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UNDERSTANDING THE INFLUENCE OF OTHERS:
CHANGING EVALUATIONS OF MESSAGES
OR MESSAGES UNDER EVALUATION?

presented by

Rachel Annette Smith

has been accepted towards fulﬁllment
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UNDERSTANDING THE INFLUENCE OF OTHERS:
CHANGING EVALUATIONS OF MESSAGES
OR MESSAGES UNDER EVALUATION?
By

Rachel Annette Smith

A DISSERTATION

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

DOCTOR OF PHILOSOPHY
Department of Communication

2003

ABSTRACT
UNDERSTANDING THE INFLUENCE OF OTHERS:
CHANGING EVALUATIONS OF MESSAGES
OR THE MESSAGES UNDER EVALUATION?
By

Rachel Annette Smith

Asch (1940) proposed that group standards change how people interpret objects under
evaluation. This paper extends his intuition into a two—step model of social inﬂuence. In
the ﬁrst step, people interpret a given message differently with knowledge of how others
interpret said message than if they did not know about anyone else’s interpretation. In the
second step, people’s interpretation of a message, in turn, inﬂuences how their attitudes
change. Six studies test (a) if knowing how others thought a newspaper article showed a
particular bias in presenting an issue affects how participants, themselves, perceive the
extremity of this article’s advocated position, and (b) if deviations in participants’
interpretation from a control group inﬂuences how they change their attitudes toward this
issue. In a meta-analytic review of these experiments, this two-step model coincides with
participants’ reactions when they read newspaper articles opposing an issue, but fails to
account for reactions to reading articles supporting an issue. A ﬁnal experiment shows
that the effect of this type of social inﬂuence increases when words in a newspaper article

possess more ambiguity and disappears when they possess less ambiguity.

ACKNOWLEDGMENTS

I wish to thank my advisor, Dr. Frank Boster, who never ﬂagged in his concerns
for my clarity of thought. You encouraged me to pursue an area leﬂ alone for 60 years.
By making time for me, you gave me priceless insights, humility, and feedback. I am
grateﬁil to my academic mentors, Dr. Burgoon, Dr. Kaplowitz, Dr. Levine, and Dr.
Smith. You provided time, energy, grace, critique, and patience, which allowed me an
opportunity to complete this dissertation. Dr. Schwarz, thank you for providing me the
inspiration to follow this line of research and the caring to cheer me.

I must thank those who have seen me through this long journey, my parents, Anne
and Ray Smith, and grandmother, Genevieve Easley. You provided me enough mettle,
willpower, and discipline to complete this project. To those who came and left, LtCol.
Richard Easley, CDR. Ray F. Smith, and Elizabeth Smith, thank you for giﬂing me with
your spirit, aptitude, and dignity.

For those friends who picked me up more days than I care to count: Marge
Barkman, Jonathan Bowman, Jim DeVaughn, Ryan Goei, and Renee Strom. Thank you
for gracing me with your friendship, guidance, and heart. Ed Downs, muim béatha dén,
you appeared just in time and helped me make the ﬁnal push with coffee, editing,

cooking, urging, and reassuring — thank you.

iii

TABLE OF CONTENTS

LIST OF TABLES ........................................................................................................ VI
LIST OF FIGURES ..................................................................................................... VII
CHAPTER 1: THEORETICAL BACKGROUND ..................................................... 1
Inﬂuence of others ...................................................................................................... 2
Content and context ............................................................................................. 5
Extremity ............................................................................................................ 8
Dictionary meaning ............................................................................................. 9

Social function .................................................................................................. 10
Interpretations of position extremity .................................................................. 12
Interpretation effects and considerations ............................................................ 15
CHAPTER 2: INITIAL TEST .................................................................................. [9
Participants .............................................................................................................. 1 9
Design ...................................................................................................................... 19
Procedure ................................................................................................................. l 9
Article interpretation ......................................................................................... 24
Attitude change ................................................................................................. 25
Additional effects .............................................................................................. 26
CHAPTER 3: REPLICATION ................................................................................. 28
Vision 2020 Support ................................................................................................. 28
Participants .............................................................................................................. 28
Design, procedure, and instrumentation .................................................................... 28
Results .............................................................................................................. 29
International Teaching Assistants Opposition ............................................................ 31
Participants .............................................................................................................. 3 1
Design, procedure, and instrumentation .................................................................... 31
Results .............................................................................................................. 31
International Teaching Assistants Support ................................................................. 33
Participants .............................................................................................................. 33
Design, procedure, and instrumentation .................................................................... 33

Results .............................................................................................................. 34

Statistical Requirement Opposition ........................................................................... 36
Participants .............................................................................................................. 36
Design, procedure, and ittstrumentation .................................................................... 36
Results .............................................................................................................. 37
Statistical Requirement Support ................................................................................ 39
Participants .............................................................................................................. 39
Design, procedure, and itrstrumeutatiou .................................................................... 39
Results .............................................................................................................. 39
Meta-analytic results ................................................................................................. 41
CHAPTER 4: VARYING AMBIGUITY ................................................................. 44
Partic1pants .............................................................................................................. 44
Design ...................................................................................................................... 44
Procedure ................................................................................................................. 45
Article interpretation ......................................................................................... 47
Attitude change ................................................................................................. 48
Additional effects .............................................................................................. 49
CHAPTER 5: DISCUSSION ................................................................................... 50
Limitations ........................................................................................................ 51

Future research and implications ....................................................................... 52
APPENDIX .................................................................................................................. 55
BIBLIOGRAPHY ...................................................................... . ................................. 79

LIST OF TABLES

Table 1: Summary of Scale Means, Standard Deviations, and Reliabilities in
Experiment 1 ............................................................................................................ 56

Table 2: Descriptive statistics of Others’ interpretations by experimental conditions. ..... 57
Table 3: Summary of Newspaper Article Interpretations by Condition in Experiment 1 58

Table 4: Scale Means, Standard Deviations, and Reliabilities for Variables in
Replications ............................................................................................................. 59

Table 5: Summary of Correlations between Social inﬂuence, Interpretations, and Attitude
Change ..................................................................................................................... 60

vi

LIST OF FIGURES

Figure 1: Optical illusion: two women may be seen within the same picture. ................ 61

Figure 2: Distribution of others’ interpretations (each one is designated by an ‘X’) of two
articles’ advocated positions for or against Vision 2020. The two arrows represent the
two articles’ advocated positions when their respective content is evaluated in the
most objective or context-free of circumstances. ...................................................... 62

Figure 3: Graphical depiction of the two-step model under investigation. The predicted
social inﬂuence score, a combination of range and frequency values, inﬂuences how
participants’ interpretations of the newspaper article’s bias toward Vision 2020
deviated from the control group. The participants’ deviations from the control group
predict how their attitudes changed toward Vision 2020. Corrected parameter
estimates and goodness-of-ﬁt indices from experiment 1 are presented. ................... 63

vii

Chapter 1: Theoretical background

Scientiﬁc controversies constantly resolve themselves into differences about the
meaning of words. — A. Schuster (as cited in Odgen & Richards, 1923)

Before encountering a message for the ﬁrst time, people may have already heard
about that message from others. Friends may have seen and talked about an
advertisement, family members might have read someone’s speech in the newspaper and
commented about it around the dinner table, or colleagues may have read and gossiped
about the most recent company memo. After hearing other people give their own
perceptions of an ad, speech, or memo, persons may perceive these messages differently
than if they previously had not heard anyone else’s thoughts. Asch (1940) proposed that
this social inﬂuence, or change ofjudgment in response to group standards, was due to “a
change in the object of judgment, rather than in the judgment of the object” (p. 455,
italics in the original). Asch (eg, 1940; 1948) provided empirical evidence consistent
with his contention that contextual features, such as hearing others’ Opinions or knowing
the source Ofa message, alter a particular object ofjudgment, speciﬁcally a message’s
meaning.

Asch provided the intuition and broad brush-strokes to guide a different
theoretical explanation for social inﬂuence and attitude change; however, he never
articulated a process by which this type of social inﬂuence may occur. This paper
expands on how knowledge of others’ interpretations may change how people interpret
messages and, subsequently, change their attitudes. Aﬂer explicating the theoretical
premise, a single study and 5 replications test if (a) other’s interpretations affect how
participants interpret the extremity of a newspaper article’s advocated position toward

some issue, (b) participants change their attitudes in line with their newspaper article

interpretations, and (0) participants evaluate other related issues consistent with their
changed attitude. In these experiments, newspaper article topics, advocated positions, and
others’ interpretations (range and frequency) vary. Because social inﬂuences Operate
increasingly as ambiguity increases (e.g., Crutchﬁeld, 1955; Sherif, 1935), a ﬁnal
experiment keeps the previous variables constant and instead varies the ambiguity of the
words in a newspaper article.
Inﬂuence of others

In 1948, Asch objected to the theoretical underpinnings of social inﬂuence
models. He argued that these concepts were created to explain observations of people
changing their beliefs or attitudes in a way that was “inadequate to or contradicted the
actual demands of the situation” (p. 250). He wrote that authors using prestige suggestion
(e. g., Lorge, 1936) and later imitation (e.g., Bandura, 1969) thought of them as “capable
of inducing people to accept arbitrary opinions and evaluations regardless of their merit”
(p. 250). Asch reﬂected on Lorge’s studies of prestige suggestion (1936) in which he
predicted that the amount of prestige held by the attributed source of a message changes a
person’s reaction to that message. Under this prestige suggestion line of research,
scholars could combine foreknowledge of readers’ assessments of a source’s prestige and
their attitudes toward a message to predict readers’ ﬁnal attitudes.

This suggestion or imitation explanation demands multiple assumptions. First,
that people weigh and combine contextual features surrounding their exposure to a
message’s content separately from how they interpret this message (Asch, 1948). Second,
interpretations of a message’s content remain constant and evaluations of this message

change as the number of positive and negative contextual features vary. Third, one could

attribute any source to any message without any residual effects. For instance, if Oprah
Winfrey and Michael Jordan have +2 points of source prestige, then either source could
be associated with a message to create a positive shift in the readers’ ﬁnal attitudes no
matter what topic a message covered.

Although many studies of prestige used a single source, this paper focuses on a
situation in which many others provide their interpretations of a message before people
have the chance to make their own interpretations and future judgments of the same
message. In prestige suggestion or imitation research, the same rationale holds. More
sources merely provide more contextual features to consider. With multiple sources,
people weight and combine each source’s opinion into an overall social inﬂuence that
creates a shiﬂ in people’s attitudes. For example, in some evaluative circumstances,
people might have a summary report of what others thought about an article before they
get to read it. After reading that many others thought the article was biased in favor of a
new parking plan on campus, they would read a newspaper article covering this plan in
the following manner. A reader would reﬂect on the credibility of others who told them
about the article, evaluate the article’s parking plan content, combine the two scores, and
report a ﬁnal evaluation of the parking plan.

Although this rationale prevailed at the time, Asch (1948) argued that this process
did not reﬂect cognition well. Source prestige or credibility is not an attribute that can be
indiscriminately associated with any message’s content and be expected to create the
same effects. In contrast, attributing the message to a Speciﬁc source provides additional

contextual information through which to interpret the message’s content.

In contrast to the rationale behind prestige suggestion, Asch (1948) proposed, “the
speciﬁc content of an event or utterance is a function of the perceived relation between it
and its context.” Lewis also argued that “the material to be judged is seen in a new light
and has consequently changed its meaning... (e.g., suggestion or imitation) operate when
the material to be judged is susceptible of more than one meaning... (social inﬂuence)
can result in a restructuring of the material so that another and perhaps quite contrary
judgment is demanded” (Lewis, 1947, p. 233). In her study, a source’s prestige
“functioned to provide context for the statement. It was often in terms of this context that
the statement had its meaning” (Lewis, 1947, p. 243).

A number of cues may be gathered from a context. These cues include source,
word order/ agreement (e. g., Gollob, 1968', 1974; Heise, 1969), character balance (Leaf,
Kanouse, Jones, & Abelson, 1968; Lerner & Simmons, 1966), wording of questions or
instructions (see Kahenman, Slovic, & Tversky, 1982 for a review), situation, and prior
attitudes to name a few.

Sometimes features of the rating scale used to evaluate a message can also
provide respondents with information, such as norms or standards to which they can
compare themselves. For example, previous research (Schwarz, Hippler, Deutsch, &
Strack, 1985) showed the effect of response categories on peoples’ reports of their
behavior and their judgments of them. U.S. participants reported their daily TV viewing
habits on a scale that ranged from 30 minutes to more than 2.5 hours (group 1) or 2.5
hours to more than 4.5 hours (group 2). Those in group 1 reported less personal television
viewing, yet evaluated TV as more important in their lives and less satisfaction with their

leisure activities than those in group 2. Most US. viewers watch four hours of television

per day (Nielsen Media Research, 2000) and probably believe that their viewing habits
are about average. With a rating scale that ends at 2.5, the researcher provides an extreme
of television viewing behavior that falls below most viewers’ habits. In trying to
compromise between personal habits and not being above normal, those in group 1 are
likely to report lower viewing habits, and yet, judge TV is being important in their lives.
Group 2 would not face the same concerns, because the high end of their rating scale was
higher than most of their viewing habits.

In the previous example, people used end-points of the rating scale as a standard
of comparison in evaluating their behavior as well as its ramiﬁcations (e. g., the
importance of TV viewing in their lives). In this paper, context refers to any information
pertinent to the subsequent judgment that is not contained in a message. The point is this
contextual information can affect the manner in which people construe a message.

