3 pages for part of the paper.
Design, Procedures, Measures
BRIEF REPORT
An Experimental Examination of
Students’ Attitudes Toward
Classroom Cell Phone Policies
Alexander L. Lancaster & Alan K. Goodboy
This study examined the manipulation of instructors’ persuasive messages to introduce
classroom cell phone policies to college students. Guided by Chaiken’s (1980, 1987)
heuristic-systematic model, we predicted significant differences in students’ systematic mess-
age processing and favorable attitudes held toward a cell phone policy based on the number of
arguments presented and involvement (i.e., motivation). Using a 2 (number of arguments:
high; low)�2 (involvement: high; low) experimental design, 101 undergraduate students
participated by watching a video-recorded persuasive message about a hypothetical cell phone
policy.
indicated that participants did not differ significantly in systematic or heuristic
message processing based on the assigned condition but held more favorable attitudes toward
the cell phone policy when assigned to the lower number of arguments condition.
Keywords: Attitudes; Cell Phone Policies; Heuristic-Systematic Model; Message
Processing; Persuasion
Recent research (Finn & Ledbetter, 2013; Johnson, 2013; Ledbetter & Finn, 2013) has
examined the effect of instructor characteristics and technology policies on instructor
credibility and learner empowerment. Finn and Ledbetter (2013) identified three types
of instructor technology policies: encouraging, discouraging, and laissez-faire policies.
An instructor’s policy on student cell phone use in the classroom is important to
Alexander L. Lancaster (MA, California State University, Long Beach, 2012) is a doctoral candidate in
the Department of Communication Studies at West Virginia University. Alan K. Goodboy (PhD, West Virginia
University, 2007) is an associate professor in the Department of Communication Studies at West Virginia University.
Correspondence: Alexander L. Lancaster, Department of Communication Studies, West Virginia University, P.O. Box
6293, Morgantown, WV 26506; E-mail: allancaster@mix.wvu.edu
Communication Research Reports
Vol. 32, No. 1, January–March 2015, pp. 107–111
ISSN 0882-4096 (print)/ISSN 1746-4099 (online) # 2015 Eastern Communication Association
DOI: 10.1080/08824096.2014.989977
consider because students who use their mobile devices in class take less-detailed notes,
recall less lecture information, and receive lower scores on exams (Kuznekoff &
Titsworth, 2013). Additionally, Johnson (2013) found that students’ use of cell phones
to engage in computer-mediated communication (CMC) during class time (i.e., to
text) was a threat to student engagement and called for instructors to find ways to abate
such behavior. It is important to examine how instructors communicate these policies
in classrooms, as students may respond differently to a policy depending on how it is
presented to them. Therefore, this study explores students’ perceptions of cell phone
policies that instructors present with persuasive messages.
Chaiken’s (1980, 1987) heuristic-systematic model of information processing
(HSM) is a dual-process model of persuasion that posits that individuals can process
a message in one of two ways: systematically or heuristically. Systematic processing
occurs when a receiver is motivated to process all argument-relevant pieces of
information presented in a message. Heuristic processing relies on a few informa-
tional cues to come to a judgment on the message (Todorov, Chaiken, & Henderson,
2002). Consistent with the HSM, two hypotheses are proposed:
H1: Participants in the (a) fewer-arguments condition will be more likely to process a
cell phone policy heuristically than participants in the more-arguments con-
dition, and participants in the (b) more-arguments condition will be more likely
to process a cell phone policy systematically than participants in the
fewer-arguments condition.
H2: Participants in the more-arguments condition will hold more favorable attitudes
toward a cell phone policy afterwards than participants in the fewer-arguments
condition.
The HSM also posits that individuals who are motivated to think about a message
tend to process persuasive appeals systematically, whereas people who are not as
highly motivated engage in heuristic processing (Chaiken, 1980). Therefore, the
following hypothesis is proposed:
H3: Participants in the (a) high-involvement condition will engage in greater
systematic processing than participants in the low-involvement condition, and
participants in the (b) low-involvement condition will engage in greater heuristic
processing than participants in the high-involvement condition.
Undergraduates (N¼118; 47 men and 71 women) participated during class time at a
large, mid-Atlantic university. Ages ranged from 18 to 31 (M¼19.97), and 89% were
White.
The study used a 2 (number of arguments: high; low)�2 (involvement: high; low)
experimental design. Participants responded to half of the items, viewed one of two
video clips (more or fewer arguments), then finished the survey. A pilot test for the
manipulation of more or fewer arguments with two groups of participants (n¼138)
who did not participate in the main study revealed a significant difference between the
more-arguments (M¼2.21, SD¼ .89) and fewer-arguments (M¼1.70, SD¼ .74)
108 A. L. Lancaster & A. K. Goodboy
pilot groups, t(133)¼3.58, p < .001. A manipulation check of involvement was successful, with all but 17 participants, who were excluded from further analyses,
responding correctly to the single-item check.
Cell phone use was measured using four forced dichotomy (i.e., yes=no) items that
were developed for this study. Participants used their cell phones to send or receive
text messages (n¼114), surf the Internet (n¼99), make calls (n¼9), and watch
media (n¼13).
Campbell’s (2006) Attitudes toward Mobile Phones scale was used to assess cell
phone policy attitudes. Measurements were conducted for attitudes preexposure
(M¼4.08, SD¼1.35, a¼ .76) and postexposure (M¼3.79, SD¼1.35, a¼ .72).
