The decoding + language condition displayed a

significant improvement over the baseline phase for the percentage of content words recalled.

Although differences were found between the decoding condition and the baseline phase, the

hypothesized pattern did not emerge for the first hypothesis. It looks as if the decoding +

language comprehension condition may have been more effective, which does not support the

second hypothesis.

Susan

Susan participated in a total of 22 sessions over 8 meetings with no treatment

interruptions. Susan actively participated in each session, and sessions occurred as originally

planned. Susan had one to four sessions per meeting.

Visual Analysis

Percentage of Content Words Recalled. Figure 14 represents Susanâ€™s percentage of

content words recalled across all phases of the study and displayed across sessions; Figure 15

displays the data across meetings. The data were displayed both across sessions and across

meetings to more accurately determine whether Susan experienced any practice effects within

meetings. Table 34 represents a data analysis summary of Susanâ€™s percentage of content words

recalled for each condition during the three phases. During the baseline phase, Susanâ€™s

percentage of content words recalled ranged from 4.9% to 17.9% (Median Level=6.7%). During

meetings one and two, Susan had an increased percentage of content words recalled during the

second session. Baseline data were considered variable, as only 40% of the data points fell

within the 20% of the median (Gast & Spriggs, 2010). Trend estimation using the split-middle

technique indicated an increasing trend (White & Haring, 1980).

During the alternating treatment phase, Susanâ€™s percentage of content words recalled in

the decoding + language comprehension condition decreased (3.2%) compared to her

performance in the last session of baseline (5.9%). Susanâ€™s percentage of content words recalled

for the decoding + language comprehension condition during the alternating treatment phase

ranged from 3.2% to 23.3% (Median Level = 16.4%). Only the fifth meeting had two sessions of

the decoding + language comprehension condition, and Susan had a slightly higher percentage of

content words recalled during the second session. Data were considered variable, as only 60% of

the data points fell within the 20% of the median (Gast & Spriggs, 2010). Using the split-middle

technique, Susanâ€™s data exhibited an increasing trend (White & Haring, 1980).

During the alternating treatment phase, Susanâ€™s first percentage of content words recalled

in the decoding condition slightly decreased (4.1%) compared to her performance in the last

session of baseline (5.9%). Susanâ€™s percentage of content words recalled for the decoding

condition during the alternating treatment phase ranged from 4.1% to 29.1% (Median Level =

18.9%). During the fourth and fifth meetings, Susan had a higher percentage of content words

recalled during the second session. Data were considered variable, as only 40% of the data points

fell within the 20% of the median (Gast & Spriggs, 2010). The split-middle technique rendered

an increasing trend (White & Haring, 1980).

Using the split-middle technique, Susanâ€™s data no accommodation condition exhibited an

increasing trend (White & Haring, 1980). Visually there seems to be only a small difference

between the scores in the no accommodation condition and the two reading accommodation

conditions.

Based on the percentage of non-overlapping data analysis (see associated results

presented in a later section), the decoding condition was identified as the best accommodation

condition and used for the best accommodation phase. During the best accommodation phase,

Susanâ€™s first percentage of content words recalled decreased (10.9%) compared to her

performance in the last session of the decoding condition in the alternating treatment phase

(19.5%). All the data points in the phase overlapped with the decoding condition in the

alternating treatment phase. During the best accommodation phase, Susanâ€™s first percentage of

content words recalled increased (10.9%) compared to her performance in the last session of the

baseline phase (5.9%). All the other data points in the phase overlapped with the baseline phase.

Visual inspection of Susanâ€™s data during the best accommodation phase with the decoding

condition revealed data ranging from 5.7% to 16.3% (Median Level = 12.4%). Data were

considered variable, as only 40% of the data points fell within 20% of the median (Gast &

Spriggs, 2010). Trend estimation using the split-method technique indicated a decreasing trend

(White & Haring, 1980).

Overall, visually there was no clear data separation between the reading comprehension

conditions and the baseline phrase.

Figure 14

Susanâ€™s Percentage of Total Content Words Recalled (Sessions)

Figure 15

Susanâ€™s Percentage of Total Content Words Recalled (Meetings)

Table 34

Data Analysis Summary of Susanâ€™s Percentage of Total Content Words Recalled

Measure Baseline

Decoding +
Languagea

Decodingb

No
Accommodationc

Best
Accommodation

Range

3.2%-23.3%

Median
Trend

4.9%-
17.9%
12.4%
6.7%
Decreasing
Increasing
Stability Variable
Variable
Note: a = decoding + language comprehension condition; b = decoding condition; c = no
accommodation condition

4.1%-
29.1%
18.9%
Increasing
Variable

8.5%
Increasing
Variable

16.4%
Increasing
Variable

2.4%-14.5%

5.7%-16.3%

Percentage of Non-Overlapping Data

The percentage of content words recalled measure was used to calculate the percentage of

non-overlapping data. One score in the decoding + language comprehension condition was

higher than the highest score in the baseline phase ( 1
5

Ã— 100 = 20%). Three scores in the

decoding condition were higher than the highest score in the baseline phase (3
5

Ã— 100 = 60%).

Therefore, the decoding condition was chosen for the best accommodation condition.

Wilcoxon Signed-Rank Test and Sign Test

The Wilcoxon signed-rank test and sign test were used to determine if there was a

significant difference between conditions for the percentage of content words recalled.

Decoding + Language Comprehension Condition vs. Baseline Phase. Due to the fact

that the distribution of differences was not symmetrically shaped, a sign test was conducted.

Susan had a higher percentage of content words recalled during the decoding + language

comprehension condition in the alternating treatment phase (Mdn = 16.4%) than during the

baseline phase (Mdn = 6.7%). The median difference produced (Mdn = 7.1%) was not

statistically significant (p = 1.00). Table 35 illustrates the results of the sign test.

Table 35

Susanâ€™s Sign Test Results for the Decoding + Language Comprehension Condition vs. Baseline

Phase

Test Statistica

Median Difference
Exact. Sig.d (Two-Tailed)

Decoding + Language Comprehension vs. Baseline
% of Content Words Recalledb
7.1
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Decoding Condition vs. Baseline Phase. Due to the fact that the distribution of

differences was not symmetrically shaped, a sign test was conducted. Susan had a higher

percentage of content words recalled during the decoding condition in the treatment comparison

phase (Mdn = 18.9%) than during the baseline phase (Mdn = 6.7%). The produced median

difference (Mdn = 8.9%) was not statistically significant (p = 1.00). Table 36 illustrates the

results of the sign test.

Table 36

Susanâ€™s Sign Test Results for the Decoding Condition vs. Baseline Phase

Test Statistica

Median Difference
Exact. Sig.d (Two-Tailed)

Decoding vs. Baseline
% of Content Words Recalledb
8.9
1.00

Note: a = Sign test; b = percentage of content words recalled; c = exact significance

Best Accommodation Phase vs. Baseline Phase. Due to the fact that the difference

scores were approximately symmetrically distributed, as assessed by a histogram with a

superimposed normal curve, a Wilcoxon signed-rank test was conducted. Susan had a higher

percentage of content words recalled during the best accommodation phase (Mdn = 12.4%) than

during the baseline phase (Mdn = 6.7%). The median difference (Mdn = 5.7%) did not elicit a

statistically significant difference (p = .50). The effect size of treatment was calculated (z = -.67,

N = 10, r = -.21), suggesting a small effect. Table 37 illustrates the results of the Wilcoxon

signed-rank test.

Table 37

Susanâ€™s Wilcoxon Signed-Rank Test Results for the Best Accommodation Phase vs. Baseline

Phase

Test Statistica

Mean Difference
Z
Asymp. Sig.c (Two-Tailed)

Best Accommodation vs. Baseline
% of Words Recalledb
5.7
-.67
.50

Note: a = Wilcoxon signed-rank test; b = percentage of content words recalled; c = asymptotic
significance

Susanâ€™s Overall Data Analysis Summary

Table 38 represents a data analysis summary of Susanâ€™s Wilcoxon signed-rank test and

sign test for the percentage of content words recalled and the number of words recalled.