Under this deﬁnition, others’ interpretations become a contextual feature that
provides information to help readers disambiguate and interpret messages. For example,
with the knowledge of how others interpreted a message, people in turn may interpret the
same message differently than if they did not have this information. In sum, the process
of interpreting messages involves both content and context.

Content and context

When reading a message, people encounter sets of symbols: letters and
punctuation. They must string these symbols into words, phrases, and sentences and then
interpret them for their meaning (Kecskemti, 1952), which may be more or less
straightforward. Some words may have more potential meanings than other words, i.e.,

ambiguity (see Eylon & Allison, 2002 for a review). For example, the word “strong” has

19 different entries in a dictionary, whereas “punishment” has one entry (Webster’s
Revised Unabridged Dictionary, 1998). Consequently, people need to use contextual cues
to disambiguate a message’s content, e. g., the word “strong,” in order to interpret it.

In cross-cultural encounters, one can see the need for common symbol systems
when two people using two different character systems try to communicate. A reader who
only reads or writes with Cyrillic characters would be hard-pressed to interpret a message
written in Chinese characters. Although sharing character systems may help, two people
who do not share vocabulary, argots, or experiences may interpret the same message in
two different ways.

Even when two people share all the previous linguistic tools, they may still not
interpret a message similarly because interpretation is a dynamic process. On ﬁrst reading
a message, people may interpret its meaning in a way that later changes. Over time,
people may encounter new messages or simply reﬂect upon the message. Reﬂection on a
message and reception of new messages may add evidence for consideration, counter-
arguments, or social expectations, which may alter one’s original interpretation of a
message.

Language equivalence and reﬂection aside, the context in which a person reads a
message for the ﬁrst time may affect his or her interpretation of the message. The
interrelated conditions surrounding one’s reading of a message’s content, e. g. source,
situation, prior attitudes, etc., may change how one interprets this message’s content.
When reading a message, people must organize all of the sensory input into an
interpretable format, which may change the meaning of the message’s content. In classes

covering Gestalt psychology, instructors often demonstrate the impact of sensory

organization on interpretation through a visual exercise. Upon viewing one particular
drawing, see Figure 1, some students report seeing an older, disﬁgured woman and others
report seeing a young, attractive woman. The students organize the same set of visual
information into two completely different pictures.

In thinking about this process with messages, some students interpret two
different “meanings” from the same message’s content. When students hear that their
classmates see a completely different woman than they do, they often try to convince
each other to see this picture in a different way. They may try to show each other how to
organize the picture to see the alternate woman. Once students see each of the two
women within the drawing, they may be able to change the optical illusion at will. To see
a particular woman in the image, students must organize the image “Gestalt-wise: the
stimulus is the ‘ﬁgure,’ and everything else is the ‘background’” (Kecskemeti, 1952, p. 3;
see also Asch, 1948). Other students in the room are contextual features that help their
peers interpret this picture in particular ways.

The speciﬁc meaning attributed to a message’s content depends on the perceived
relationship between it and the context surrounding the message’s content (Asch, 1948).
Context can be directly tied to a message, e.g., coming from a designated source, or can
be indirectly primed, e.g., being in a good mood because of something else that preceded
one’s reading of a message. Context may inﬂuence interpretations of a message’s content
in at least three ways: (a) the extremity of a message’s advocated position toward an
issue, (b) the dictionary meaning of the words in a message, and (c) the social function of

this content.

Extremity

The context may guide how extreme a message’s advocated position seems to the
reader, i.e., that a message expresses some degree of militancy, conservativeness, bias
toward an issue, etc. Asch (1948) examined Lorge’s (1936) work to illustrate his point. In
Lorge’s study, participants read a message about capitalism. Some participants heard that
Harry Bridges, a famous union leader wrote the message. Other participants heard that
the author was the current president of the US. Chamber of Commerce. After reading the
message, the participants wrote a description of what the message meant. Participants
interpreted the message’s advocated position (more or less supportive of capitalistic
attempts) differently depending on the source of the message. For example, one
participant wrote that this message was an expression of the union leader’s complete
opposition to capitalist attempts, whereas another wrote that this message was the
president’s support of capitalist attempts with some modiﬁcation.

In another study (Burgoon, 1970), participants were split into two groups and
evaluated a set of black activists with a history of either militant or non-militant activism.
Afterwards, in a separate task, participants from both groups read the same, neutral
message about supporting black students on campus, and then they evaluated the
message’s militancy. Participants rated the message’s militancy differently depending on
(a) the participants’ own racial heritage and (b) which activists they had to evaluate
before reading the message. Black readers who evaluated militant activists versus non-
militant activists, rated the message as more militant. The white readers who evaluated
militant activists rated the message as less militant than those who evaluated the non-

militant activists. The process of evaluating activists’ militancy contributed to how

readers rated the message’s militancy, whereas the differences were signiﬁcantly
different from a control group who read the same message, but did not think about
anyone beforehand. Both of these studies illustrate how context may inﬂuence how a
reader interprets the extremity of a message.
Dictionary meaning

Context also may indicate which dictionary meaning should be used for particular
words or phrases. By indicating one deﬁnition instead of another, the entire meaning of
the message may change. If someone asked for a pen over by a mouse, one would likely
look for a writing instrument by a computer attachment and not a large containment area
next to a may little animal. In a past experiment, the meaning of ‘dislike’, e. g., Joe
dislikes Bill, was interpreted differently depending on other parts of the sentence.
Participants who read the following sentence, “Joe and Bill dislike each other, Bill and
Sam dislike each other. How do you think Joe and Sam feel about each other?” (Gerbing
& Hunter, 1979, p. 299). They interpreted the content of ‘dislike’ in the passage in
multiple ways: Bill was hard to get along with; Joe, Bill, and Sam are all offensive
people; and Joe and Sam share a dislike for Bill to name a few. Other participants, who
read similar sentences with the minor difference that Bill and Sam liked each other,
interpreted ‘dislike’ between Joe and Bill as dissimilar interests, enemies, and a reason
for the dislike. In this experiment the relationship between Bill and Sam changed how
participants interpreted the meaning of ‘dislike’ between Joe and Bill.

Allen and Wilder (1980) conducted three experiments to test how participants’
interpretations of the meaning of phrases could be inﬂuenced by knowing what other

people thought these phrases meant. In these experiments, participants read a sentence

such as “I would never go out of my way to help another person if it meant giving up
some personal pleasure” (p. 11 18, italics in original). The participants marked their
interpretations of the italicized phrase on a single item using a 10-point scale anchored
with “be inconvenienced” and “risk my life.” In a set of three experiments, they found
that (a) knowing of other’s interpretations of the phrases’ meaning inﬂuenced how the
participants interpreted the phrases’ meaning, (b) the participants’ chosen meaning could
not be explained by simple conformity to a group norm, and (c) their chosen meaning
affected how they evaluated (agreement or disagreement) an entire sentence.

Social function

The last context effect is the social function for content in the message. Content
serves social functions, a particular kind of work one intends the content to perform, or a
service expected by the reader due to his or her relationship to others. Duncker (193 8)
anticipated Asch’s work (e. g, 1948) when he suggested that when he associated an object
with a storybook hero, he might have created a new contextual meaning for it. In another
study, Lewis (1941) found that participants interpreted the purpose of the content of
slogans differently when President Hoover or Roosevelt ranked these slogans.

To illustrate this point, consider the meaning of colors, e. g., green. Most schools
in the United States select speciﬁc colors to represent the school, for example, Michigan
State University’s (MSU) colors are green and white. Most students are aware of their
school’s colors, but may not always think about their school every time they see the
color. If you ask MSU students to predict what color t-shirts another MSU student,
Henry, might buy, the students may or may not pick green, depending on whether or not

they know what colors Henry likes to wear and who is selling the t-shirts. If the students

10

learn that Henry likes green, needs a t-shirt, and another person from MSU is selling
shirts in green and white and orange and white, most students would predict that Henry
would buy a green shirt. If, however, the MSU vender is selling shirts in green and white
and blue and yellow (the colors of a rival university), the meaning of ‘green’ may very
well change to signify group loyalty.

Findings in a recent study showed that students predicted Henry would buy more
green t-shirts from an MSU vender who was selling shirts in green or rival school colors,
than when the same MSU vender sold shirt in green or non-rival colors (Smith, 2002).
One possible interpretation of this effect is that the alternative t-shirt in rival colors
provides a different interpretation to the t-Shirt color options. When Henry bought green
and white, he was not just supporting his own color preferences, but supporting the home
school in the face of a rival.

Understanding how people interpret messages should allow one to make
predictions about their subsequent attitude change in a two-step model. Others’
interpretations should inﬂuence how participants interpret an article, and participants’
interpretations, in turn, should inﬂuence how they change their attitudes. Whether a
message is true, liked, or representative of a person’s values is contingent on how this
person interpreted the message’s content (Asch, 1948; Kecskemeti, 1952). Although this
paper could focus on multiple contextual cues and message perceptions, the choice was
made to focus on one particular kind of message perception. We examine peoples’
perceptions of how strongly a message advocates a particular position on an issue, i.e.,

the amount and kind of bias the message may portray toward the issue it is addressing.

ll

Interpretations of position extremity

After reading the content of a message, people may make evaluations of how
much this message may advocate for or against the issue it is addressing. If a message’s
content refers to Vision 2020 (a plan to establish perimeter parking around campus and
rely on quick mass transit rather than front-door parking), people may interpret this
message’s advocated position differently, e.g., strongly in favor of Vision 2020,
moderately in favor of Vision 2020, or moderately against Vision 2020. People may look
to contextual features, such as how others interpreted this message, to disambiguate the
message’s content in order to interpret the extremity of this message’s advocated
position, especially ifthe words used in this message are highly ambiguous (Sherif, 1935;
West, 1981).

Range-frequency theory, started within psychophysics research, has been
extended to explain how others’ interpretations may inﬂuence the interpreted extremity
of a message’s content (Parducci, I965; I995). Range-frequency theory posits that the
judged value or weight of a stimulus is determined by its location within a distribution of
contextual stimuli that are salient at the time of judgment. Carrying this idea to message
interpretation, people’s evaluation of the extremity of a message’s advocated position is
contingent on this message’s location within the salient distribution of others’
interpretations of this message. For example, readers’ memory of how others interpreted
a newspaper article’s advocated position toward Vision 2020 would impact how these
readers would interpret how extremely the same newspaper article advocates for or

against Vision 2020.

12

Range-frequency theory rests on two estimated values. The range value (Parducci,
1965; Volkmann, 1951) is an estimate of the relative discrepancy between the message’s
content and the two end-points of a subjective interpretation scale. The most disparate
interpretations from others would set the end-points of a subjective scale in which a
person interprets the message. Holding all else constant, the range value increases as the
distance between the message’s content and each end-point of the subjective scale
becomes more un—equal. If the message’s content is closer to the positive end-point than
the negative end-point, the range value will increase positively. In the opposite case, the
range value will increase negatively. The range value, Rmc, of Message m in Context c is
given as

Rmc = (Sm - Sf)/ |S,,,ax — Smml,

where S,,, is the extremity of a message’s advocated position, SW and Smax are the
minimum and maximum interpretations that others provided, and Sfis the observed
maximum or minimum that is farthest from the message’.

The frequency value (Parducci, 1965) is an estimate of the location of the target
stimulus described by its rank within a set of stimuli. Holding all else constant, the
frequency value increases as the number of others’ interpretations falling on either side of
the message’s content becomes less symmetrical. If others provide more negative than
positive interpretations of a message, relative to the message’s content, the frequency
value will increase positively. In the opposite case, the frequency value will increase
negatively. The frequency value, ch, of Message m in Context c is given as

ch : (nn _ np)/ (Ne _ 1),

 

1 In cases where the message advocates against an issue, the numerator changes. The message is subtracted
from the farthest point.

13

where nn is the number of interpretations that are more negative than the message
and 11,; is the number of interpretations that are more positive than the message. NC is the
total number of others’ interpretations of the message. Others’ interpretations that are
equivalent to the message’s content are counted with the interpretations between the
message and the farther end-point.

Interpretations of messages are inﬂuenced by the weighted, linear combination of
both range and frequency values. As the range value becomes increasingly negative, a
reader will make a more negative interpretation of a message, because this reader
interprets this message’s content as more representative of the closer, negative end-point
of the subjective scale. As the frequency value becomes increasingly negative, a reader
will interpret a message as more negative. The reader gives each interpretation provided
by others an equivalent space on their subjective interpretation scale. When the frequency
value is negative, i.e., more people provide more positive, versus negative, interpretations
than the message’s content, the amount of space on the subjective scale between the
message’s content and the positive end of the scale stretches (Parducci, 1995).
Subjectively, the positive end is farther away from the message’s content, leading to a
more negative interpretation of the message’s content. Interpretations may move in a
positive direction as well: as range and frequency values become increasingly positive,
one should interpret the message’s content as more positive. The range and frequency
values are averaged into a total predicted social inﬂuence on one’s interpretation of how
extreme is a message’s advocated position.