Additional analyses were conducted on the number of words recalled. As presented below, there

were no major differences in the scores Susan obtained for the percentage of content words

recalled and the number of words recalled.

Table 38

Data Analysis Summary of Susanâ€™s Wilcoxon Signed-Rank Test and Sign Test

Test Statistic

Median Difference

% of
Wordsc

# of
Wordsd

Exact. Sig.a
(Two-Tailed)
# of
Wordsd

% of
Wordsc

Asymp. Sig.b (Two-
Tailed)

% of
Wordsc

# of
Wordsd

8.9

7.1

1.00

Decoding + LC vs.
Baselinee
Decoding vs. Baselinef
Best Accomm vs.
Baselineg
Note: a = exact significant used for the sign test; b = asymptotic significance used for the
Wilcoxon signed-rank test; c = percentage of content words recalled; d = number of words
recalled; e = decoding + language comprehension condition vs. baseline; f = decoding vs.
baseline; g = best accommodation vs. baseline

1.00

5.69

.38

.06

.50

The primary outcome of Susanâ€™s results indicated no difference between the baseline and

the reading comprehension accommodation conditions. Specifically, based on the visual

analysis, there was no clear data separation between the reading comprehension conditions and

the baseline phrase. The accommodation scores during the alternating treatment phase displayed

no difference visually when compared to the two no accommodation session scores within that

phase. Based on the PND, Susanâ€™s best accommodation condition was the decoding condition.

Neither accommodation condition displayed a significant improvement over the baseline phase.

Although slight differences were found between reading comprehension conditions and the

baseline phase, the hypothesized pattern did not emerge for either condition.

Reading Comprehension Measure Summaries

Overall, only a few of the participants displayed a statistically significant difference

between the reading accommodation condition and the baseline phase, and in only one case were

significant positive results similarly identified in the best accommodation phase. Table 39

displays a summary of the median differences and statistical significance of the percentage of

content words recalled for the Wilcoxon signed-rank test and sign test for each participant.

Table 39

Percentage of Content Words Recalled: Summary of Median Difference and Statistical

Significance

Test Statistic

James Robert

John William Matthew Mary

Susan

6.2
(p=.06)
4.9
(p=.08)
4.4
(p=1.00)

Decoding vs.
Baselinea
D+LC vs.
Baselineb
Best Accomm
vs. Baselinee

15
(p=.06)
18.3
(p=.04)*
15.7
(p=.04)*
Note: a = decoding condition vs. baseline phase; b = decoding + language comprehension
conditions vs. baseline phase; c = best accommodation phase vs. baseline phase; * p < .05,
which indicates a significant difference.

2.9
(p=1.00)
-2.1
(p=1.00)
-4.2
(p=1.00)

8.3
(p=1.00)
3.4
(p=.04)*
2.9
(p=1.00)

2.4
(p=1.00)
2.7
(p=.38)
-.07
(p=.89)

13.6
(p=.06)
3.8
(p=.08)
4.0
(p=.06)

8.9
(p=1.00)
7.1
(p=1.00)
5.7
(p=.50)

CHAPTER V: DISCUSSION

Overview of the Study

This study examined the effects of reading comprehension accommodations on the

reading comprehension of students who were considered poor decoders but demonstrated

average or above average listening comprehension. Seven participants read expository texts

across a baseline phase (i.e., with no accommodations provided), an alternating treatment phase,

and the best accommodation phase. In the alternating treatment phase, participants alternated

between receiving the decoding condition (i.e., read-aloud), the decoding + language

comprehension condition (i.e., read-aloud, vocabulary support, and comprehension monitoring),

and the no accommodation condition (i.e., reading independently). In the best accommodation

phase, the accommodation condition identified as corresponding with the strongest reading

comprehension performance was repeated to validate the effects of the corresponding

accommodation condition.

Two main findings from the current study were identified. First, none of the participants

demonstrated a statistically significant increase in reading comprehension scores corresponding

to the decoding condition. Second, two participants (i.e., John and Mary) experienced a

statistically significant increase in reading comprehension scores that corresponded with the

decoding + language comprehension condition; however, these significant benefits were

inconsistent across measures, as described below.

Reading Comprehension Accommodations

Research Question 1: To what extent does the use of the read-aloud accommodation

affect general comprehension of text-based material for participants with word decoding

difficulties? The present study revealed minor effects regarding the practical use of the decoding

100

condition, with no statistically significant difference observed between the condition and the

baseline. Based on the percentage of content words recalled measure, the visual analysis

displayed some data separation between the decoding condition and the baseline phase for only

two participants (i.e., John and Matthew). Based on the PND, the best accommodation condition

for three participants (i.e., James, Matthew, and Susan) was the decoding condition. Based on the

Wilcoxon signed-rank test and sign test results, none of the participants experienced a

statistically significant increase in reading comprehension scores corresponding to the decoding

accommodation condition. The results raise questions about the effectiveness of the read-aloud

accommodation for students with poor decoding skills. Based on past research, the results of the

current study were unexpected due to the abundance of high effect sizes that were found in

studies where students with disabilities utilized the read-aloud accommodation (Bonifacci et al.,

2022; Buzick & Stone, 2014; Ceyhan & Yildiz, 2021; Li, 2014; Schiavo et al., 2021; Sulaimon

& Schaefer, 2023). However, the current study exhibited some differences from the past studies

that found high effect sizes. Some potential explanations for the differences include the

following: the current study did not allow participants to view the passage while recalling, the

majority of participants did not utilize the option to reread parts of the passages, the participants

were only provided the read-aloud accommodation, and participants were able to decode many

words during eligibility testing and in the baseline passages. These are all discussed in the

following paragraphs.

One explanation for the limited effects identified in the current study is that participants

were not able to view the passage while responding to the comprehension prompt. A consistent

theme across multiple studies, which reported a limited impact of the read-aloud accommodation

on reading comprehension, is that participants were unable to simultaneously view the passage

101

while responding to the comprehension questions (Meyer & Bouck, 2014; Schmitt et al., 2011;

Sorrell et al., 2007). In contrast, several other studies that allowed participants to view the

passage while answering comprehension questions found that the increase in reading

comprehension scores while using the read-aloud accommodation was statistically significant

(Bonifacci et al., 2022; Sulaimon & Schaefer, 2023). Similar to past studies that found no

significant effect, the current study did not allow participants to view the passage while

answering the comprehension question, which may be one reason why only minimal effects were

found.

In the current study, while participants were instructed on how to reread parts of the

passage using the read-aloud accommodation, very few participants utilized the option. Many

researchers have reported that rereading texts improved reading comprehension (e.g., Dunlosky,

2005; Pressley & Afflernach, 1995; Walczyk et al., 2004). According to Pressley and Afflernach

(1995), successful readers enhance their comprehension of a passage by employing various

strategies, such as revisiting unclear or confusing sections during the initial reading. Although

students in the current study could have maneuvered the read-aloud accommodation in a manner

that would allow them to engage in rereading of selected text sections, doing so could be

particularly challenging. Specifically, it would take the ineffective reader several steps to reread

particular parts of a passage using the read-aloud accommodations. The reader would first need

to recognize that they do not comprehend something; then, navigate the read-aloud to the

specific section of the passage and activate it to reread the text. Therefore, the minimal gains in

the reading comprehension scores may have been due to the participants' reluctance to reread

parts of the passages.

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A second explanation for the minimal effects of the read-aloud accommodation identified

in the current study may be that the read-aloud accommodation is only particularly effective

when paired with other related supports. The current study supports the notion that some students

may benefit more from multi-component accommodations. Specifically, the decoding + language

comprehension condition, but not the decoding condition, corresponded to significant

improvements for both John and Mary. Other studies suggest additional supports may result in

different findings as well. A study by Schiavo and colleagues (2021) paired the read-aloud

accommodation with eye-tracking technology to give students more control over the speed and

help them stay focused on the passage. The eye-tracking technology, Gaze and Read it by

Yourself (GARY), moves through the text, following the readerâ€™s gaze while the text is

highlighted and read aloud. GARY monitored whether the reader looked at the words following

the highlighted text, and if not, then GARY paused the reading. Schiavo and colleagues (2021)

found that students with dyslexia scored higher on reading comprehension measures while using

the read-aloud accommodation with eye-tracking technology compared to traditional read-aloud

technology. Ceyhan and Yildiz (2021) investigated the effects of interactive read-aloud on

reading comprehension, incorporating the use of graphic organizers, scaffolding, and think-aloud

strategies. For example, while listening to a story, the teacher supported students in re-creating

images in their minds, making connections, asking questions, identifying main themes,

summarizing, checking the predictions, evaluating, and learning new vocabulary words. Ceyhan

and Yildiz (2021) found that using these techniques positively affected students' reading

comprehension. Overall, in previous studies, it was reported that students benefit from using

multi-component reading support strategies, which supports the notion that participants in the

current study may have required more support than just the read-aloud to meet their needs.

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Another reason for the lack of effects identified may be that the participants in the current

study did not have such low word decoding skills that they ultimately needed the

accommodation(s) to be able to comprehend. Although all participants had low Word Attack

scores based on the standardized test used for screening, they ultimately were able to decode

many words of the texts used during the baseline phase (i.e., without accommodation) that were

of the same difficulty as those used during the accommodated conditions. Thus, it may be the

case that readers either need much lower decoding skills to benefit from the accommodations

examined in the current study, or more difficult-to-decode passages to demonstrate the

effectiveness of the accommodation. Interestingly, one of the students who showed positive

effects (albeit only when both decoding and language comprehension support were provided)

was the one student who was in a lower grade level (i.e., Mary). It may be the case that she had

particularly low decoding skills (especially since her screening threshold was â€˜lowerâ€™ than others

given that it was based on a grade-based standard score), and that the accommodation effects

identified for her were in part due to her lower decoding skills. This would align with other

existing research highlighting how the effectiveness of the read-aloud accommodation varies by

grade level. A meta-analysis by Li (2014) reported that the effects of read-aloud

accommodations were significantly stronger for elementary school students than those in middle

school. Another meta-analysis by Buzick and Stone (2014) also found that a studentâ€™s grade

level is a significant moderator of the effects of the read-aloud accommodation. Therefore, the

lack of gains in the reading comprehension scores may have been due to the fact that participants

had enough decoding skills to read many words and that the read-aloud accommodation was

ultimately not necessary to remove a barrier to accessing new information.

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Overall, the current study raises questions about the effectiveness of the read-aloud

accommodation when provided in isolation. Moreover, although the read-aloud accommodation

in isolation may be effective for some students, it appears that merely using the standardized

score from a Word Attack subtest (as applied in the given study) may not be sufficient to identify

who will benefit accurately.

Research Question 2: To what extent does the read-aloud accommodation,

vocabulary support, and comprehension monitoring affect general comprehension of text-

based material for students with word decoding difficulties? Based on the simple view of

reading (SVR), it was anticipated that participants would experience a similar but no greater

benefit from the combination of the read-aloud accommodation, vocabulary support, and

comprehension monitoring compared to the read-aloud accommodation alone. However, for

more than half of the participants, their best accommodation condition was the decoding +

language comprehension condition.

The current study is the first to investigate the read-aloud accommodation, vocabulary

support, and comprehension monitoring as an accommodation package for participants with poor

decoding skills. The present study revealed some positive effects of the decoding + language

comprehension condition for three students. Based on the percentage of content words recalled,

the visual analysis displayed data separation between the decoding + language comprehension

condition and the baseline phase for only one participant (i.e., John). Based on the PND, the best

accommodation condition for four participants (i.e., Robert, John, William, and Mary) was the

decoding + language comprehension condition. John and Mary displayed a significant increase

in reading comprehension scores that corresponded to the decoding + language comprehension

condition.

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John was the only participant for which positive effects were evident across both the two

measures and phases (i.e., effects were evident based on data from both the alternating treatment

and best accommodation phases). Only for Johnâ€™s case is it, therefore, possible to rule out the

possibility of multitreatment interference as a reason for the gains identified; for all other cases,

the effectiveness identified may have been due to multitreatment interference (see Chapter III for

more information on this possible effect). When considering the two participants (i.e., John and

Mary) whose decoding + language comprehension condition displayed a statistically significant

effect, the one apparent difference between them and the other participants was that their

Listening Comprehension subtest scores were lower than the other participants. It may be the

case that benefits from support that integrates decoding, vocabulary, and comprehension

monitoring are more likely among those with both low decoding and low language

comprehension scores. If so, this would ultimately be aligned with the SVR, and it may simply

be the case that the threshold for determining adequate language comprehension in the current

study was not accurate. This also indicates that the threshold for language comprehension used in

this study may have been below what was necessary for the student to have sufficient language

comprehension for understanding the passages used in the study.

Findings of prior research have suggested much more consistent positive effects of these

accommodations for a variety of students (e.g., Boardman et al., 2015; Fletcher et al., 2006;

Gaskin et al., 1996; Guthrie et al., 2004; Hawkins et al., 2010). Some potential explanations for

the differences between the current study findings and past work include the following: a limited

amount of time for participants to learn vocabulary words, participants were only expected to

summarize and not engage in other related activities, and insufficient participant exposure to

technology. These are discussed in the following paragraphs.

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A limited amount of time allocated to teaching vocabulary words during the decoding +

language comprehension condition is one possible reason for the lack of gains in reading

comprehension. Each participant used the read-aloud technology to listen to the definitions of

each vocabulary word before listening to the passage. The participants also had the option to

pause the reader and go back to the vocabulary list to look at the definitions. However, very few

participants returned to the vocabulary list while listening to the passage. In past studies,

participantsâ€™ reading comprehension scores benefited from vocabulary previewing (Hawkins et

al., 2010; Koury, 1996). In their 2010 study, Hawkins and colleagues engaged in the following

for the vocabulary previewing condition. First, the researcher read the vocabulary word and

asked the participant to repeat it aloud, then the researcher provided a definition and used the

word in a sentence. Compared to Hawkinsâ€™s study (2010), the participants in the current study

received a very brief exposure to the vocabulary words and definitions. This lack of engagement

in quality teaching of the vocabulary words may have been a reason for the lack of gain in

reading comprehension scores in the current study.

Requiring participants to only summarize what they read and not engage in a more

thorough review and engagement in the material covered may be another explanation for the lack

of gains on the reading comprehension measures compared to other studies (Boardman et al.,

2015; Fletcher et al., 2006; Guthrie et al., 2004). In the current study, participants were asked to

pause and summarize what they read halfway through the passage. Many researchers have

reported that participantsâ€™ reading comprehension scores increased when the comprehension

monitoring included summarizing, developing questions, and reviewing the main idea

(Boardman et al., 2015; Fletcher et al., 2006; Guthrie et al., 2004). Compared to past studies, the

current study did not require participants to do more than summarize. It may be the case that had

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the current study involved a more thorough review than merely summarizing, more positive

effects may have been identified.

Insufficient exposure to the technology during the decoding + language comprehension

condition may be another possible reason for the lack of reading comprehension gains. Explicit

instruction was used when teaching the participants how to utilize the technology, and step-by-

step instructions were given during each session. Each participant was also given one session to

familiarize themselves and practice with the technology. However, researchers have suggested

that taking time to interact with and practice using reading technology can improve reading

comprehension outcomes (Elkind et al., 1993; Parr, 2012). Therefore, the participants may have

needed more time to familiarize themselves with the technology.

The current study was the first to investigate whether students with poor decoding skills

would benefit from the combination of the read-aloud accommodation, vocabulary support, and

comprehension monitoring. Although somewhat more evidence was identified, suggesting

positive effects of this accommodation combination compared to the corresponding evidence for

the decoding accommodation (in isolation), positive effects were again only evident for fewer

than half the participants and tended to vary based on measure and were rarely evident across

both expected phases. Much more support may be needed for many students to experience gains

from these accommodations.