To illustrate the predictions, a sample of others’ interpretations of a newspaper

article is illustrated in Figure 2. The distribution ranges on a scale from 5 to -5. In the ﬁrst

situation, students either read the message that is rated in the most context-free possible
situation as -2 (moderately against Vision 2020, M1 in the ﬁgure) or as 2 (moderately in
favor of Vision 2020, M2 in the ﬁgure) on the same scale. The moderately unfavorable
message (M1) within this distribution of others’ interpretations would have a range value
of.-7 (i.e., (-2 — 5)/ |(-5) — 5]) and a frequency value Of-.7 (i.e., (2 — 9)/(1 l-l)),
combining to a —1.4 inﬂuence, leading to a more unfavorable interpretation of Vision
2020 than a context free interpretation. The moderately favorable message (M2) within
the same distribution would have a range value of .7 (i.e., (2 — (-5))/ l5 — (-5)|) and a
frequency value of.3 (i.e., (7 — 4)/(1 1-1)), combining to a 1.0 inﬂuence, leading to a
more favorable interpretation of Vision 2020 than a context free interpretation. When
comparing the relative inﬂuences on the favorable and unfavorable message, the
discrepancy between the message interpretations and the context-free interpretation
should be higher for the unfavorable message than the favorable message.
Interpretation effects and considerations

Concern over message interpretation stems from an interest in explaining attitude
change that results from reading a message. The second step of the proposed model uses
the linear discrepancy model (Hunter, Levine, & Sayers, 1976) to predict attitude change.
The prediction is that people should change their attitudes in the direction of their
interpretation of the message’s advocated position. After people interpret a message, they
compare this message’s advocated position to how they feel about this position. For
example, after students interpret the newspaper article’s position toward Vision 2020,
they would then compare how they feel about Vision 2020 to their interpretation of the

article’s position toward Vision 2020.

15

Holding all else constant, attitude change is a ﬁJIICIIOII of how much discrepancy
exists between the message and the person (e.g., French, 1956; Hunter, Levine, & Sayers,
1976). As discrepancy between the message and the person increases, the person should
have proportionally larger changes in their attitude toward their interpretation of the
message’s advocated position (e.g., French, 1956; Hunter, Levine, & Sayers, 1976). This
model is consistent with data obtained in studies of attitude and Opinion change
experiments (e. g., Danes, Hunter, & Woelfel, 1978; Hoyland & Pritzker, 1957) and group
decisions (e. g, Boster, Fryrear, Mongeau, & Hunter, 1982; Boster, Hunter, & Hale, 1991;
Boster, Mayer, Hunter, & Hale, 1980). Although some studies have found non-linear
results (see McGuire, 1985 for a review), scholars attribute these results to source
credibility, issue and ego involvement, and attachment to initial position. In order to
control for these issues, as well as in-group/ out-group source effects, sources of other
interpretations were made anonymous. Although these variables may moderate the
hypothesized relationship, the focal crux of this social inﬂuence should be the inherent
ambiguity of the message, itself.

Sherif (1935) contented that social inﬂuences operate increasingly as ambiguity
increases. The message must have inherently some level of ambiguity in order to
necessitate the use of contextual information, such as what others thought about a
message. In a careful, controlled study Crutchﬁeld (I956) varied his stimuli in two ways:
factual to attitudinal and structured to ambiguous. As the ambiguity of these stimuli
increased, social inﬂuence effects increased. Participants viewed the same stimuli (Slides)
in groups of ﬁve. Participants were asked to make a judgment about each stimulus, one at

a time, in a designated order. When participants heard how others judged stimuli before

16

they made their judgments, the most pronounced social inﬂuence effects occurred with
the inherently ambiguous slides. The exceptions to this general rule came when
participants made judgments about which slides they preferred. In these cases, inﬂuence
effects dissipated. People do not need others to determine how to interpret their own
preferences, so we see ambiguity diminished from the type of question, even if what they
are viewing is somewhat ambiguous. In the following experiments, as the ambiguity of a
message increases, participants should depend more on contextual features as they
determine the extremity of a given message’s advocated position toward an issue.

In sum, the hypothesis of this paper is that pre-existing knowledge of how much
bias others believe a newspaper article portrays toward the issue it addresses would alter
participants’ own perceptions of this article as long as the words possess inherent
ambiguity. For example, a reader’s interpretation of how much a newspaper article
supports Vision 2020 would vary depending on whether this reader had pre-existing
knowledge of how others interpreted this article. Holding all else constant, the closer a
message’s content is to the negative end of others’ interpretations and asymmetrically
further from the positive end, a reader will interpret this message more like the closer
(negative) end. As the number of others who interpret a message more positively than a
message’s content, versus more negatively, increases, readers psychologically will
provide Space for each additional positive interpretation, pushing the positive end farther
away, leaving them to interpret the message more like the subjectively closer (negative)
end.

Three experiments examine these predictions. The ﬁrst experiment tests (a) if pre-

existing knowledge of how much bias others believe a newspaper article portrays toward

l7

the issue it addresses alters participants’ own perceptions of this article as predicted by
the combined range and frequency estimates. Next, it tests (b) if participants change their
attitudes about an issue toward the position they believe the newspaper article holds
towards this issue. Last it tests (c) if participants’ attitude changes also affect their
attitudes toward other related issues. Others’ interpretations will vary in scope (wide or
narrow) and distribution (normal or negative-skew) to induce changes in range and
frequency values. The second set of experiments test if the results from experiment 1
replicate with different issues presented with different valences. The third experiment
tests if the effect of others’ interpretations on the participants’ interpretation varies as a

function ofthe ambiguity ofthe words used in an article.

18

Chapter 2: Initial Test

Participants

Fifty undergraduate students enrolled in communication courses at a large
Midwestern university participated in this study. On average, participants were 21 years
old (SD = 2.15), in their third year at the college (SD = 1.20), female (68%), and drove
cars (64%).
Design

The experimental design was a scope (wide or narrow) by distribution (negative-
skew or normal) factorial, control-group design. Participants completed an attitude survey
before and after processing the newspaper article. Variation in the scope and distribution
Of others’ interpretations of the article induced differences in participants’ range and
frequency values. All participants read a newspaper article opposing Vision 2020. Ten
participants were randomly assigned to each condition.
Procedure

The experimenter told participants that they would be helping her develop
stimulus materials for a future study. These materials were newspaper articles from the
students’ local paper. The students were led to believe that the experimenter needed to
know if these articles presented balanced, objective, neutral coverage of an issue prior to
using them in a future experiment. Participants heard that other students had read these
articles previously. Each participant would then read how 10 other people evaluated one
particular newspaper article. Participants would (a) categorize and scale how others
evaluated that newspaper article and then (b) provide their own evaluation of the

newspaper article.

19

Before participants began this procedure, they were told that the experimenter
needed each student to ﬁll out a short questionnaire in order to ﬁnd out what pre-existing
opinions they had toward the issues that their newspaper article might cover. Hence,
participants completed a short questionnaire to measure their pre-existing opinions on a
set of issues, including a plan to establish perimeter parking around campus and rely on
quick mass transit rather than front-door parking (Vision 2020), new course requirement
before declaring a major, diversity on campus, and the quality of campus parking
facilities.

After completing this questionnaire participants picked up a second packet. First,
participants read how to categorize and scale others’ interpretations of one newspaper
article. The experimenter explained that 10 other students already had read one
newspaper article. Each of these other 10 students wrote down what they thought the
article was advocating, in other words, they wrote down if they thought the article
covered Vision 2020 in a favorable, unfavorable, or neutral light. The experimenter
explained that these other students did not write down if they personally liked the article
or Vision 2020, but they wrote down what opinion or bias the newspaper article
presented. Participants had no information about the identity of these ﬁctitious students.

The participants read these others’ interpretations, and then rated them on a scale
that they developed. In order to develop their scale they used a line on the survey to mark
where they thought each of the 10 interpretations fell along a continuum from showing a
bias in favor or in opposition toward Vision 2020. Participants could mark more than one
of the 10 responses in the same place on their scale. After they ﬁnished arranging their

interpretations, they would identify the most extreme student response (i.e., the ones

20

furthest to the left and furthest to the right). Once they identiﬁed these extremes,
participants would label them as “neutral, opposed, or favorable” and qualify whatever
they chose with “very, moderately, or mildly.” Consequently, some participants produced
scales anchored with “very opposed” to “very neutral,” other scales were anchored by
“mildly favorable” to “very opposed.”

Pilot testing indicated that this elaborate procedure helped participants believe
that the experimenter really did not want their opinions about what other people thought.
The experimenter simply wanted participants to read these other interpretations and
elaborate on them. In the pilot debrieﬁngs, participants reported that in other experiments
they only report their opinions. They needed afﬁrmation that their role in this study was
to help create a stimulus and categorize others’ opinions, because, in their minds,
“participants” in a study report their opinions.

After ﬁnishing their scale, participants rated each of the other 10 student
interpretations individually on three standardized scales. Participants provided their
Opinion of how credible each of the other students were. Next, participants read the
newspaper article that the other 10 Students read previously. Participants provided their
own perception of how the article covered Vision 2020 and whom they believed wrote
their article. Last, participants completed the original questionnaire, measuring their
attitudes toward topics covered in newspaper articles, a second time.

Those participants in the control group heard that they were to evaluate articles
from their local university newspaper. This condition differed from the experiment, in
that these participants heard no information about how others interpreted these articles.

Sample stimulus materials are available in the Appendix.

21

Instrumentation

The following indicators were tested for unidimensionality (Hunter & Gerbing,
1982). All indicators that could be tested passed these tests.

Article advocacy. Participants indicated their interpretations of an article’s
advocacy of an issue with (a) an open—ended question, asking them how they interpreted
the newspaper article’s meaning and (b) three 9-point, semantic differential items. Items
asked participants to rate the extremity of the article’s advocated position on Vision 2020
with anchors, veryfavorable/vety unfavorable, strongly like/strongly dislike, and strongly
support/Strongly oppose. A single summed score for article advocacy was generated, 12 =
strongly supported, - l 2 = strongly opposed, SI a = .97.

Attitude. Participants indicated their attitudes toward Vision 2020 and other issues
covered in their local paper on three 9-point, semantic differential items for each issue.
Items asked participants how they felt about an issue, e. g., Vision 2020, with anchors,
very favorable/very unfavorable, strongly like/strongly dislike, and strongly
support/Strongly oppose. A single summed score for each issue was generated, 12 =
strongly supported, -12 = strongly opposed, see Table 1 for reliabilities, means, and
standard deviations.

Range and frequency values. Participants scaled what bias others (labeled with
letters “a” through “j” to retain anonymity) thought an article exhibited on three 9-point
semantic differential items with anchors, very favorable/very unfavorable, strongly
like/strongly dislike, and strongly support/Strongly oppose. A single summed score for

each person was generated, 12 = strongly supported, -12 = strongly opposed, (a S1 or =

22

.98;bS/a= .99; cSIa= .99; dSIa= .98; cSIa= .99; fSIa= .99;gSIa= .98; hSIa=
.99; iSl a = .99;j SI (1 =99).

To induce different range and frequency values, the scope of each distribution
varied. The narrow condition provided others’ interpretation four points above and below
the message’s content; the wide condition spanned seven points above and below the
message’s content. For normal distribution, an equal number of opinions were more
positive and negative than the message; for negative skew distribution, seven opinions
were more positive and three opinions were more negative than the content. Table 2
provides student ratings of these interpretations.

The maximum and minimum scores each participant gave the Others’
interpretations were used to calculate a range value denominator. The range value
numerator was calculated by (a) determining which interpretation from the others resided
the farthest from the control group’s estimate, and then (b) subtracting this interpretation
from it. The absolute difference between the extreme interpretations from others served
as the range value denominator.

For their frequency value numerator the experimenter counted the number of
others’ interpretations scaled more positively and negatively than baseline estimates. The
number of others evaluated, 10, served for their frequency value denominator.

The two values were averaged into a single predicted social inﬂuence score.
Descriptive statistics of range value, frequency value, and predicted social inﬂuence

score may be seen in Table 2.

23

Others" credibility. Participants indicated the credibility of each of the others who
interpreted their newspaper article on a single 5-point scale, 5 = very credible, I = very
uncredible. These scores were rescaled, 2 = very credible, -2 = very uncredible.

Source attribution. Participants identiﬁed who they thought wrote their newspaper
article in an open-ended question. This information does not appear in the analyses, but is
available upon request.

Results

Participants in the control group rated this experimental newspaper article as
opposing Vision 2020 (M = -2.90, SD = 7.10), but within sampling error of a neutral
rating, I (9) = -1.29, ns. Participants interpreted this article’s opposition to Vision 2020
differently if they read how 10 other (ﬁctitious) students interpreted this article. On
average, participants reading others’ interpretations moved 20% up or down the scale
used to index the bias represented in the newspaper article (see information by condition
in Table 3). Participants in the experimental conditions rated the ﬁctitious 10 students as
credible (M = .23, SD = .52), t (39) = 2.86, p < .05, without variation between conditions
(F< 1).

Article interpretation

The social inﬂuence hypothesis, see Figure 3, coincided with these data. Each
participant’s range value (asymmetrical closeness to one endpoint over the other) and
frequency value (asymmetrical representation of more positive versus negative

interpretations) were averaged to create a predicted social inﬂuence scorez. Their social

 

2 The two values were analyzed as separate values within a multiple regression. Using the single averaged
score, i.e., the predicted social inﬂuence score, accounted for the same amount of variance in participants’
message interpretations as the two separate values. Because multiple R and single r were similar, the

24

inﬂuence score, the sum of frequency and range values developed from each participant’s
exposure to others’ interpretations of this article, accounted for how participants’
interpretations deviated from the baseline interpretation, r (39) = .44, p < .05.
Experimental conditions and assessments of the others’ credibility accounted for no
additional variance (1“ < 1).

Attitude change

All participants’ attitudes toward Vision 2020, including those in the control
group, became less favorable after reading the newspaper article opposing Vision 2020
(M change = -2.46, SD = 5.61), t (49) = -3.10,p < .05. For those exposed to others’
interpretations, how their article interpretation deviated from the baseline interpretation
predicted how their attitudes toward Vision 2020 changed, r (39) = .4l,p < .05. The
linear discrepancy model ﬁt these data well. The correlation between participants’ initial
attitude toward Vision 2020 and their attitude change was negative, r (3 9) = -.21.
Additionally, the autocorrelation between the initial and ﬁnal attitude reports was high
(.72).

This two-step model: Others’ interpretations inﬂuence how participants interpret
an article and participants’ interpretations, in turn, inﬂuence how they change their
attitudes toward Vision 2020, coincided with this data, X2 (I, 39) = .01, ns, RMSE = .00
(see Figure 3 for model with corrected parameter estimates). Whether participants drove

cars on campus or not did not affect this model (F < l).

 

decision was made to use the more parsimonious model. Only the predicted social inﬂuence score is used
in the rest of the manuscript.

25

Additional effects

For those exposed to Others’ interpretations, their initial attitudes toward Vision
2020 (B = .21) and the use of non-motorized vehicles, such as walking, hiking, or skating
to places on campus ([3 = .60) related to their ﬁnal attitudes toward non-motorized
vehicles, F (2, 37) = 17.86, p < .05, R = .70. As approval ofthe parking plan decreased,
their approval of non-motorized vehicles on campus decreased. Their attitudes toward
Vision 2020 did not relate to any of their ﬁnal attitudes toward the other issues (trustee’s
recent proposal, course requirement, parking facilities, international teaching assistants,
advising ofﬁce, diversity on campus, and science classes).

Discussion

A two-step model of social inﬂuence inspired by Asch’s (1940) conclusion that
group standards change how people interpret objects under evaluation was tested in this
experiment. The two-Step, causal model received empirical support. Pre-existing
knowledge of how biased (ﬁctitious) other people thought a newspaper article was in
addressing Vision 2020 affected participants’ own perceptions of the article’s bias. The
way in which participants’ perceptions deviated from the control group predicted how
participants’ attitudes changed toward Vision 2020. The two-step model predicted their
article perceptions and their resulting attitude change.

Initial attitudes toward the Vision 2020 parking plan did not inﬂuence ﬁnal
attitudes toward other, related issues strongly and did not inﬂuence unrelated issues at all.
Initial attitudes correlated weakly to one related topic, evaluations of using non-
motorized vehicles on campus. As participants reported more initial approval of the

Vision 2020 parking plan and using non-motorized transportation, such as walking,

26

hiking, or skating, to places on campus, they reported more ﬁnal approval toward non-
motorized transportation.

Without longer longitudinal studies the long-term impact of changes in attitudes
toward Vision 2020 remains hidden. Longer studies provide an additional beneﬁt by
allowing scholars to see how long participants’ attitude change toward Vision 2020
would be sustained.

Although the model received empirical support in this experiment, replication
using newspaper articles that support Vision 2020 as well as presenting both kinds of bias
with different issues provides a more rigorous test. The next set of experiments presents

these replications.

27

Chapter 3: Replication

To test how well the two-step model of social inﬂuence replicates, ﬁve
experiments varying article advocacy (supportive or opposing) and issue (implementing
the Vision 2020 parking plan, requiring a research methods course before students
declare a communication major, and employing international teaching assistants for
undergraduate classes) were conducted. The two-step model under investigation may be
seen in Figure 3.

These experiments repeated the design, procedure, and instrumentation from
Experiment 1. Each experiment used separate samples; within each experiment there
were independent groups. The measurement validity and reliability showed no signiﬁcant
changes from Experiment 1 or between experiments. Refer to Table 4 for means,
standard deviations, and reliabilities of articles and attitude changes toward issues.

Vision 2020 Support
Participants

Undergraduate students (n = 95) enrolled in communication courses at a large
Midwestern university participated in this study. On average, participants were 21 years
old (SD = 2.21), in their third year at the college (SD = 1.26), female (62%), and drove
cars on campus (59%).

Design, procedure, and instrumentation

The experimental design was a scope (wide or narrow) by distribution (negative-
skew or normal) factorial (n = 75), control-group (n = 21) design with random
assignment. Variation in the scope and distribution of others’ interpretations induced

differences in participants’ range and frequency values. Participants completed an

28

attitude survey before and after processing the newspaper article supporting Vision 2020.
The procedures for this experiment replicate those used in experiment I. All indicators
passed tests of unidimensionality (Hunter & Gerbing, 1982). Measurement validity and
reliability showed no signiﬁcant changes from Experiment 1.

Results

Participants in the control group rated this experimental newspaper article as
supporting Vision 2020 (M: 8.04, SD = 4.54), t (19) = 8.12,p < .05. Participants
interpreted this article’s support for Vision 2020 differently ifthey read how 10 other
(ﬁctitious) students interpreted this article. Participants in the experimental conditions
rated the ﬁctitious 10 students as credible (M = .37, SD = .42), t(73) = 7.55, p < .05
without variation between experimental conditions (F < 1).

Article interpretation. The social inﬂuence hypothesis, see Figure 3, was
inconsistent with these data. Their predicted social inﬂuence score, the sum of frequency
and range values developed from each participant’s exposure to others’ interpretations of
this article, did not account for how article interpretations between experimental and
control group participants differed from zero, r (73) = .08, ns.

Under ﬁirther investigation, almost 30% of the participants (n = 22) who read the
supportive article held pre-existing attitudes outside of any of the others’ interpretations
oftheir article. In this case these participants strongly opposed Vision 2020 (M = -8.23,
SD = 4.07), t (19) = -9.27, p < .05. For those whose held these strong, negative pre-
existing attitudes, their predicted social inﬂuence score accounted for how their

interpretations deviated from the control group’s interpretation, r (20) = .30, ns, as in

29

Experiment 1. Experimental conditions and assessments of the others’ credibility
accounted for no additional variance (F < 1).

For the rest of the participants who read this article (n = 53), their pre-existing
attitude toward Vision 2020 was supportive (M: 2.31, SD = 5.51), t (51) = 3.11,p < .05.
Their social inﬂuence prediction did not account for how their article interpretations
deviated from the control group, r (51) = .01, ns. Those in only one condition, narrow
scope and normal frequency, estimated their supportive article as much less supportive
(M = -4.07, SD = 6.86) than the control group’s interpretation, while all other participants
perceived the article similarly to the control group (M = -.58, SD = 4.51), F (1, 51) =
4.72, p < .05, r = .29. Others’ credibility accounted for no additional variance (F < 1).

Attitude change. All participants’ attitudes toward Vision 2020, including those in
the control group, became more favorable after reading the newspaper article supporting
Vision 2020 (M change = 2.62, SD = 5.46), t (93) = 4.64, p < .05. For those exposed to
others’ interpretations, their deviations from the control group’s interpretation of the
article predicted how their attitudes toward Vision 2020 changed, r (73) = .29, p < .05.
The linear discrepancy model ﬁt these data well. The correlation between participants’
initial attitude toward Vision 2020 and their attitude change was negative, r (93) = -.23.
Additionally, the autocorrelation between the initial and ﬁnal attitude reports was high
(.73).

The hypothesized two-step model does not receive empirical support because the
ﬁrst link failed with most of the participants. The mediation model, changes in attitudes

mediated through interpretations of a message, coincided with this data, X2 (1,74) = .01,

30

ns, RMSE = .00 (see Table 5 for corrected parameter estimates). Whether participants
drove cars on campus or not did not affect this model (F < 1).

Additional effects. Their initial attitudes toward Vision 2020 did not relate to any
of their ﬁnal attitudes toward the other issues. This result differed from Experiment 1.

International Teaching Assistants Opposition

Participants

Undergraduate students (it = 108) enrolled in communication courses at a large
Midwestern university participated in this study. On average, participants were 21 years
old (SD = 1.38), in their third year at the college (SD = .70), and female (77%).
Design, procedure, and instrumentation

The experimental design was a scope (wide or narrow) by distribution (negative-
skew or normal) factorial (n = 90), control-group (n = 18) design with random
assignment. Variation in the scope and distribution of others’ interpretations induced
differences in participants’ range and frequency values. Participants completed an
attitude survey before and after processing the newspaper article opposing the
employment of international teaching assistants (ITAs). The procedures for this
experiment replicate those used in Experiment 1. All indicators passed tests of
unidimensionality (Hunter & Gerbing, 1982). Measurement validity and reliability
showed no signiﬁcant changes from Experiment 1.
Results

Participants in the control group rated this experimental newspaper article as
opposing the employment of international teaching assistants (ITAs) in undergraduate

classes (M = -7.72, SD = 5.60), t (16) = -5.85, p < .05. Participants interpreted this

31

article’s opposition toward employing ITAs differently if they read how 10 other
(ﬁctitious) students interpreted this article. Participants in the experimental conditions
rated the ﬁctitious 10 students as credible (M = .28, SD = .50), t(88) = 5.42, p < .05,
without variation between experimental conditions (F < 1).

Article interpretation. The social inﬂuence hypothesis, see Figure 3, coincided
with these data, although the effect was within sampling error of zero. Their predicted
social inﬂuence score, the sum of frequency and range values developed from each
participant’s exposure to others’ interpretations of this article, did not account
signiﬁcantly for how article interpretations between experimental and control group
participants differed, r (88) = .18, p = .09. Experimental conditions and assessments of
the Others’ credibility accounted for no additional variance (F < 1).

Attitude change. All participants’ attitudes toward employing ITAs, including
those in the control group, became less favorable after reading a newspaper article
opposing ITAs’ employment (M change = -l.75, SD = 5.27), t (106) = -3.47,p < .05. For
those exposed to others’ interpretations, their deviations from the control group’s
interpretation of the article predicted how their attitudes toward employing ITAs
changed, r (88) = .22, p < .05. The linear discrepancy model ﬁt these data well. The
correlation between participants’ initial attitudes toward Vision 2020 and their attitude
changes was negative, r (88) = -.52. Additionally, the autocorrelation between the initial
and ﬁnal attitude reports was strong (.59).

This two-step model: others’ interpretations inﬂuence how participants interpret
an article and participants’ interpretations, in turn, inﬂuence how they change their

attitudes toward employing ITAs, coincided with this data, X2 (1,89) = 1.81, ns, RMSE =

32

.04 (see Table 5 for corrected parameter estimates). High error associated with the model
and limited support for the ﬁrst link in the chain limits empirical support for the two-step
model.

Additional effects. For those exposed to others’ interpretations, their initial
attitudes toward international teaching assistants ([3 = .10) and a trustee’s proposal to
reimburse students’ tuition if students could not understand their teachers (0 = .85)
related to their ﬁnal attitudes toward the trustee’s proposal, F (2, 88) = 162.19,p < .05, R
= .89. Their attitudes toward international teaching assistants did not relate to any oftheir
ﬁnal attitudes toward the other issues.

International Teaching Assistants Support
Participants

Undergraduate students (it = 1 17) enrolled in communication courses at a large
Midwestern university participated in this study. On average, participants were 21 years
old (SD = 2.16), in their third year at the college (SD = .66), and female (78%).

Design, procedure, and instrumentation

The experimental design was a scope (wide or narrow) by distribution (negative-
skew or normal) factorial (n = 97), control-group (n = 20) design with random
assignment. Variation in the scope and distribution of others’ interpretations induced
differences in participants’ range and frequency values. Participants completed an
attitude survey before and after processing a newspaper article supporting the
employment of international teaching assistants (ITAs). The procedures for this

experiment replicate those used in Experiment 1. All indicators passed tests of

33

unidimensionality (Hunter & Gerbing, 1982). Measurement validity and reliability
showed no signiﬁcant changes from Experiment 1.
Results

Participants in the control group rated this experimental newspaper article as
supporting the employment international teaching assistants (ITAS) in undergraduate
classes (M = 8.50, SD = 4.58), t (18) = 8.30, ns. Participants interpreted this article’s
support of employing lTAs differently ifthey read how 10 other (ﬁctitious) students
interpreted this article. Participants in the experimental conditions rated the ﬁctitious 10
students as credible (M = .34, SD = .47), t (95) = 7.25, p < .05, without variation between
experimental conditions (1" < 1).

Article interpretation. The social inﬂuence hypothesis, see Figure 3, was
inconsistent with these data. Their predicted social inﬂuence score, the sum of frequency
and range values developed from each participant’s exposure to others’ interpretations of
this article, associated with how participants’ interpretations deviated from the control
group’s interpretation, r (95) = -.33, p < .05, in a direction counter to prediction.
Experimental conditions and assessments of the others’ credibility accounted for no
additional variance (F < 1).

Under further investigation, 46% of the participants (n = 45) who read the
supportive article held pre-existing attitudes outside of any of the others’ interpretations
of their article. In this case these participants strongly opposed the employment ITAs (M
= -7.42, SD = 3.70), t(43) = -13.45,p < .05. For those who held these strong, negative
pre-existing attitudes, their social inﬂuence score associated with how their

interpretations deviated from the control group’s interpretation counter to prediction,

34

r(43) = -.43, p < .05. Experimental conditions and assessments of the others’ credibility
accounted for no additional variance (F < 1).

For the other half of participants who read this article (n = 52), their pre-existing
attitude toward employing international teaching assistants was near the scale’s neutral,
mid-point (M= -1.13, SD = 4.65), t(50) = -1.75, ns, Their social inﬂuence score
associated with how their article interpretation deviated from the control group’s
interpretation counter to prediction, r (50) = -.28, p < .05. Experimental conditions and
assessments of the others’ credibility accounted for no additional variance (F < 1).