Motivation. When considering the lack of positive effects overall, the dearth of rereading

and reviewing of vocabulary strategies used by participants, as well as the fact that this was a

research study in which there were no positive or negative personal consequences for studentsâ€™

comprehension of the material, it is important to note another important factor that may have

played a role in the findings: student motivation to comprehend. According to many studies, a

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readerâ€™s motivation affects their reading comprehension (Ahmadi, 2017; Grabe & Stroller, 2002;

Guthrie & Wigfield, 2000; Seymour & Walsh, 2006). Participantsâ€™ potential lack of motivation

may have been a barrier to determining if the accommodation conditions truly could affect their

reading comprehension (Gottfried et al., 2005). Overall, the measurement of comprehension may

have been compromised by limited motivation among participants during the activity.

Social Validity. In the current study, social validity (e.g., how useful students find the

accommodations (Wolf, 1978)) was not directly measured. However, looking at the number of

times participants used a feature of the accommodations when it was an option instead of a

demand may give some insight into whether they found the particular accommodations useful.

During the decoding + language comprehension condition, participants were told they had the

option to review the vocabulary definitions while reading the passage. However, only one

participant reviewed the definition of one vocabulary word. Therefore, it may be the case that the

participants in the current study did not find the vocabulary support accommodation useful.

According to a literature review by Lovett and Leja (2013), if a student does not find an

accommodation helpful, they will likely not use it if given the option. It is important to

understand students' thoughts/feelings about the accommodation(s) because some students find

accommodations distracting (Lovett & Leja, 2013), which could negatively impact their ability

to learn. Therefore, since social validity was not measured it is unknown whether students would

use these accommodations outside the context of the study and/or if they found the

accommodations distracting.

Direct and Indirect Effects Model of Reading (DIER). In the current study, there

appeared to be an overall lack of evidence to support accommodation decisions based on the

simple view of reading; as noted above, many other factors may have influenced our ability to

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detect the anticipated effects of accommodations. One recent framework that has been described

and empirically studied may be of value in future related work: The direct and indirect effects

model of reading (DIER). The DIER framework suggests a more complex view than the simple

view of reading. Specifically, the â€œDIER proposes that the following skills, abilities, and

knowledge contribute to reading development: word reading, listening comprehension, text

reading fluency, background knowledge, socio-emotions or reading affect, higher order

cognitions and regulations, vocabulary, syntactic/grammatical knowledge, phonology,

morphology, orthography, and domain general cognitions or executive function.â€ (Kim, 2020, p.

6). An important component of the DIER framework is the dynamic relations hypothesis, which

indicates that there is an interaction between an individualâ€™s reading development and the text

demands of the passage (Kim, 2020). The DIER framework, namely the dynamic relations

hypothesis, may better explain the results of the current study, such that the nature of the

passages may have played a role in the extent to which studentsâ€™ decoding and language

comprehension skills were at a sufficient level for the accommodation(s) to show effects on the

particular passages used. Even though the passages in the current study had similar reading

levels and lengths, other aspects of the passage that put more demands on the reader were not

taken into account, such as the sophistication of the vocabulary words, the location of relevant

information, and the density of the information (Kim, 2020). This may be why the majority of

participantsâ€™ scores in the current study did not demonstrate stability based on the visual analysis

of the data. In other words, different passages may have had more or less demands on the reader,

which may have contributed to the student performing worse or better on the reading

comprehension measure. Overall, the student's performance on the comprehension measures may

110

be better explained using the DIER framework because reading may be more complex than the

simple view of reading suggests.

Limitations

The interpretation of these results must be viewed in light of several limitations of the

study, which are highlighted below.

Background Knowledge. The first limitation concerns a lack of control of the

participantsâ€™ background knowledge and the corresponding impact that background knowledge

may have had on variation in reading comprehension scores. Background knowledge represents

the prior knowledge the participants had on the topics the passages described in the study and is

a critical factor that influences the comprehension of new material (Guthrie et al., 2004).

Although passages were selected to prevent background knowledge from influencing the

findings (see Chapter III on how passage topics were chosen), some passages portrayed topics

that could be considered common knowledge (i.e., Underground Railroad) compared to more

obscure ones (i.e., Colonial Architecture). The participants' background knowledge was not

assessed before administering the passages. Therefore, their reading comprehension scores may

have been influenced by their background knowledge instead of their reading comprehension

level alone.

Possible Practice Effects. The second limitation is related to possible practice effects. In

the current study, participants were asked to read multiple passages per day, which seemed to

cause a practice effect for some participants. A practice effect occurs when participants have

become familiar with some aspects of the experiment from engaging in multiple measurement

occasions in a short period of time. As a result of this effect, participants may have performed

worse in the first session compared to the second session. Therefore, their reading

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comprehension scores may have been influenced by how comfortable the participants were with

the materials instead of solely the reading comprehension accommodation conditions. Moreover,

the possibility of practice effects becomes even more apparent when examining data for the

comparison conditions. More specifically, during the alternating treatment phase, when

examining the two no accommodation conditions during the alternating treatment phase, four out

of the seven participants displayed at least one no accommodation condition that was visually

higher than the highest score during their baseline phase. For example, John demonstrated a

significant increase between the decoding + language comprehension condition and the baseline

phase for the percentage of content words recalled measure. For this measure, John also showed

a visual increase in his reading comprehension score during the second no accommodation

condition compared to his highest score during his baseline phase. This begs the question of

whether John's reading comprehension scores were due to implementing the decoding +

language comprehension condition or simply learning how to respond to the prompts more

effectively over time.

Reading Comprehension Measures. The third limitation is related to the technical

adequacy of the reading comprehension measures. Recall measures (which were the type of

reading comprehension measures applied in the current study) have been criticized for lack of

technical adequacy in prior work (Keenan et al., 2008; Reed & Vaugn, 2012). For example,

according to a study by Carlisle (1999) students without disabilities perform better on recall tasks

compared to students with learning disabilities. Also, the recall measure is dependent on the

studentâ€™s verbal language abilities (Johnston, 1981). Therefore, the recall measures used in the

current study may not have accurately measured reading comprehension.

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Moreover, although some evidence of technical adequacy is available for the scores used

in this study (i.e., â€œnumber of words recalledâ€ and â€œpercentage of content words recalledâ€) when

applied using similar passages, technical adequacy for the scores when applied to the specific

passages used in this study was not available. A pilot study was conducted on a few of the

passages to examine whether the passage selection criteria that were applied corresponded to

passages that showed a basic level of reliability. However, only four students were in the pilot

study, and they only read five passages. Therefore, it is unknown whether the technical adequacy

of the reading comprehension measures was solid.

Study Eligibility Testing. The fourth limitation is relevant to the eligibility testing for

the current study. Eligibility testing for the study was conducted virtually due to the COVID-19

pandemic. Initial research has suggested no significant difference between scores acquired in-

person and virtually on cognitive and achievement assessments (Hamner et al., 2021; Wright,

2020). However, during in-person administration, the researcher can have more control over the

environment compared to virtual administration. For example, a few participants got distracted

during testing due to activities going on in their homes and/or just by being on a computer.

Therefore, it is a possibility that some participants did worse than they would have if tested in

person, which may have caused some participants to meet the SVR criteria when they typically

would not have.

Another limitation of the eligibility testing was whether students were accurately

identified as fitting the category of a â€œpoor decoderâ€ according to the SVR. Although the criteria

used were similar to other studies that categorized students according to the SVR (e.g., Catts et

al., 2006; Giusto & Ehri, 2019), cut scores and metrics for measuring decoding and language

113

comprehension of the SVR are highly variable (Fletcher et al., 2018). Therefore, without having

more uniform criteria for the SVR, participants may not have been categorized correctly.

Implications for Future Research

Findings from the current study offer some potentially helpful directions for future

research discussed in this section.

Simple View of Reading. The current study examined the effects of accommodations for

students who fall into just one of the four types of readers according to the SVR: the poor

decoding group. As discussed, it was found that few displayed clear benefits of the decoding

condition, which does not align with the SVR. Along with potentially exploring alternative

thresholds for assigning students to SVR groups, it may be helpful to also study the other groups

in the SVR to develop a stronger understanding of whether the SVR may be an efficient and

accurate way to assign accommodations to other reading groups.