Attitude change. All participants’ attitudes toward employing ITAs, including
those in the control group, became more favorable after reading a newspaper article
supporting their ITAs’ employment (M change = 2.84, SD = 4.86), t(115)= 6.33,p < .05.
For those exposed to others’ interpretations, their deviations from the control group’s
interpretation of the article did not predict how their attitudes toward employing ITAs
changed different from zero, r (95) = .04, ns. Although participants did not exhibit much
attitude change, the linear discrepancy model ﬁt these data. The correlation between
participants’ initial attitudes toward international teaching assistants and their attitude
changes was negative, r (96) = -.21. Additionally, the autocorrelation between the initial
and ﬁnal attitude reports was strong (.65).

Under further investigation, participants seemed to exhibit a different pattern for
attitude change if they held pre-existing attitudes very opposed to employing ITAs, r (43)
= -.13, ns, versus if they held less extreme pre-existing attitudes, r (50) = .15, ns. Neither

of these correlations differed signiﬁcantly from zero.

35

Although the ﬁrst part of the two-step model turned out counter to the prediction,
the mediated model coincided with these data, X2 (1, 96) = .21, ns, RMSE = .01 (see
Table 5 for corrected parameter estimates). The two-step model did not receive empirical
support because the ﬁrst hypothesis was inconsistent with these data.

Additional effects. For those exposed to others’ interpretations, their initial
attitudes toward international teaching assistants (0 = -.10) and a trustee’s proposal to
reimburse students’ tuition if students could not understand their teachers ([3 = .81)
related to their ﬁnal attitudes toward the trustee’s proposal, F (2, 94) = 109. 18, p < .05, R
= .84. Their attitudes toward international teaching assistants did not relate to any of their
ﬁnal attitudes toward the other issues. This result replicated how participants’ responded
to an article opposing the employment of ITAs.

Statistical Requirement Opposition
Participants

Undergraduate students (it = 48) enrolled in communication courses at a large
Midwestern university participated in this study. On average, participants were 21 years
old (SD = 1.61), in their third year at the college (SD = .83), female (68%), and majors in
communication (86%).

Design, procedure, and instrumentation

The experimental design was a scope (wide or narrow) by distribution (negative-
skew or normal) factorial (n = 39), control-group (n = 9) design with random assignment.
Variation in the scope and distribution of others’ interpretations induced differences in
participants’ range and frequency values. Participants completed an attitude survey

before and after processing a newspaper article opposing a new requirement to pass a

36

statistical course before declaring communication as a major. The procedures for this
experiment replicate those used in Experiment 1. All indicators passed tests of
unidimensionality (Hunter & Gerbing, 1982). Measurement validity and reliability
showed no signiﬁcant changes from Experiment 1.

Results

Participants in the control group rated this experimental newspaper article as
opposing a new requirement for students to pass a statistical course before they could
declare communication as their major (M= -6.00, SD = 6.16), t (7) = -2.58,p < .05.
Participants interpreted this article’s opposition toward this course requirement
differently if they read how 10 other (ﬁctitious) students interpreted this article.
Participants in the experimental conditions rated the ﬁctitious 10 students as neutral on
credibility (M = .09, SD = .51), t (37) = 1.1 1, us, without variation between experimental
conditions (F< 1).

Article interpretation. The social inﬂuence hypothesis, see Figure 3, coincided
with these data. Their predicted social inﬂuence scores, the sum of frequency and range
values developed from each participant’s exposure to others’ interpretations of this
article, accounted for how participants’ interpretations deviated from the control group’s
interpretation, r (3 7) = .36, p < .05. Experimental conditions and assessments of the
others’ credibility accounted for no additional variance (F < 1).

Attitude change. All participants’ attitudes toward a new statistical course
requirement, including those in the control group, became less favorable after reading a
newspaper article opposing a statistical course requirement (M change = -l .08, SD =

5.13), t (47) = -1.46, us. For those exposed to others’ interpretations, their deviations

37

from the control group’s interpretation was in the right direction of how their attitudes
toward employing ITAs changed, r (3 7) = .23, ns, but the correlation was within
sampling error of zero. The linear discrepancy model ﬁt these data well. The correlation
between participants’ initial attitudes toward this requirement and their attitude changes
was negative, r (38) = -.31. Additionally, the autocorrelation between the initial and ﬁnal
attitude reports was high (.83).

The two-step model: others’ interpretations inﬂuence how participants interpret
an article and participants’ interpretations, in turn, inﬂuence how they change their
attitudes toward the statistical requirement, coincided with these data, X2 (I, 38) = .32,
ns, RMSE = .02 (see Table 5 for corrected parameter estimates), although the error was
high. Whether participants majored in communication or some other discipline did not
affect this model (F < 1).

Additional effects. For those exposed to others’ interpretations, their initial
attitudes toward the new statistical course requirement ([3 = .24) and toward the
employment of international teaching assistants (B = .31) related to their ﬁnal attitudes
toward international teaching assistants, F (2, 37) = 4.81, p < .05, R = .46. In addition,
their initial attitudes toward the new requirement ([3 = -.20) and toward the new parking
plan, Vision 2020, (B = .65) related to their ﬁnal attitudes toward Vision 2020, F (2, 37)
= 16.74, p < .05, R = .70. Their attitude change toward the new statistical requirement did

not relate to any of their ﬁnal attitudes toward the other issues.

38

Statistical Requirement Support

Participants

Undergraduate students (it = 50) enrolled in communication courses at a large
Midwestern university participated in this study. On average, participants were 21 years
old (SD = 1.61), in their third year at the college (SD = 1.13), female (60%), and majors
in communication (77%).
Design, procedure, and instrumentation

The experimental design was a scope (wide or narrow) by distribution (negative-
skew or normal) factorial (n = 40), control-group (n = 10) design with random
assignment. Variation in the scope and distribution of others’ interpretations induced
differences in participants’ range and frequency values. Participants completed an
attitude survey before and after processing a newspaper article supporting a new
requirement to pass a statistical course before declaring communication as a major. The
procedures for this experiment replicate those used in Experiment I. All indicators passed
tests of unidimensionality (Hunter & Gerbing, 1982). Measurement validity and
reliability showed no signiﬁcant changes from Experiment 1.
Results

Participants in the control group rated this experimental newspaper article as
neutral toward a new requirement for student to pass a statistical course before they could
declare communication as their major (M = .75, SD = 6.94), t (8) = .28, ns. Participants
interpreted this article’s support of this statistical course requirement differently if they

read how 10 other (ﬁctitious) students interpreted this article. Participants in the

39

experimental conditions rated the ﬁctitious 10 students as credible (M = .34, SD = .37), t
(38) = 5.74, p < .05 without variation between experimental conditions (F < 1).

Article interpretation. The social inﬂuence hypothesis, see Figure 3, coincided
with these data, however the correlation resides within sampling error of zero. Their
predicted social inﬂuence score, the sum of frequency and range values developed from
each participant’s exposure to others’ interpretations ofthis article, did not account
signiﬁcantly for how participants’ interpretations deviated from the control group’s
interpretation, r (3 8) = .21, ns. Experimental conditions and assessments of the others’
credibility accounted for no additional variance (F < l).

Attitude change. All participants’ attitudes toward a new statistical course
requirement, including those in the control group, did not change after reading the
newspaper article supporting this requirement (M change = -.04, SD = 3.38), t (48) = -.08,
ns. Participants seemed to exhibit a different pattern for attitude change if they were in
the control group (M change = -1.80, SD = 3.05) versus the experimental group (M
change = .40, SD = 3.35); however, neither of these change scores signiﬁcantly differed
from zero.

For those exposed to others’ interpretations, their deviations from the control
group’s interpretation of the article did not predict how their attitudes toward a new
requirement changed, r (3 8) = -.06, us. Even though participants’ attitudes did not change
dramatically, the linear discrepancy model ﬁt these data well. The correlation between
participants’ initial attitudes toward the new statistical course requirement and their
attitude changes was negative, r (3 8) = -.43. Additionally, the autocorrelation between the

initial and ﬁnal attitude reports was high (.87).

40

Although the second path was inconsistent with the two-step model, the mediation
model coincided with these data, X2 (1, 39) = .42, ns, RMSE = .03 (see Table 5 for
corrected parameter estimates), but the error was high. In addition, a participant
characteristic did relate to the results. Participants with a communication major held more
favorable attitudes toward the new course requirement (M = .35, SD = 3.08) than
participants with other majors (M= -1.81, SD = 3.89) t (48) = 1.95, p < .05, r = .28.

Additional effects. Their attitude change toward the new statistical requirement
did not relate to any of their ﬁnal attitudes toward the other issues. This result differed
from participants’ responses to reading an article opposing the same requirement.

Meta-analytic results

Table 5 summarizes the two sets of correlations corrected for measurement
reliability (Hunter, Schmidt, & Jackson, 1982) from all the previous experiments,
including Experiment 1. The ﬁrst correlation represents the relationship between
participants’ predicted social inﬂuence scores (the average of their range and frequency
values) and their deviation from the control groups’ interpretations. The second
correlation represents the relationship between their interpretation deviations and their
subsequent attitude changes. Across newspaper articles, the predicted social inﬂuence
score exhibits a small inﬂuence (r Named = .08) on how participants’ interpretations
deviate from baseline interpretations, while participants’ interpretations exhibit a
moderate inﬂuence (r wwgmed = .19) on their attitude change. The variance in the
correlations between social inﬂuence and article interpretation varies enough to
investigate for a moderator (Hunter, Schmidt, & Jackson, 1982), X2 (2, 376) = 27.28, p <

.05. An article’s valence (support or opposition) seems to be a moderator, r (5) = .70, p <

41

.05. Splitting the experimental results by article valence decreases the variance between
correlations for articles opposing issues, but not those supporting issues.

For articles opposing an issue, the two-step model holds. Others’ interpretations
inﬂuenced how participants interpret an article differently from the control group (r
WWW: .30). Their interpretation deviations, in turn, inﬂuenced how they changed their
attitudes (r WWW: .30). The predicted model does not hold for newspaper articles
supporting an issue. The variance between the results of experiments using supportive
articles still exceeds variation expected from sampling error, X2 (2, 207) = 11.41, p < .05,
therefore other mediators probably persist’.

Discussion

These experiments tested if the two-step model of social inﬂuence replicated with
newspaper articles, which differed in their advocacy (supportive or opposing) and their
issue. For those participants who read articles opposing issues: employing international
teaching assistants and requiring a statistical course before declaring a communication
major, the two-step model held, thereby replicating Experiment 1. The sum of
participants’ range and frequency values, from their knowledge of other students’
perceptions of an article’s bias in addressing an issue, predicted how participants’
perceptions of an article’s advocacy differed from the control group. Their interpretation
deviations, in turn, predicted how their attitudes changed toward the article’s issue.

The two-step model was inconsistent with data from participants who read articles
supporting these same issues. In attempting to investigate this situation, one factor

emerged. Some participants, sometimes almost half of the sample, held very negative

 

3 The supportive articles also were separated into two groups based on the strength of their pre-existing
negative attitudes toward the article topics. This breakdown did not reduce variance between the studies.

42

attitudes toward the article’s issue. Even with splitting the sample on these pre-existing
attitudes, no consistent pattern of effects emerged. Sometimes knowledge of others’
perceptions inﬂuenced those with strong, negative pre-existing attitudes as predicted, but
other times others’ perceptions had the complete opposite effect. Without a consistent
pattern nor any prior reason to expect the causal model to fail with supportive articles,
this question remains for future research.

As a ﬁnal test of the causal model, and its theoretical premise, a ﬁnal experiment
tests if the strength of the predicted social inﬂuence varies as the ambiguity of the words
used within a newspaper article varies. According to this paper’s theoretical premise,
others inﬂuence how participants disambiguate the meaning of words. Some words
inherently present more ambiguity, or different possible meanings, than do others. If
words in a newspaper article possess more ambiguity, then others should be able to
inﬂuence how peOpIe interpret the words’ meaning. In contrast, if words in a newspaper
article possess less ambiguity, others’ interpretations should have little impact. To test
this fundamental assumption, the last experiment replaces words in one experimental

article with synonyms that possess more or less ambiguity.

43

Chapter 4: Varying Ambiguity

This experiment further tests if people use contextual information, such as
knowledge of how other people interpreted words, to disambiguate the words used in
these articles. The words in one newspaper article, advocating against the Vision 2020
parking plan, were replaced with synonyms that possessed more or less ambiguity. All
participants reviewed the same interpretations from 10 ﬁctitious students. When the
words in the newspaper article possess less ambiguity, knowledge of how others students
interpreted an article should have less inﬂuence on participants’ own interpretations.
When the words possess more ambiguity, knowledge of how others students interpreted
an article Should have more inﬂuence on participants’ own interpretations.
Participants

Undergraduate students (n = 34) enrolled in communication courses at a large
Midwestern university participated in this study. Participants were 22 years old (SD =
.85), in their fourth year at the college (SD = .26), female (77%), and drove cars on
campus (81%).
Design

The experimental design is single factor design (high ambiguity or low
ambiguity) with 17 participants randomly assigned to each condition. Participants
completed an attitude survey before and after processing a newspaper article opposing
Vision 2020. The experiment repeated the same procedure and instrumentation from

Experiment 1.

44

Procedure

The procedure for this experiment mirrored the one used for Experiment 1. Only
the words in the newspaper article varied between the two conditions. In order to vary
word ambiguity, the experimenter counted the number of dictionary entries, or possible
interpretations, for words within the text of article. Synonyms with more entries appeared
in the article with high ambiguity (from 7 to l 1 entries, with an average 9 entries);
synonyms with fewer entries appeared in the article with low ambiguity (from 1 to 4
entries, with an average 2 entries). In both articles, synonyms were provided for the same
words; thirty-six words (about 10%) were varied, see Appendix.

All participants read and categorized the same interpretations from other students.
These interpretations came from the wide scope and negative-skew distribution induction
in Experiment 1. All indicators passed tests of unidimensionality (Hunter & Gerbing,
1982). The measurement validity and reliability showed no signiﬁcant changes from
Experiment 1 or between experiments.
Instrumentation

Article advocacy. Participants indicated their interpretations of a newspaper
article’s advocacy of an issue with (a) an open-ended question, asking them how they
interpreted the article’s meaning and (b) three 9-point, semantic differential items. Items
asked participants to rate the extremity of the article’s advocated position on Vision 2020
with anchors, very favorable/very unfavorable, strongly like/{strongly dislike, and strongly
support/strongly oppose. A single summed score for article advocacy was generated, 12 =

strongly supported, -12 = strongly opposed, SI a = .97.

45

Attitude. Participants indicated their attitudes toward Vision 2020 and other issues
covered in their local paper on three 9—point, semantic differential items for each issue.
Items asked participants how they felt about an issue, e.g., Vision 2020 with anchors,
very favorable 'very unﬁrvorable, strongly like strongly dislike, and strongly
support»Strong/y oppose. A single summed score for each issue was generated, 12 =
strongly supported, -12 = strongly opposed (average SI a = .97). The change scores were
used, (Vision 2020, S] a = .90; Trustee proposal, S] a = .91; Course requirement, S] a =
.92; Parking facilities, SI a = .97; International teaching assistants, S] a = .98; Advising
office, SI a = .97; Non—motorized transportation, SI a = .93; Diversity on campus, SI a =
.99; Science classes, S] a = .61).

Range and frequency values. Participants scaled what bias others, labeled with
letters “a” through “j” to retain anonymity, thought an article exhibited on three 9-point
semantic differential items with anchors, very ﬁrvorable/very unfavorable, strongly
like/strongly dislike, and strongly supportstrotrgly oppose. A single summed score for
each person was generated, 12 = strongly supported, -12 = strongly opposed, (a SI 0: =
.97;bSIa=.97;cSIa=.98;d SIa=.97;eSIa= .97;fSIa=.98;gSIa=.97;hSla
= .97; i SI a = .98;j SI (1 = .97). Range and frequency value calculations matched those
performed in Experiment 1.

Others ’ credibility. Participants indicated the credibility of each of the others who
interpreted their newspaper article on a single 5-point scale, 5 = very credible, 1 = very

uncredible. These scores were rescaled, 2 = very credible, -2 = very uncredible.

46

Source attribution. Participants identiﬁed who they thought wrote their newspaper
article in an open-ended question. This information does not appear in the analyses, but is
available upon request.

Results

Participants in the control group rated this experimental newspaper article as
Opposing Vision 2020 (M = -2.24, SD = 7.1 1), but within sampling error Ofa neutral
rating, t (32) = -1.83, ns and Experiment 1. Participants interpreted a newspaper article’s
opposition to Vision 2020 differently if they read how 10 other (ﬁctitious) students
interpreted this article. On average, participants reading others’ interpretations moved
25% up or down the scale used to index the bias represented in the newspaper article.
Participants in the experimental conditions rated the ﬁctitious 10 students as credible (M
= .20, SD = .33), t (32) = 3.51,p < .05 without variation between experimental conditions
(F < 1).

Article interpretation

The social inﬂuence hypothesis, see Figure 3, coincided with these data. Their
predicted social inﬂuence score, the sum of frequency and range values developed from
each participant’s exposure to others’ interpretations of this article, accounted for how
participants’ interpretations deviated from the control group’s interpretation. Those
reading the article with ambiguous synonyms showed a strong correlation between their
social inﬂuence score and how their interpretations deviated from the control group, r(15)
= .64, p < .05. Those reading the article with unambiguous synonyms showed a small
correlation, within sampling error of zero, between their social inﬂuence score and how

their interpretations deviated from the control group, r (15) = -.07, us. As predicted,

47

words with more inherent ambiguity enhanced the social inﬂuence; words with less
ambiguity reduced this inﬂuence. Experimental conditions and assessments of the others’
credibility accounted for no additional variance (F < l).

Attitude change

Across conditions, participants’ attitudes toward Vision 2020 did not change after
reading a newspaper article opposing Vision 2020 (M change = .70, SD = 4.35), t (32) =
.92, ns. Their deviations from the control group’s interpretation of the article predicted
how their attitudes toward Vision 2020 changed, r (32) = .41, p < .05. The linear
discrepancy model ﬁt these data well. The correlation between participants’ initial
attitudes toward Vision 2020 and their attitude changes was negative, r (32) = -.28.
Additionally, the autocorrelation between the initial and ﬁnal attitude reports was high
(.81 ).

The two-step model was tested only for those reading the ambiguous article,
because the ﬁrst link diminished, as predicted, with the unambiguous article. For these
participants, others’ interpretations inﬂuence how participants interpret an article
(corrected r (15) = .65) and participants’ interpretations, in turn, inﬂuence how they
change their attitudes toward Vision 2020 (corrected r (15) = .30), coincided with these
data, X2 (1,16) = .01, ns, RMSE = .00. Whether participants drove cars on campus or not
did not affect this model (F < 1). Although not predicted, when looking between
conditions, the relationship between interpretation deviation and attitude change was
stronger for those who read the unambiguous article, r (15) = .56, p < .05, versus those

who read the ambiguous article, r (15) = .28, ns.

48

Additional effects

Their initial attitudes toward Vision 2020 did not relate to any of their ﬁnal

attitudes toward the other issues. This result differed from Experiment 1.
Discussion

The two-step model presented in this paper rests on a fundamental assumption:
ambiguity matters. If people use contextual features to disambiguate the meaning of
words in a message, then knowledge of others’ interpretations should only inﬂuence
participants’ own interpretations to the degree to which these words possess some
ambiguity. In this experiment, when the words in one newspaper article were replaced
systematically by words with less ambiguity, i.e., fewer dictionary entries, contextual
information should have less inﬂuence; words that are more ambiguous should
necessitate greater use of contextual information.

This assumption coincided with the data. The relationship between participants’
range and frequency values, from their knowledge of other students’ perceptions, and
how participants’ perceptions of an article’s advocacy differed from the control group
changed in relation to word ambiguity. The relationship increased with the ambiguous
synonyms and virtually disappeared with the unambiguous synonyms. As ambiguity
increases, participants do seem to depend more on contextual features as they determine
the extremity of a given message’s advocated position toward an issue. This experiment’s
ambiguous condition exhibited the strongest impact of this type of social inﬂuence across

all the previous experiments.

49

Chapter 5: Discussion

When words in messages possess ambiguity, people must use some contextual
information to disambiguate their meaning. Knowledge of how other people
disambiguated these words may be one such contextual feature. Over sixty years ago
Asch wrote that social inﬂuence may not just change how people evaluate objects, but
inﬂuence what objects people think may be under evaluation. Psycho-physics theories
were used in an attempting to develop a two-step model to predict how others might
inﬂuence people’s message perceptions in this way. The proposed two-step model makes
predictions, which often differ from other models of social inﬂuence, e. g., conformity.
When tested in multiple experiments, the two-step model coincided with how
experimental participants interpreted newspaper articles and subsequently changed their
attitudes within two boundary conditions. First, the articles needed to present a negative
bias toward the issues they were addressing. Second, the words in the newspaper article
needed to possess some ambiguity. The second boundary condition was anticipated
theoretically as an underlying assumption of this type of social inﬂuence. The ﬁrst
boundary condition was unexpected.

One reason why the two-step model failed to predict reactions to the articles that
presented a favorable bias may have to do with the choice of issues. Foremost these
issues: course requirements, parking plans, and teaching assistants, all pertain to
university administrative decisions. Participants reading the articles supporting these
issues were more likely to guess that the author was an administrator than those reading
the articles opposing these issues. It is possible that participants did not elaborate as much

on articles, which they might have believed to be propaganda from university

50

administration, versus appeals from their fellow students. Other contextual features that
might vary how much people would elaborate on the message itself Should be
investigated in future research.

The cognition limitation begs yet another point: ambiguity in messages may relate
to the cognitive load people hear when reading messages. Persuasion theories that focus
on how different amounts of cognition affect persuasive outcomes may be bounded by
the amount of ambiguity within the message itself.

Across these experiments, determining if changing people’s attitudes toward one
issue also affects their attitude toward other issues remains unclear and inconsistent. One
reason for this lack of clarity may be the short time span that elapsed between the ﬁrst
attitude report and the ﬁnal attitude report. On average, 20 minutes lapsed between the
two reports. This amount of time may simply be too short to allow related attitudes to
change. In addition, experiments with longer durations of time between observations may
provide insight into how long these attitude changes may sustain.

Interestingly, participants evaluated the other students who read the newspaper
article before they did as relatively credible. Future research should vary the credibility of
others providing their interpretations to see if credibility plays a role in this type of social
inﬂuence. The question remains if anyone might serve as a source to disambiguate a
message or this type of social inﬂuence is bounded others’ credibility.

Limitations

At least three features of these studies limit their internal and external validity:

issues, time, and ambiguity measure. The concerns with the issues chosen for these

articles and the short duration between pre and post testing were addressed previously.

51

The ambiguity measure, using the number of entries for each word in the dictionary, is a
blunt tool. This method of indexing ambiguity does not address qualitative differences in
the type of entries. For example, the word “strong” has twenty-one entries, while
“cleave” has two. The entries for “strong” are all relatively similar, e.g., physically
powerful, force of character, or effective exercise of authority, etc., however, the entries
for “cleave” are direct opposites, i.e., to adhere together or to split apart. In this case, the
need to disambiguate a word like “cleave” from two opposite meanings may be more
critical than disambiguating the shades of gray in “strong.” Without addressing this
component of the words used in these messages, the conclusions drawn from these
studies are limited.

Future research and implications

The next studies to build on this research will address real others, new issues, and
consequences for c0gnitive theories of social inﬂuence. In order to improve ecological
validity, these studies will be replicated with people providing their interpretations Ofa
newspaper article, in person. Although some applied circumstances provide anonymous
authors for interpretations, e.g., those peer reviewing a medical malpractice suit may see
how other doctors interpreted the situation (as malpractice or not) before they read the
case, themselves, most likely this information would be provided in person.

In these future studies, additional efforts will be taken to seek out issues that seem
to be sponsored by the reader’s peer group. In these studies, most participants thought
that a peer was the author of the oppositional articles, while administrators were the
authors of the supportive articles. As Stated earlier, the suspected author of the article

may also help disambiguate these articles in ways that currently were not addressed. If

52

using different issues does help to discover why the model failed with supportive articles,
attempts to disentangle mediators and moderators will be pursued.

Last, this line of research may provide insight into existing theories. As stated
earlier, the amount of cognitive work implied in disambiguating words in a message may
impact dual-processing theories of persuasion (e.g., ELM or HSM, see Eagly & Chaiken,
1993 for a review). When people need to look to contextual cues to disambiguate words
in a message, they may attend to these ‘peripheral’ cues more than if they do not need to
disambiguate the message. The need to disambiguate a message may also make
processing the message feel more difﬁcult, thereby qualifying the potential utility,
credibility, and one’s involvement with the message’s content. On the other hand, people
may elaborate more on the words and content of the message, because they need to
disambiguate the message, potentially encouraging more central processing. Future
research may be able to clarify when and how message ambiguity may interact with
cognitive models of persuasion.

In addition, a theory of organizational communication, strategic ambiguity
(Eisenberg, 1984), may be impacted. The idea behind strategic ambiguity is to use
symbols for organizational values that inherently possess some ambiguity so that
employees may make individual interpretations of these values and think that other
employees share these values. This suggestion attempts to balance maximum
individuality and organizational cohesion. Other researchers suggest messages like PSAs
should be designed with strategic ambiguity (DeJong, Wolf, & Austin, 2001). These

studies and future work should provide explanatory and pragmatic guidance for how

53

messages may be designed with strategic ambiguity and the consequences ofthis strategy
for message effects.

The ﬁnal experiment provides insight into an interesting decision for message
designers. Unambiguous messages may inﬂuence attitude change more noticeably than
ambiguous messages. Participants’ attitude changes after reading the unambiguous
message were considerably higher than the changes evidenced in ambiguous
experimental conditions. Although an ambiguous message might seem like a reasonable
alternative to message designers who do not want to seem didactic, they might be missing
out on greater attitudinal change.

In sum, the two-step model articulated within this paper showed promise for
accounting for a speciﬁc type of social inﬂuence. Sometimes, other people may serve a
role to disambiguate the meaning of words within a message, thereby inﬂuencing what
message people will process. By altering what message people process, a subtle form of
persuasion may be produced. This persuasive effect should continue until a new set of
circumstances stimulates one to re-evaluate the message’s meaning. This two-step model
may begin to provide an explanation for why ambiguous messages produce unexpected
results; when other individuals, who control word of mouth, can spin a message’s

interpretation.