Intensive Accommodation Supports. Based on the results of the current study, more

evidence of positive effects was found for the larger accommodation package (i.e., the decoding

+ language comprehension condition) compared to the read-aloud accommodation alone. This

may suggest that more intensive accommodation supports are ultimately needed for more

students to benefit. Relatedly, it could be helpful for researchers to explore whether multi-

component reading support strategies (i.e., combining the read-aloud with eye-tracking

technology and combining the read-aloud with instruction on using a graphic organizer) are more

beneficial for students with poor decoding skills. Future research should study an adapted read-

aloud accommodation that more easily facilitates rereading or adapt the current study to include

a requirement that the participants complete two readings of each passage prior to measuring

their recall. In the current study, the vocabulary support accommodation was utilized. As stated

114

above, in past studies, it was reported that a more comprehensive vocabulary previewing

procedure resulted in higher reading comprehension scores (Hawkins et al., 2010; Gaskins et al.,

1996). Therefore, replicating parts of the current study and including a more comprehension

previewing of vocabulary words may result in an increase in reading comprehension scores.

Participants in the current study also utilized the comprehension monitoring tool. As previously

discussed, in past studies, it was reported that when a reader summarized, developed questions,

and reviewed main ideas, the reader had stronger reading comprehension scores (Boardman et

al., 2015; Fletcher et al., 2006; Guthrie et al., 2004). Therefore, it may also be beneficial to

investigate whether utilizing different comprehension monitoring skills (e.g., summarizing,

developing questions, reviewing the main idea, etc.) affects reading comprehension. Overall,

future research that examines more comprehension accommodation supports may show stronger

effects.

Accommodation and/or Instruction. In the current study, participants were provided

several supports, but overall, it was questionable whether the supports were effective. According

to Cavanaugh (2002), reading accommodations can be appropriate to help students access the

curriculum, but it is important not to rely solely on the accommodations. King-Sears and

Bowman-Kruhm (2010) stated that accommodations do not replace specialized reading

instruction. Thompson and colleagues (2004) suggest that students with learning disabilities may

benefit from the combination of direct instruction in reading comprehension strategies and

reading accommodations. By combining the two approaches, students may develop stronger

reading comprehension skills while aiding them to meet grade-level requirements that do not

require decoding (Thompson et al., 2004). Therefore, researchers should investigate which

approach, accommodations alone, high-quality comprehension instruction/ decoding instruction,

115

or a combination of accommodation and high-quality instruction results in better long-term

effects for students with poor decoding skills.

Student Level Predictors. In the current study, a few participants did benefit from the

reading comprehension accommodation(s), so it would be helpful to investigate other possible

student-level predictors of those who benefited. For example, researchers should measure

participants' comfort level, knowledge, and ease of technology use as possible predictors of

benefit. As previously stated, one potential reason the current study found few significant results

may be due to the threshold used to determine whether participants were eligible for the study; a

careful review of results suggested that those with lower skills may be more likely to benefit.

Research that examines accommodation effects for large numbers of students representing a

wide range of decoding skill levels may be helpful in determining if there is a particular

threshold that can help identify who will benefit from a read-aloud accommodation. In the

current study, very few participants utilized the rereading or review vocabulary options, which

may be indicators that they had low motivation. The current study did not measure motivation or

interest, but it would be beneficial for future studies to examine whether higher motivation

results in more use of accommodation(s) and, therefore, results in higher comprehension scores.

Implications for Practice

Results from the current study hold several implications for practice, which are

highlighted below.

The results of this study beg the question of whether providing a read-aloud

accommodation will be helpful for many students; it is critical for teachers to avoid assumptions

that an accommodation will necessarily increase the comprehension of material among all

students to whom it is provided. The results of the current study support the notion that reading

116

accommodations may have different effects for different students and that it remains difficult to

predict who will benefit. One tool developed in the past to help facilitate related predictions (i.e.,

the Dynamic Assessment of Test Accommodations (DATA; Fuchs et al., 2000b), was indeed

found to be better than teacher recommendations at predicting benefits from accommodations;

however, it is no longer available for purchase, likely due to the excessive time necessary for

administration and corresponding questions about the value added of administration. As

discussed in Chapter II, it was thought that the SVR could be a more cost and time-efficient way

to identify which students would benefit from certain accommodations, but such was not found.

Therefore, until more information is available about the student-level predictors associated with

accommodation benefits, it may be best to return to a DATA-type approach if one wants to better

determine whether a student will benefit. Such involves repeated testing of a student under

accommodated and non-accommodated conditions to examine the extent of benefit.

Although accommodations may help some students, it is also important to emphasize that

they may not be a particularly fruitful and ideal solution for addressing the reading-related

barriers that many students experience during instruction and learning. To date, considerable

literature highlights how many reading difficulties could be prevented or addressed through the

provision of high-quality reading instruction and intervention (Archer & Hughes, 2011; Carnine

et al., 2004; Coyne et al., 2006; Daly et al., 2005; McCormick, 2003; Rupley et al., 2009). An

emphasis on ensuring high-quality reading instruction and intervention is in place should

ultimately be emphasized for those who are considered to need accommodations. Indeed, past

literature has found that combining accommodations with reading comprehension

interventions/strategies improves understanding of an expository text (Roberts et al., 2012), and

practitioners are correspondingly encouraged to ensure any student who is provided a reading

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accommodation should similarly be receiving quality reading instruction and intervention such

that the accommodation may not be needed in the future.

Conclusion

Reading comprehension accommodations are one tool students might use to gain access

to and understanding of written material. Overall, upon visual inspection of the descriptive data,

the results of the current study demonstrated little to no separation between the reading

comprehension conditions and the baseline phase, which indicates that the study did not show

effectiveness of the reading comprehension accommodations for the participants. The results of

the current study also highlight that it remains difficult to predict which students benefit from

accommodations and the conditions under which they benefit from them. Although some benefit,

additional research may be helpful to identify the characteristics of those who do, as well as the

specific accommodation features necessary to promote access. Without clear guidance about who

will benefit, practitioners are encouraged to engage in close monitoring of student performance

with and without accommodations to gauge the conditions under which they are helpful.

118

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APPENDIX A: Procedure for Guardians to use before Every Session

1. Start setting up about 5 minutes before the meeting time.
2. Make sure the computer is set up in a quiet place where distractions are minimal, the wifi

has a strong signal and your child will be comfortable.

3. If your child prefers, they can wear headphones. If they do want to wear headphones,

please have them set up before the meeting.

4. Click on the zoom link from my original email and type in the password.
5. Make sure to join with audio and video

131

APPENDIX B: Example Passage

Black Americans in the Civil War

While many people loyal to the Union lived in the South, no group was more supportive

of the Union than African Americans. They not only served as spies, providing information on

plans and troop movements, but they also fought for the freedom they earnestly desired.

Harriet Tubman, one of the leaders of the Underground Railroad, was also a spy during

the Civil War. In 1863, she began taking short trips to the Confederate states to spy on enemy

forces. One time she led a Union force of 150 men up the Combahee River in South Carolina

where they surprised a Confederate camp. They destroyed a huge cache of supplies and brought

out 750 slaves.

When the Civil War started, there was a rush of black men who wanted to sign up to

fight. At first, they turned away. Lincoln did not want to alienate the border states more than

necessary. Many white soldiers did not think blacks could fight well. In May 1863 the

Government established the Bureau of Colored Troops. Once they were deployed on the

battlefield, black soldiers proved their courage over and over again.

Not everything was rosy for the black soldiers, however. They were paid less than white

soldiers, their weapons were often in poor shape, and other supplies were of lower quality. Many

struggled for equal pay, refusing their pay for months until Congress gave it to them in June

1864.

While only ten percent of the whole Union army was black, their losses were high. As

many as one-third died. Still, their bravery and courage under fire were proven by the 16 Medals

of Honor that were awarded. Few records of the deeds of black Americans have survived. Some

were lost, while others were purposely destroyed. Even so, enough information remains to show

us their valuable contribution.

132

APPENDIX C: Procedure for How Vocabulary Words Were Chosen

1. https://readabilityformulas.com/free-readability-formula-tests.php
2. Show word statistics
3. Show all unique and hard words
4. Delete duplicates
5. Delete proper nouns
6. Delete words defined in passage
7. Compare words left to the vocabulary lists from grades 4-7

a. https://docs.google.com/spreadsheets/d/1DDQ4mfkLV_guepo7m6ALIzUTr_HR

U54KKG_edlrNfEA/edit?usp=sharing
8. The words found on the higher grade levels will be defined
9. Ten words will be chosen
10. The following website was used to define the words
a. https://kids.wordsmyth.net/we/?ent=activites

133

APPENDIX D: Procedure for How to Create the Content Words List

â— Make contractions into two words
o Wonâ€™t = will not
o Isnâ€™t = is not

â— Remove sounds

o Um, oh, ah,

â— Copy and paste transcribed recall into the online automatic parts of speech checker

(https://parts-of-speech.info/).

â— Use the results to make a list including all the proper nouns, common nouns, verbs,

adjectives, adverbs, and numbers based on the online automatic parts of speech checker
results.

o Delete all words that are not highlighted
o Copy and paste list into excel sheet

â— Working on the list of words

o Delete duplicates â€“ including different tenses

â–ª For example, if the passage has the words â€œisâ€ and â€œare,â€ then one will be

deleted

o Split up proper nouns

â–ª For example, United States will be worth two points

o Include numbers

â–ª Each digit is worth one point (The number 438 is worth four points = four,

hundred, thirty, eight)
o Put list in alphabetical order

134

APPENDIX E: Flyer for Study

Figure 16

Flyer for the Study

135

APPENDIX F: Administering Computerized Assessments

136

137

138

139

APPENDIX G: Reading Background Questions

1. Does your child struggle in reading? Yes or no

2. If so, do you know what they struggle with while reading (i.e., sounding out words,

understanding what they read, limited vocabulary, etc.)

140

APPENDIX H: Scripted Protocols for Introduction and No Accommodation

Introduction and No Accommodation

1. Start recording the meeting
a. Share pleasantries

2. Hello ____.
3. I am Jessica and I am a graduate student at Michigan State University
4. We are going to be working together over the next several weeks.
5. In this study, I am going to be looking at if different technology tools help you

comprehend what you read.

6. When we meet you will be asked to read one or more passages
7. Starting out you will silently read the passages. After a couple of weeks, I will

introduce you to technology that may support your reading, to see if they affect your
reading comprehension.

8. Some of these passages may be hard for you to read, but all I ask is that you do your

best.

9. Just so you know, I will be recording our meeting so I can go back and listen to your
answers. Only me and a few people working on this project will see these videos.

10. If you need to take a break let me know. You can take a break before or after

reading a passage but not while reading.

a. If the student does ask for a break while reading a passage say, â€œIf it is an

emergency we can stop, but please try to finish reading the passage, and then you
can take a break.â€

11. Remember nothing we do here will affect your grades. Also, anything you tell me is
strictly between me and you. Unless you tell me that you are hurting someone or
someone is hurting you, then I will need to tell someone.

Let me demonstrate one of these passages:

12. If at any time you canâ€™t hear me, my audio is breaking up and/or a video lag, please

let me know!

a. See cheat sheet for what to do

13. As I said, youâ€™re going to start by reading the passages silently and at the end I will

ask you to tell me all about what you read.

14. All of the passages you will be reading are about social studies.
15. This passage is titled The Study of the Past

a. Share practice passage tab with the student

16. Are you able to see the passage titled The Study of the Past?

a. If the student cannot see the passage:

i. Make sure you are sharing your screen and the shared screen is correct.
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen.

17. When I demonstrate I will read the paragraph aloud but when it is your turn you

will read silently.

141

18. I will now demonstrate.

a. Read paragraph
b. The people of the ancient world didn't build skyscrapers, invent the

automobile, or send spaceships to Mars. But they did remarkable things.
Among their amazing feats were building huge temples, inventing writing,
and discovering planets. Every step we take in technology, science, education,
literature, and all other fields builds on what people did long ago. We are
who we are because of what people did in the past.

19. When it is your turn, you will tell me you are done and I will stop sharing my screen

and ask you to tell me all about what you just read.

20. I will now demonstrate recalling what I just read
a. Demonstrate recalling the paragraph
b. There were people who lived a long time ago and it was called the ancient
world. They didnâ€™t invent things like cars or spaceships but they did some
really cool things. They did build temples, invented writing, and saw planets.
Every new discovery is based on what people did a long time ago.

21. Now it is your turn.
22. But first, you will take control of the mouse so you can scroll the passage while

reading.

a. Give the student access to the mouse

i. If the student has trouble taking control of the mouse or trouble scrolling
say, â€œclick on the zoom window and try again.â€ If that doesnâ€™t help, make
sure on zoom you have clicked on â€˜remote controlâ€™, and have given mouse
control to the student.

23. You should now see a message on your screen asking if you want access to the

mouse. After the message goes away, click on the zoom window (or the screen I am
sharing with you) to control the mouse.

a. Walk the adult/student through this as they are following the steps.

24. Please try to scroll. Great!

a. If the student has trouble scrolling, ask the student/adult to try moving the

pictures so the student can see the scroll bar on the right-hand side of the screen.

i. To move the pictures, just click and drag

25. Now, I want you to practice reading and recalling the following paragraph.
26. While reading the paragraph, if you see a word you donâ€™t know, just try your best.
Also, when you are telling me all about what you read, I cannot help you or tell you
if you are correct. Please just try your best.

27. Please read the paragraph silently and tell me when you are done reading.

a. Answer any of the technology questions the student asks pertaining to the study
b. If the student asks how to pronounce a word or a definition of a word, say, â€œjust

try your best.â€

c. If the student is still reading after about 3 minutes, say, â€œremember to tell me

when you are done reading.â€

d. If the student is still reading after about 5 minutes, say, â€œthat is a really hard

paragraph, letâ€™s try a different one.â€

i. Scroll down and there are several different paragraphs the student can

practice with.

142

e. Wait for the student to say they are done reading.

28. Stop sharing screen
29. Now that you have read about The Study of the Past, please tell me all about what

you just read. Try to tell me everything you can. Begin.

a. Listen to the recall and do not provide corrective feedback.
b. If the student asks if they forgot anything from the passage, or along those lines,

say, â€œjust try your best.â€

30. Great job!
31. Do you feel comfortable with the recall passage and ready to do more on your own,

or would you like to practice some more with me demonstrating first?

a. If the student says no or pauses for several sections say, â€œyou can practice some

more if you want.â€

b. Practice recalling paragraphs until the student reports they feel comfortable

i. Scroll down and there are several different paragraphs the student can

32. Any questions so far?

practice with.

a. Answer any questions the student has about the study.

33. If there are technical difficulties during a passage we will stop that passage and
begin a new one. If during a practice passage we may have to wait until the next
session to practice.

a. See cheat sheet.

34. If at any time you cannot hear me please use the chat feature to tell me.

a. Verbally tell the student where to find the chat and how to send a chat message.
b. Have the student do the steps as you explain

35. Great! Letâ€™s get started with reading the full recall passages

Steps for Introduction for Recall
1. Practice recall passage displayed on the computer
2. Researcher provided the correct directions
3. Researcher demonstrate how to read and recall the paragraph
4. Recall questions asked AFTER child indicates they are finished
5. Researcher stop sharing the passage screen BEFORE recall question
6. Researcher refrained from providing corrective feedback to reading

and recalling the passage

7. Student practiced recall passage and indicated they feel comfortable

Yes

Total ____/7 _____/7

143

APPENDIX I: Scripted Protocols for No Accommodation

No Accommodation

1. Reference the studentâ€™s passage schedule and pull up the correct passage on the

computer.

2. Do not share the screen with the student until all directions have been given
3. While reading the passage, if you see a word you donâ€™t know, just try your best.

Also, when you are telling me all about what you read, I cannot help you or tell you
if you are correct. Please just try your best.

4. Please read the passage silently and tell me when you are done reading.
5. This passage is titled ________

a. Share the passage tab with the student and give them access to the mouse

6. Are you able to see the passage titled ______?

a. If the student cannot see the passage:

i. Make sure you are sharing your screen and the shared screen is correct
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen.