54

APPENDIX

55

Table 1

Summary of Scale Means, Standard Deviations, and Reliabilities in Experiment 1

 

 

 

 

 

Time 1 Time 2 Change
Variable Sla M SD Sla M SD Sla M SD
Vision 2020 .98 -1.43 6.87 .99 -4.58 7.39 .95 -2.46 5.61

Trusteeproposal .99 4.55 7.15 .99 4.18 7.14 .86 -0.38 2.69

Course

. .98 0.58 5.72 .98 0.35 5.42 .92 0.04 3.08
requrrement

Parkingfacilities .98 -4.10 7.40 .99 -4.88 6.66 .94 -0.68 3.50

International
teaching .97 -I83 4.91 .97 ,-0.28 5.78 .95 1.36 4.94

assistants
Advisingofﬁce .97 3.80 4.28 .98 3.08 5.96 .93 -0.50 3.94

Non-motorized

. .97 3.55 5.98 .97 3.23 6.14 .96 0.06 4.83
transportation

Diversity on
campus

.99 7.45 4.25 .99 7.43 4.38 .86 -0.08 1.95

Scienceclasses .92 -1.40 7.1.5 .95 -1.03 7.14 .86 0.22 3.90

 

56

Table 2:

Descriptive statistics of others’ interpretations by experimental conditions.

 

 

Narrow Wide
Normal Negative Skew Normal Negative skew
Max 1.8 1.2 4.5 5.0
Min -7.5 -7.0 -11.0 -9.5
Num positive 5 7 5 7
Num negative 5 3 5 3

 

Note. This message’s content was rated at -2.90. The narrow condition spans four points
above and below the content; the wide condition spans seven points above and below the

COIIICIII.

57

Table 3

Summary of Newspaper Article Interpretations by Condition in Experiment I

 

 

Scope
Distribution Narrow Wide Control

Skewed

M -7.10 -1.70 -2.90

SD 5.86 7.24 7.11

n 10 10 10
Normal

M -l.10 -3.30

SD 6.35 4.88

n 10 10

 

58

Table 4

Scale Means, Standard Deviations, and Reliabilities for Variables in Replications

 

 

 

 

Support Opposition
V2020 ITA SR ITA SR

Newspaper article

M (SD) 6.75 (4.97) 9.34 (4.19) 4.60 (5.12) —8.49 (4.57) -3.04 (5.98)

SI (1 .98 .96 .98 .95 .94
Vision 2020

M(SD) 2.62 (5.47) -0.19 (4.99) -I.36 (4.23) -0.50 (4.12) -.71 (4.79)

SI (1 .93 .92 .95 .91 .93
Trustee proposal

M (SD) 0.11 (3.60) -1.21 (4.06) -040 (2.81) -0.55 (3.97) -013 (4.13)

SI 01 .80 .91 .87 .94 .63
Course requirement

M (SD) 0.43 (3.67) 0.02 (3.78) -004 (3.38) -0.44 (3.29) -l.08 (5.13)

SI (1 .89 .93 .88 .89 .94
Parking facilities

M (SD) -0.04 (5.17) -0.06 (4.44) -0.76 (3.01) ~0.77 (4.94) 0.48 (4.12)

SI 01 .88 .89 .85 .93 .93
ITAs

M (SD) 0.83 (4.46) 2.85 (4.86) 0.92 (3.79) -1.75 (5.27) -0.83 (5.21)

SI 01 .92 .94 .95 .93 .95
Advising ofﬁce

M (SD) 0.57 (3.79) 0.02 (4.38) 0.36 (4.06) -0.55 (4.21) 0.13 (2.45)

S] or .87 .95 .96 .95 .85
Non-motorized
transportatron

M (SD) -0.33 (3.56) 0.15 (3.85) -0.66 (3.01) 0.05 (3.74) 1.10 (4.80)

SI (1 .92 .94 .92 .91 .93
Diversity on campus

M (SD) -0.89 (4.07) 0.04 (3.07) -0.04 (3.37) -0.98 (3.17) 0.31 (3.25)

SI 01 .93 .95 .94 .95 .85
Science classes

M (SD) 0.08 (3.08) 0.26 (3.13) -0.83 (4.96) -0.76 (3.29) -0.37 (3.86)

SI (1 .77 .61 .92 .73 .79

 

Note. All attitudinal variables (this excludes the newspaper article variable) are change scores.

59

Table 5

Summary of Correlations between Social inﬂuence, Interpretations, and Attitude Change

 

 

 

 

rPSI,AI {31.5.4 ’7
Opposition
Vision 2020 ‘45 .44 40
ITA .19 .25 90
Course .38 .26 39
r weighted .30 .30 169
s,’ .01 .01
(Yr .06<r,,.<.53 .06<rw<.54
Suppon
Vision 2020 .08 .30 74
[TA -.33 .04 96
Course .21 -.07 40
r MW...) -.08 .1 1 210
Sr: .05* .02
Clr -.32<rw<.15 -.12<r ,,.<.34
Total r WM...) .08 .19 379
3,? 07* .02
CH -.16<r,,.<.33 -.04<rw<.43

 

Note. r p31, .31 = corrected correlation between predicted social inﬂuence score and

deviation of interpretation from baseline. rAI, A A = corrected correlation between

deviation of interpretation from baseline and attitude change.

*p < .05, variance between studies outside of sampling error

60

 

Figure I : Optical illusion: two women may be seen within the same picture.

61

XX XXXXX XXXX

 

 

 

 

 

 

 

 

 

 

 

M1 M2
Ilititifl ittl Ii’rllli‘ri Iiiiliiiiit
-5 -4 -3 -2 -1 0 1 2 3 4 5
Against Vision 2020 Supporting Vision 2020

Figure 2: Distribution of others’ interpretations (each one is designated by an ‘X’) of two
articles’ advocated positions for or against Vision 2020. The two arrows represent the
two articles’ advocated positions when their respective content is evaluated in the most

objective or context-free of circumstances.

62

 

Predicted
social inﬂuence

 

.45

 

 

Figure 3: Graphical depiction of the two-step model under investigation. The predicted

 

 

Inﬂuenced article
interpretation

.44

 

 

 

 

Attitude
change

 

x2 (1,39) = .01, ns, RMSE: .00

social inﬂuence score, a combination of range and frequency values, inﬂuences how

participants’ interpretations of the newspaper article’s bias toward Vision 2020 deviated
from the control group. The participants’ deviations from the control group predict how

their attitudes changed toward Vision 2020. Corrected parameter estimates and goodness-

of-ﬁt indices from experiment 1 are presented.

63

 

Sample Survey
Evaluating stimulus materials

In this study, we are asking you to help us evaluate some newspaper articles and how
others have interpreted these articles in order to develop stimulus materials for another
experiment. We are asking you to evaluate other students’ interpretations and the article
those students read, and to provide us your opinions about a few topics. This study has
been developed by researchers in the Department of Communication at Michigan State
University. Participation in this study should not take more than 15-20 minutes to
complete.

Your participation is strictly voluntary and you may stop at any time. In order to provide
you research credit, please sign and print your name at the bottom of this consent form.
Do not put your name on the questionnaire. Your answers on the questionnaire will be
completely conﬁdential. Your privacy will be protected to the maximum extent allowable
by law.

Your participation is voluntary. You may choose not to participate at all, or you may
refuse to participate in certain procedures or answer certain question or may discontinue
at any time without penalty or beneﬁts to which you are otherwise entitled.

If you have any questions about this study, please contact the investigator, Frank Boster,
355-1514. If you have questions or concerns regarding your rights as a study participant,
or are dissatisﬁed at any time with any aspect of this study, you may contact —
anonymously, if you wish — Ashir Kumar, M.D., Chair of the University Committee on
Research Involving Human Subjects (UCRIHS) by phone: (517) 355-2180, fax: (517)
432-4503, e-mail; ucrihs@msu.edu, or regular mail: 202 Olds Hall, East Lansing, MI
48824.

Your signature below indicates your voluntary agreement to participate in this
study.

 

Signature Date

 

Printed name (please make it as legible as possible)

 

PID

Please do not write your name on the survey materials. This consent form will be kept
separate from your survey answers in order to protect your privacy.

64

This study’s focus is to obtain interpretations of a newspaper article in order to
construct stimulus materials for a future study. Before we get started, we need to
know what opinions you might have about issues that these articles may cover.
Please provide your opinions on all three scales for each of the following issues. By
marking a space closer to either end (e.g., very favorable) indicates that you feel
stronger than if you mark the spaces closer to the middle. For example, if I marked
how much I really like Granny Smith apples...

Granny Smith Apples

1. very favorable X very unfavorable

Please provide your opinions about the following issues

A. Vision 2020: a plan to establish perimeter parking around campus and
rely on quick mass transit rather than front-door parking

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

B. Trustee proposal to reimburse students that cannot understand their
Professors or TAs up to four weeks before the end of the semester.

very unfavorable

strongly dislike

1. very favorable

——_———.———-

2. strongly like

3. strongly support _ strongly oppose

C. The new requirement to pass Communication 200 ﬂommunication
Research Methods) before being allowed to declare communication as a
major.
I. very favorable very unfavorable
2. strongly like strongly dislike

3. strongly support strongly oppose

D. The cost, availability, and conditions of parking student cars on
cam US.

1. very favorable very unfavorable
2. strongly like strongly dislike

3. strongly support _ strongly oppose

 

Please turn the page over...

 

 

 

65

- . strongly support

- . strongly support

- . strongly support __

E. Taking classes with international teaching assistants teaching the lab,
discussion, lecture orgradingstudent assignments.

. very favorable

.—.—--——n.

. strongly like

. strongly support __

very unfavorable

strongly dislike

strongly oppose

F. The quality. care, and competence of undergraduate student advising
staff, procedures, and department.

. very favorable

. strongly like

———————

very unfavorable
strongly dislike
strongly oppose

G. The use of non-motorized transportation (walking, biking, skating,

blading, etCIto places on or off campus

. very favorable

. strongly like

H. Exposed to diversity on campus:

. very favorable

. strongly like

very unfavorable
strongly dislike
strongly oppose

diversity in ethniCLracial, cultural, and
linguistic backgrounds of students. faculty. and staff.

very unfavorable

strongly dislike

strongly oppose

1. Taking classes covering mathematical, statistical, or scientiﬁc content.

. very favorable

. strongly like

. . strongly support _

very unfavorable

strongly dislike

strongly oppose

Once you have completed marking your opinions, please turn this form
into the research staff and retrieve the last form.

66

Part 11:
Creating stimulus materials: evaluating how others read the stimulus

In this last form, we are looking for your help with the development of stimulus materials for a
future study. In an earlier study, we asked 10 other students to read a section of a newspaper
article. Each of the 10 students wrote down what theLthought the article was advocating, in other
words, they wrote down if they interpreted the article as favorable, unfavorable, or neutral toward
Vision 2020. They were asked not to write down if they personally liked the article, but to capture
what opinion or bias (if any) might be presented in the newspaper article.

 

We would like you to read their interpretations and then rate them on a scale that YOU develop.

111 order to develop your scale, use the provided line (on the next page) and mark where you think
each response falls along the continuum from showing a bias in favor or in opposition toward
Vision 2020 (note, you can mark multiple responses in the same place). After you ﬁnish
arranging their interpretations. identify the most extreme student interpretations (the ones furthest
to the left and furthest to the right). Once you identify these interpretations, then label them as
“neutral. opposed, or favorable” and qualify whatever you choose with “very, moderately, or
mildly.”

For example, if I had to rate fruit (apples (1), grapes (2), strawberries (3), cranberries (4), and
blueberries (5)) from blue to red, I might make the following scale.

 

 

 

3
5 2 4 l
Moderately Very
Blue F arthest I wrote “very red” to describe RCd
\ score to the farthest scores to the right: /
left apples (1) and strawberries (3)

 

 

 

 

 

 

On the next page, instead of “Blue” and “Red” you will mark the interpretations as either
“Favored, Opposed, or Neutral” then add modiﬁers of “Very, Moderately, or Mildly”. For
example, if someone (B) had written “I think the author kind of likes blueberries” as the most
negative comment toward fruit, I might make this scale, placing B on it:

 

B
Mildly Very
Favored Favored

Understand? If not, stop, raise your hand and ask for a researcher to assist you before
turning the page over. If you do understand, please turn the page over to develop your
own scale.

67

VCN

Here are the previous students’ interpretations of the newspaper article.

a.

$7

9.0

0

In my opinion, the article was a little against taking out the parking and
constructing campus like Vision 2020.

I don’t think this article is taking a stand on either side of the Vision 2020 debate.
The article was completely critical of making Vision 2020 happen.

I don’t think they are for or against Vision 2020.

They mildly oppose putting through Vision 2020 at MSU.

I believe the article is a balanced view toward Vision 2020 without a bias in
either direction.

They are basically saying, Vision 2020 never should occur.

I think the article is hostile toward having perimeter parking, in other words
Vision 2020.

It is deﬁnitely against us putting Vision 2020 into place.

I believe the article is neutral about developing campus within the Vision 2020
plan.

 

 

Neutral, Opposed, Favored

 

 

 

Very, Moderately, Mildly

 

 

When you are done please turn the page over.

68

Now, please rate the same interpretations on three standardized scales. Please use a check
mark on the following items to scale their interpretations (not your opinion about their
interpretations).

For example, someone might rate an interpretation like this. . . ..
“She seems to really like granny smith apples”
1. very favorable _ X _ very

_—_—_—-———-—

unfavorable

a. In my opinion, the article was a little against taking out theparking and

constructing cangJus like Vision 2020.
1. very favorable

 

very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

b. I don’t think this article is taking a stand on either side of the Vision
2020 debate.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

c. The article was completely critical of making Vision 2020 happen.

very unfavorable

I. very favorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

d. I don’t think they are for or against Vision 2020.