7. Remember to click on the screen to access the mouse and tell me when you are done

reading.

a. Answer any of the technology questions the student asks pertaining to the study
b. If the student asks how to pronounce a word or a definition of a word, say, â€œjust

try your best.â€

c. If there are significant technical difficulties, ask the student to stop reading, fix

the technology issues, and start a new passage.

i. Use a backup passage

d. If the student is still reading after about 5 minutes, say, â€œremember to tell me

when you are done reading.â€

e. If the student is still reading after about 10 minutes, say, â€œthat is a really hard

passage, letâ€™s try a different one.â€
use a backup passage

f. Wait for the student to say they are done reading

8. Stop sharing screen
9. Now that you have read about _______ (title of the passage), please tell me all about

what you just read. Try to tell me everything you can. Begin

a. Listen to the recall and do not provide corrective feedback
b. If the student asks if they forgot anything from the passage, or along those lines,

say, â€œjust try your best.â€

10. Thank you for working so hard on this passage!
11. Now you are going to read another passage.

144

Steps for No Accommodation
1. Reference the studentâ€™s passage schedule and pull up the correct

Yes

passage on the computer steps

2. Passage provided AFTER all directions provided
3. Researcher provided the correct directions
4. Student read the passage silently
5. Recall questions asked AFTER child indicates they are finished
6. Researcher stop sharing the passage screen BEFORE recall question
7. Researcher refrained from providing corrective feedback to reading

and recalling the passage

Total ____/7 _____/7

145

APPENDIX J: Scripted Protocols for Pre-Training

Pre-training

Now we are going to learn how to use the technology reading tools.

Read-Aloud Practice

1. The first tool I will teach you is the read-aloud. With the read-aloud, you will hear
the computer reading the passage out loud and you will listen. This may make it
easier for you to understand what is written in the passage since you donâ€™t have to
read it on your own.

a. Bring up the read-aloud practice recall passage on the computer screen.
b. Open Natural Reader (see cheat sheet)

2. This passage is titled ________

a. Share the practice passage tab with the student

3. Are you able to see the passage titled ______?

a. If the student cannot see the passage

i. Make sure you are sharing your screen and the shared screen is correct
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen

4. You may have seen many different types of read-aloud accommodations. For this

study, Natural Reader is used.

5. Look at the top right hand side of the document and you will see a blue play button.

You will practice using this a little later.

a. Use your mouse to show the student where the play button is.

6. An important aspect of the read-aloud is choosing a voice and speed you feel

comfortable with. I will play you a few options and you will tell me which one you
like best.

a. To choose voice:

i. Click settings
ii. Click â€œPlusâ€
iii. Click each US name and then the play button next to the blue dot
iv. After playing 3 ask the student to choose which of the three they like best.
v. After all 8 have been played, use the 3 names they liked the best and play
the first three sentences of the passage and then ask the student to choose
the name they like the best.

b. To choose a speed:

i. Use the voice the student chose
ii. Click on like next to â€œSpeedâ€
iii.
iv.
v. After you have 2 numbers, play the two speeds for the student again and

Start at 0 and the play button next to their chosen voice
Preview -1 to +1, after three speeds ask which one they prefer.

have them choose one

7. If while listening to this practice passage you realize you do not like the voice or

speed, please let me know and we can change them.

8. Now, I will show you how to use the read-aloud.

146

a. First I will click the play button.
b. You can see how it highlights the sentence it is reading.
c. If I press the pause button and then the play button. The read-aloud starts

from the beginning of the sentence.

d. If you need to skip around you can click the forward or rewind arrows, look
next to the play button. You can only do this if the read-aloud is playing.

e. You will need to scroll down as the read-aloud reads the passage.

i. Demonstrate while explaining.

9. Now, you will practice using the read-aloud. Remember to click on the zoom

window. Move the mouse around to make sure you have control.

a. Give the student access to the mouse
b. If the student does not attempt, tell them the action again. If still no action, ask

them if they need help.

c. If the student struggles using the mouse, ask if there is a different type of mouse
they can use (i.e., instead of using the pad, using an external mouse). You can
also ask their guardian to come back in the room to help

10. First I just want you to play around using the read-aloud in the document, starting
in the second paragraph. Tell me when you feel comfortable with the read-aloud.
a. Give the student a few minutes to just familiarize themselves with the tool

11. Great now, pause the read-aloud for me.

a. Press play again
b. Press the rewind arrow and then the forward arrow
c. Then pause
d. If the student struggles with any of these commands, provide support.

12. Wonderful!

a. Open the next practice passage

13. Now I want you to try to listen to the next paragraph by yourself. Let me open the

document before you begin. Okay, go ahead.
a. Have the student practice independently.

14. Do you have any questions about the read-aloud?
a. Answer studentâ€™s questions about read-aloud

15. Do you feel comfortable with the read-aloud and ready to do more on your own, or

would you like to practice some more with me demonstrating first?

a. If the student says no or pauses for several sections say, â€œyou can practice some

more if you want

b. Practice using the read-aloud until the student reports they feel comfortable.
c. Scroll down and there are several different paragraphs the student can practice

with.

16. Great!
17. I just want to double check you are okay using this is the voice and speed when we

meet.

18. Now let me show you how to use the vocabulary tool.

147

Vocabulary Practice

1. The second tool I will teach you is the vocabulary tool. This can be helpful because it
tells you the definition of words that you may not know the meaning of. Knowing
the definition of difficult words may help you comprehend the passage better.
a. Bring up the vocabulary practice recall passage on the computer screen.
b. Make sure the correct voice and speed is selected for the student

2. For this passage you will use the read-aloud again.
3. This passage is titled ________

a. Share the practice passage tab with the student

4. Are you able to see the passage titled ______?

a. If the student cannot see the passage:

i. Make sure you are sharing your screen and the shared screen is correct.
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen

5. Under the title of the passage, you will see the word â€œVocabularyâ€ that is blue and

underlined. To get to the vocabulary words you first need to right-click on the word
â€œvocabularyâ€ and then â€œopen link.â€
a. Demonstrate with explaining

6. When you open the new tab you will see the list of vocabulary words and definitions.

You will use the read-aloud to listen to the definitions

i. Demonstrate

7. After you are done listening to the definitions, you will go back to the passage tab

and listening to the passage.

a. Demonstrate while explaining.
b. You can see the vocabulary words are in blue.
c. Read the paragraph outload pointing out the blue words.

8. Now you try, in the next paragraph.
9. Remember you need to click on the zoom window. Then right-click on the word

vocabulary in blue word and then the title of the document.

a. Give the student access to the mouse
b. Have the student practice independently.
c. If the student needs help getting to the vocabulary list, provide support.
10. Great! Now that the vocabulary list is open please use the read-aloud to listen to the

definitions

a. Wait for the student to read/listen to the definitions

11. Now that you are done reading all the definitions you can go back to the passage tab

and listen to the paragraph.

a. Have student read to the second paragraph.
12. Do you have any questions about the vocabulary tool?
a. Answer studentâ€™s questions about vocabulary tool

13. Do you feel comfortable with the vocabulary tool and ready to do more on your own

later, or would you like to practice some more or have me demonstrate more?

a. If the student says no or pauses for several sections say, â€œyou can practice some

more if you want.

b. Practice using the vocabulary tool until the student reports they feel comfortable.

148

c. Scroll down and there are several different paragraphs the student can practice

with.

14. Great!
15. Now let me show you how to use the summarizing tool.

Comprehension Monitoring Practice

1. The final tool I will teach you is the summarizing tool. This can be helpful because it
provides you time to reflect on what you have read. Reflecting on what you have
read may help you comprehend the passage better.

a. Bring up the summarizing practice recall passage on the computer screen
b. Make sure the correct voice and speed is selected for the student

2. This passage is titled ________

a. Share the practice passage tab with the student

3. Are you able to see the passage titled ______?

a. If the student cannot see the passage:

i. Make sure you are sharing your screen and the shared screen is correct.
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen

4. While you are reading the passage you will see a pause sign (show the pause sign to

student). When you get to the pause sign stop reading and tell me in your own words
what you read.

5. For this passage we use the read-aloud.
6. I will listen to the first paragraph.

a. use the reader for the first paragraph.

7. When I get to the pause (hover the clicker on the first pause sign in the document) sign

I might say something like,

a. See how I summarized in my own words and I didnâ€™t read the passage again.
Instead of just reading the passage aloud, I took some main ideas and said it
in my own words.

8. Now you try. First, read the paragraph using the read-aloud. when you get to the
pause sign, pause the reader and tell me in your own words what you have read.

a. Give the student access to the mouse
b. Have the student practice independently.
c. Remind them to use the forward arrow until they get to the beginning of the next

paragraph.

9. Do you have any questions about the summarizing tool?

a. Answer studentâ€™s questions about the summarizing tool.

10. Do you feel comfortable with the summarizing tool and ready to do more on your

own later, or would you like to practice some more or have me demonstrate more?
a. If the student says no or pauses for several sections say, â€œyou can practice some

more if you want

b. Practice using the summarizing tool until the student reports they feel

comfortable.

c. Scroll down and there is an extra paragraph for the student to read. If they need

another one they can read the first paragraph.

11. Great!

149

Yes

Steps for Accommodation Use Practice
Read-Aloud
1. Researcher explained how to use the RA
2. The researcher demonstrated the RA
3. The researcher and student practiced using the RA together
4. Researcher provided the correct directions
Vocabulary
5. Researcher explained how to use the vocabulary
6. The researcher demonstrated the vocabulary
7. The researcher and student practiced using the vocabulary together
8. Researcher provided the correct directions
Comprehension Monitoring
9. Researcher explained how to use the comp monitoring
10. The researcher demonstrated the comp monitoring
11. The researcher and student practiced using the comp monitoring

together

12. Researcher provided the correct directions

Total ____/12 _____/12

150

APPENDIX K: Scripted Protocols for Decoding

Decoding

1. Reference the studentâ€™s passage schedule and pull up the correct passage on the

computer.

2. Do not share the screen with the student until all directions have been given
3. Make sure the correct voice and speed is selected for the student.
4. You will use the read-aloud tool to listen to the passage. For our session today, it is
important that you use the read-aloud for the entire passage, even if you do not
think it helpful. If you donâ€™t use it then we will have to stop and start a new passage.
5. After listening to the passage, I will ask you to tell me all about what you just read.
6. This passage is titled ________

a. Share the passage tab with the student and give them access to the mouse

7. Are you able to see the passage titled ______?

a. If the student cannot see the passage:

i. Make sure you are sharing your screen and the shared screen is correct.
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen.

8. Remember to click on the screen to access the mouse.
9. Press the play button at top of the screen and tell me when you are done listening.
a. Answer any of the technology questions the student asks pertaining to the study
b. If the student does not listen to the whole passage using the read-aloud, remind

the student to use the tool to listen to the whole passage.

c. If the student asks for help using the read-aloud say, â€œpress play and then click on

the passage where you want the reader to start.â€
d. Wait for the student to say they are done reading

10. Stop sharing the screen.
11. Now that you have read about _______ (title of the passage), please tell me all about

what you just read. Try to tell me everything you can. Begin.

a. Listen to the recall and do not provide corrective feedback.
b. If the student asks if they forgot anything from the passage, or along those lines,

say, â€œjust try your best.â€

12. Thank you for working so hard on this passage!

151

Steps for Decoding Recall
1. Reference the studentâ€™s passage schedule and pull up the correct

Yes

passage on the computer steps

2. The correct voice and speed are selected
3. Directions were given step-by-step
4. Researcher provided the correct directions
5. Student had the reader read all the words in the passage
6. Recall questions asked AFTER child indicates they are finished
7. Researcher stop sharing the passage screen BEFORE recall question
8. Researcher refrained from providing corrective feedback to reading

and recalling the passage

Total ____/8 _____/8

152

APPENDIX L: Scripted Protocols for Decoding + Language Comprehension

Decoding + Language Comprehension

1. Reference the studentâ€™s passage schedule and pull up the correct passage on the

computer.

2. Do not share the screen with the student until all directions have been given
3. Make sure the correct voice and speed is selected for the student
4. You will use the vocabulary, read-aloud, and summarizing tools. For our session

today, it is important that you use all three tools for the entire passage, even if you
do not find them helpful. If you donâ€™t use them then we will have to stop and start a
new passage.

5. After listening to the passage, I will ask you to tell me all about what you just read
6. This passage is titled ________

a. Share the passage tab with the student and give them access to the mouse.

7. Are you able to see the passage titled ______?

a. If the student cannot see the passage:

i. Make sure you are sharing your screen and the shared screen is correct.
ii. Make sure the student has the zoom window showing on their screen by

asking what they see on their screen.

8. Remember to click on the zoom window to access the mouse.
9. To open the vocabulary list right click on the word vocabulary and then open link.

a. Wait for vocabulary list to be open

10. Now, open the reader by clicking on the blue N and then the play button. Remember

to listen to all of the definitions.

a. Wait for the student to listen to all the definitions

11. Now that you are done listening, go back to the passage page, press the blue N in the
corner and then play button to start listening to the passage. If while listening to the
passage you canâ€™t remember a definition, you can go back to the vocabulary tab.

12. Tell me when you get to the pause sign and pause the reader.

a. Wait for student to tell you they are at the pause sign

13. Tell me in your own words what you have listened to. Tell me when you are done

summarizing.

a. Wait for student to say they are done summarizing.

14. Great! Press the play button and continue listening to the passage, if you canâ€™t

remember a definition you can go back to the vocabulary tab.

15. Tell me when you are done listening to the passage.

a. Answer any of the technology questions the student asks pertaining to the study
b. If the student does not listen to the whole passage using the read-aloud, remind

the student to use the tool to listen to the whole passage.

c. If the student asks for help using the read-aloud say, â€œpress play and then click on

the passage where you want the reader to start.â€

d. If the student asks for help using the vocabulary tool say, â€œclick on the word

â€œvocabularyâ€ in blue, then the preview icon, and then the arrow in the top right
corner.â€

153

e. If the student does not click on the â€œvocabularyâ€ or does open the list but

switches back to the passage too quickly, the researcher will remind the student
that it is beneficial to double-check their knowledge by reading the definitions,
even if they already know the meaning of the word.

f. If a student skips a comprehension reflection, the researcher will prompt the

student to go back and complete the reflection.

g. If the student asks for help using the comprehension monitoring tool say, â€œwhen

you see the pause sign, tell me in your own words what you have read.â€

h. Wait for the student to say they are done reading.

16. Stop sharing the screen.
17. Now that you have read about _______ (title of the passage), please tell me all about

what you just read. Try to tell me everything you can. Begin.

a. Listen to the recall and do not provide corrective feedback.
b. If the student asks if they forgot anything from the passage, or along those lines,

say, â€œjust try your best.â€.

18. Thank you for working so hard on this passage!

Steps for Decoding + Language Comprehension Recall
1. Reference the studentâ€™s passage schedule and pull up the correct

Yes

passage on the computer steps

2. The correct voice and speed are selected
3. Directions were provided step-by-step
4. Researcher provided the correct directions
5. Student had the reader read all the words in the passage
6. Student opened the vocabulary list before reading the passage
7. Student used the comprehension monitoring tools
8. Recall questions asked AFTER child indicates they are finished
9. Researcher stop sharing the passage screen BEFORE recall question
10. Researcher refrained from providing corrective feedback to reading

and recalling the passage

Total ___/10 ____/10

154

APPENDIX M: Example Schedule

Meetings:

1. May 10th

â€¢ 1 session

2. May 12th

â€¢ 2 sessions

3. May 17th

â€¢ 2 sessions

4. May 19th

â€¢ 1 session

5. May 24th

â€¢ 1 session

6. May 26th

â€¢ 3 sessions

7. May 31st

â€¢ 3 sessions

8. June 2nd

â€¢ 2 sessions

9. June 7th

â€¢ 3 sessions

10. June 9th

â€¢ 3 sessions

11. June 14th

â€¢ 2 sessions

155