1. very favorable very unfavorable

2. strongly like strongly dislike

—.——————————.—_

3. strongly support _ strongly oppose

e. They are basically saying, Vision 2020 never should occur.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

69

f. They mildly oppose putting through Vision 2020 at MSU.

 

I. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

g. I believe the article is a balanced view toward Vision 2020 without a
bias in either direction.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

h. I think the article is hostile toward having perimeter parking, in other
words Vision 2020.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

i. It is deﬁnitely against us putting Vision 2020 into place.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

j. I believe the article is neutral about develoging campus within the
Vision 2020plan.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

Now that you have rated the other students’ interpretations of our stimulus message,
please tell us how credible you think each of the authors are. Next to each of the

numbers below, please rate the author of the previous statement with the same number.
5 = Very credible, 4 = Somewhat credible, 3 = Neutral, 2 = Somewhat uncredible, l = Very uncredible

a. e. h.
b. f i.
c. g. j.
d.

70

Now, please read the newspaper article that everyone else was rating.

The Vision 2020 plan calls for the removal of parking lots along Shaw Lane to make way
for green space and academic structures. West circle dorms, the ivy-covered gothic buildings,
would be demolished. The plan is to remove all parking from central campus and move parking
to remote campus areas, such as Farm Lane and Mount Hope Road.

Unfortunately, parking has been, one of the biggest infrastructure problems faced by
students, faculty, and staff members for years. New problems seem to arise each year, as more
students arrive on campus. No major parking facilities are available on the north side of campus,
and any larger campus ﬂat lots exist only on far reaches of campus. Students have to pay extra to
park their cars in a lot that is over 10 minutes away from their dorm. Commuters have to buy a
pass just to get a discount at the commuter lot.

Vision 2020 proposes to create a 1,300-space parking lot on Harrison Avenue where
Michigan State Police headquarters is located. With the state police headquarters relocated, some
people fear that campus safety may be compromised. Many students argue that it is not safe to
walk to a bus stop or a parking lot far from the center of campus after working late hours. They
argue that reliable public transportation does not exist, currently

Vision 2020 planners rejected suggestions to convert visitor parking to student lots.
“Visitor lots contribute signiﬁcant revenue to the system,” he said. “That revenue is what keeps
teaching assistant and faculty parking costs reasonable. To build more ramps would be incredibly
efﬁcient, but incredibly expensive.” Places like the Spartan Stadium surface lot, Trowbridge
Road parking ramp, the commuter lot at Mount Hope Road and Farm Lane and others will be
needed to make the 2020 plan work. The trend of creating larger plots for black, endless seas of
pavement in the far reaches of campus has offered little solution to the parking problems on
campus.

Think about whether you think the article supports or opposes Vision 2020. What
stance do you think the article sponsors, in your own words (i.e., your
interpretation)?

Just to make sure we have your evaluation in both formats, please rate what stance
you think the article advocates, concerning Vision 2020, on the following scales:

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

Please write down who you think was the newspaper article’s author (this could be
anyone):

71

Finally, although we realize you have done this once, please mark your opinions
about the following topics.

A. Vision 2020: a plan to establish perimeter parking around campus and
rely on quick mass transit rather than front-door parking.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

B. Trustee proposal to reimburse students that cannot understand their
Professors or TAs up to four weeks before the end of the semester.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support _ strongly oppose

C. The new requirement to pass Communication 200 (Communication
Research Methods) before being allowed to declare communication as a

major.

I. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support strongly oppose

D. The cost, availability, and conditions of parkig student cars on
cam us.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

E. Taking classes with international teaching assistants teaching the lab,
discussion, lecture or grading student assignments.

1. very favorable very unfavorable

2. strongly like strongly dislike

3. strongly support __ strongly oppose

F. The quality, care, and competence of undergraduate student advising
staff, procedures, and department.

1. very favorable very unfavorable

2. strongly like strongly dislike

strongly oppose

3. strongly support __

72

G. The use of non-motorized transportation (walking, bikinggskating,

 

blading, etc.) to places on or off campus

I. very favorable

2. strongly like

3. strongly support

H. Exposed to diversity on campus:

very unfavorable

strongly dislike

————_

strongly oppose

diversity in ethnic, racial, cultural, and

linguistic backgrounds of students,faculty, and staff.

1. very favorable

———

2. strongly like

3. strongly support _

very unfavorable

strongly dislike

strongly oppose

1. Taking classes covering mathematical, statistical, or scientiﬁc content.

1. very favorable

2. strongly like

3. strongly support _

very unfavorable
strongly dislike
strongly oppose

Last, please ﬁll out some information about yourself

Year in school: freshman
Age: Sex:
Are you an international student?
Do you drive on campus?

Are you a communication major?

 

sophomore junior senior other
Male Female

Yes No

Yes No

Yes No

If you have any ﬁnal comments about our stimulus materials, please feel free to provide

them.

73

Other Messages

Vision 2020 PRO

The future of MSU’s campus has become clearer. Anticipating the completion of the
second component of the 2020 Vision project, university officials released maps and
information that outlined what campus may look like two decades from now. The 2020
Vision parking plan is to establish perimeter parking around campus and rely on quick
mass transit rather than “front-door” parking.

Some of the most valuable land is at the center of campus, and it is used for parking lots.
South campus should look similar to north campus 50 years from now. It does not have to
be asphalt. Even now, many students are frustrated with the lack of parking because they
get tickets all the time. Parking structures can blend into campus to make it look beautiful
in a park-like setting.

“It is important we maintain the beauty of campus,” he said. “We have done a fabulous
job on the north side and we are aggressively working on the area south of the Red
Cedar.” Although most changes will not impact current students, they should take an
interest. “We are looking at how our campus will look in 20 years,” he said. “By that
time, they will be alumni, but they will be interested in what we do and how it looks.”

Improvements in parking and transportation are also part of the plan, which calls for
more parking ramps on campus and the addition of ramps adjacent to MSU. The project
aims to accommodate facility growth, expand green and open space and balance vehicle
trafﬁc with a pedestrian environment. “We are attempting to create the most creative and
stimulating area for people to learn: a park-like quality and a naturally occurring
landscape.” he said. The plan also calls for new bicycle pathways, which will include
bike lanes in roadways and 4-foot-wide paths separate from walkways.

ITA CON

It is difﬁcult because students need help and are not getting the teachers who can help
students out the most. Charging $180 an hour per semester credit, all semester long, is a
long time and a lot of money. Students should not have to pay for a class with a teacher
they cannot understand.

First off, approaching the instructor is of little good when you cannot understand them in
the ﬁrst place. Is it the students’ fault that most of the teaching assistants are
international? Accents are a barrier, even if the TAs can pass English speaking and
writing tests.

As for the screening test, it is hard to believe they are effective when ITAs may speak
English ‘proﬁciently’, they just do not understand much when students speak it to them.
An ITA may be able to explain a lab, even grade effectively, but when students have
questions for which an ITA was not prepared, everyone gets lost. If the university sits
down and thinks about language ﬁrndamentals for about two seconds, they would realize
that teachers need to understand as well as speak the language they are using.

74

Students are stressed out by the work it takes to get ‘help’ from international TAs —— it can
require hours longer to ﬁgure out problems. That extra stress was not a part of the
original purchase of the course credit hours, and other students, with domestic TAs, get
more teaching per dollar, which is not fair.

ITA PRO

Rubbing shoulders with other cultures in the classroom is a part of the value of being at a
university. Learning to understand different accents, learning styles, explanations for an
event, and worldviews is an important exercise for every student, in every discipline.

Isn’t that why students go to University, so they can meet people with different opinions,
different ways of doing things? Most students attune themselves to accent differences
quickly: whether the accent comes a person living previously in Russia, China, New
York, or Louisiana.

Many of our international teaching assistants are experts in their content area in order to
get sponsorship to study at our university and they are willing to teach our students -
some of the most intelligent, skilled, and knowledgeable people, world-wide. These
teachers can improve the quality of undergraduate education in direct (great command of
the course material) and indirect (sharing a diversity of perspectives) ways, thus
enhancing the reputation of the students, their education, and the institution from which
their degree is conﬁrmed.

Many Americans are ignorant of the rest of the world - but our students have the
opportunity in class to learn about different countries and cultures, so they will be more
marketable and well-rounded graduates.

Corn 200 CON

MSU students in statistics and mathematics classes have a tradition of having a harder
time with their courses. University ofﬁcials admit grades for statistics and math classes
are often lower than for other courses, if the students even pass. Communication 200, for
example, is basic statistics and research methods course. Most students repeat the course
in order to pass. The failure rate is alarming, and many blame the teachers’ and
department’s shortcomings for students’ poor performance.

Department ofﬁcials urge students to talk to their professors when they need help,
however, sometimes these professors are harsh and unwilling to help. Two students may
take the same course, but have professors who organize their classes differently. This
results in an unorganized, careless department and opens the possibility for each
professor to teach either harshly or easily. If professors taught a standard curriculum, then
perhaps students may go to other students for help as an alternative if they still do not
understand what the professor has to say.

Students do not often understand why they are taking the course they have enrolled in.
Students complain they will never need the material they are learning. If the university
can not explain how these requirements apply to students’ lives after MSU, then perhaps

75

there should be a different requirement. One student grinding through Communication
200 last semester heard another MSU professor remarked he had not used any of the
material since he was in college.

In every department there are going to be those who do not see how a particular subject is
going to be relevant to the rest of their lives. The fact is, between the department and
student advisers, there has been a failure to help students excel in this area. Instead of
accepting that math grades are generally lower than grades in other subjects, ofﬁcials
could take steps to ﬁnd out why this is so and rectify the situation.

Com 200 PRO

MSU students in statistics and mathematics classes have a tradition of having a harder
time with their courses than they should. University officials admit grades for math
classes are often lower than for other courses, if the students even pass. The failure rate is
alarming, and many blame the teachers’ and department’s shortcomings for students’
poor performance. But the blame should not lie on the university alone.

Communication 200, for example, is basic statistics and research methods course. The
average person should have some knowledge regarding this content before they arrive in
college. And despite what some may want to believe, basic statistics and research does
get used in day-to-day living.

Department ofﬁcials, including those in Communication, urge students to talk to their
professors when they need help. Some students say their professor is hard to deal with or
cannot be understood. There are many ways for students to get around this obstacle,
ranging from the Math Learning Center to simply sitting down with the TA or professor
during ofﬁce hours. The responsibility merely lies on the students to actually use them. In
the same vein, many students readily admit to simply not doing the homework or not
taking advantage of the extra avenues of assistance that are made available. Students need
to make sure they use the help they have access to and actually do the work, instead of
simply brushing it aside. The theory that practice makes perfect can hold true here as
well.

The university needs to do a better job of teaching this material, standardizing classes,
and making the purposes of the curriculum known to students. Instead of accepting that
math grades are generally lower than grades in other subjects, MSU and its students need
to shoulder some of the responsibility together for the students’ success in math and
statrstrcs.

Con Vision 2020: vague (direct)

76

The Vision 2020 plan involves clearance (necessitates removal) of parking lots along
Shaw Lane to allow (make way) for green space and academic structures. West circle
dorms, the ivy-covered gothic buildings, would be demolished. The plan is to clear
(removes) all parking from central campus and move (relocates) parking to distant
(faraway) campus areas, such as Farm Lane and Mount Hope Road.

Unfortunately, parking has been, an (the leading) infrastructure problems faced by
students, faculty, and staff members for years. New problems seem to start (begin) each
year, as more students arrive on campus. No major parking lots are open (available) on
the north side of campus, and any larger campus ﬂat lots exist only on distant parts (far
reaches) of campus. Students have to pay extra to park their cars in a lot that is over 10
minutes away from their dorm. Commuters have to buy a pass just to get a cut (a
discount) at the commuter lot.

Vision 2020 advances (proposes) to create a 1,300-space parking lot on Harrison Avenue
where Michigan State Police headquarters is (resides currently). With the state police
headquarters relocated, some people fear that campus safety may be compromised
(reduced). Many students maintain (assert) that it is not safe (unsafe) to walk to a bus
stop or a lot (parking lot) far from the center of campus after working late hours. They
maintain (argue) that reliable public transportation does not exist, currently.

Vision 2020 planners rejected suggestions to make (convert) visitor parking to student
lots. “Visitor lots contribute signiﬁcant revenue to the system,” he said. “That revenue is
what keeps teaching assistant and faculty parking costs reasonable. To build more ramps
would be impossibly (unbelievably) efﬁcient, but impossibly (unbelievably) expensive.”
Places like the Spartan Stadium surface lot, Trowbridge Road parking ramp, the
commuter lot at Mount Hope Road and Farm Lane and others will be involved (are
necessary) to make (accomplish) the 2020 plan work (blank). The trend of creating larger
plots for black, endless seas of pavement in the far reaches of campus has offered a
modest solution to parking problems on campus.

77

BIBLIOGRAPHY

78

BIBLIOGRAPHY

Allen, V. L., & Wilder, D. A. (1980). Impact of group consensus and social
support on stimulus meaning: Mediation of conformity by cognitive restructuring.
Journal of Personality and Social Psychology, 39, 1116 — I 124.

Asch, S. E. (1940). Studies in the principles of judgments and attitudes: 11.

Determination of judgments by group and by ego standards. Journal of Social
Psychology, 12, 433 — 465.

Asch, S. E. (1948). The doctrine of suggestion, prestige, and imitation in social
psychology. Psychological Review, 55 (5), 250 — 276.

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