Griffin, Neuwirth, Giese, and Dunwoody’s (2002) systematic and heuristic risk
information processing items were modified to address cell phone policies. For systematic
processing, measurements were conducted for premessage exposure (M¼3.63,
SD¼1.17, a¼ .59) and postmessage exposure (M¼4.50, SD¼1.29, a¼ .61). For heu-
ristic processing, measurements were conducted for premessage exposure (M¼4.78,
SD¼1.05, a¼ .53) and postmessage exposure (M¼4.08, SD¼1.26, a¼ .58).
Participants rated message quality using three 7-point semantic differential items
modified from the 9-point semantic differential items used in Petty, Cacioppo,
and Schumann’s (1983) study. Measurements were conducted for the
more-arguments (M¼3.00, SD¼1.41, a¼ .88) and fewer-arguments (M¼3.91,
SD¼1.45, a¼ .86) conditions.
Four 7-point Likert-type items (1¼completely unlikely; 7¼completely likely) were
developed for this study to measure propensity to comply with cell phone policies.
Measurements were conducted for the more-arguments (M¼2.96, SD¼1.43,
a¼ .83) and the fewer-arguments (M¼2.37, SD¼1.12, a¼ .77) conditions.
Results
Before testing the hypotheses, all data were included in a manipulation check for the
number of arguments conditions. The manipulation was successful, t(113)¼2.098,
p < .05. Participants in the more-arguments group (M¼1.92) reported that the
speaker used more arguments than participants in the fewer-arguments group
(M¼1.63).
For H1, results of t-tests revealed no significant differences in systematic,
t(99)¼ .114, p > .05, or heuristic, t(99)¼ .447, p > .05, processing based on the
condition to which participants’ were assigned. Thus, H1a and H1b were not sup-
ported. For H2, results of a t-test revealed that a significant difference between the
groups existed, t(99)¼�2.941, p < .01, but in the direction opposite the prediction. Participants in the fewer-arguments condition (M¼4.21) had more favorable attitudes toward the cell phone policy than individuals in the more-arguments con-
dition (M¼3.45). Hypothesis 2 was not supported. For H3, results of two t-tests
revealed no significant differences between participants in different conditions for
either systematic processing, t(99)¼1.813, p > .05, or heuristic processing,
t(99)¼�1.868, p > .05. Thus, Hypotheses 3a and 3b were not supported.
Communication Research Reports 109
Given the unexpected findings contrary to the HSM, two post hoc tests were con-
ducted. The first revealed a positive relationship between participants’ attitudes
toward cell phone policies and their attitudes toward the cell phone policy in the
experiment (r¼ .72, p < .001). Participants who had unfavorable attitudes toward cell phone policies in general also held negative attitudes toward the cell phone policy in
this study. See Table 1 for all correlations.
The second post hoc test revealed a negative relationship between participants’
attitudes toward the cell phone policy and participants’ likelihood to use their cell
phones during class time (r¼�.28, p < .01). Thus, participants who had less-favorable attitudes toward a cell phone policy also were likely to use their cell
phones in classes that have such policies in place.
The results of this study suggest that the number of arguments does not significantly
affect systematic or heuristic message processing and that a greater number of sup-
porting arguments in the persuasive message led to participants holding
less-favorable attitudes toward the message. Furthermore, the results suggest that
there is no significant difference in systematic or heuristic message processing based
on where the cell phone policy will be implemented. This finding should be inter-
preted with caution, considering the low reliability of the HSM measure.
Two explanations for these results are discussed. First, from a social judgment
(Sherif, Sherif, & Nebergall, 1965) and cognitive miser (Fiske & Taylor, 1991) per-
spective, individuals tend to maintain consistent attitudes and will not change their
opinion without sufficient reason to do so. Thus, because participants held negative
attitudes toward cell phone policies in general, it is logical that they would hold nega-
tive attitudes toward the cell phone policies in this study as well. Second, in this
study, nearly all participants reported using their cell phones to send text messages
during class time, which likely influenced their attitudes toward cell phone policies
that ban the use of these devices during class time. Thus, because participants were
already behaving in a manner that was counter to the advocated policy, it follows that
they also would be likely to hold negative attitudes toward the policy.
Table 1 Pearson Correlations Among Variables
Variables 1 2 3 4 5 6
1. Policy attitudes in general – – – – – –
2. Advocated policy attitudes .72�� – – – – –
3. Argument quality perceptions .48� .60�� – – – –
4. Cell phone use likelihood �.22� �.28� �.48�� – – –
5. Heuristic processing .02 �.03 �.06 �.03 – –
6. Systematic processing .16 .07 .28� �.20� �.28�� –
�p < .05; ��p < .01 (two-tailed).
110 A. L. Lancaster & A. K. Goodboy
This study complements previous research on instructor technology policies (Finn
& Ledbetter, 2013; Ledbetter & Finn, 2013) by looking at students’ attitudinal
reactions to a type of technology policy in the wake of an instructor’s attempt to
implement the policy in a classroom. On a practical level, instructors should avoid
the use of threats because students appear to be unlikely to respond favorably to this
type of communication. According to psychological reactance theory (Brehm, 1966),
individuals may perform the very behavior that a persuasive message attempts to
induce them to stop. Thus, classroom technology policies may be more successful
when they include an encouraging aspect, as well as discouraging aspect (Finn &
Ledbetter, 2013; Ledbetter & Finn, 2013). For instructors, who are charged with
maintaining an orderly, productive classroom environment, the challenge remains
to find a classroom policy that discourages the nonacademic use of cell phones in
class, and one that students will follow.
Brehm, J. W. (1966). A theory of psychological reactance. New York, NY: Academic Press.
Campbell, S. W. (2006). Perceptions of mobile phones in college classrooms: Ringing, cheat-
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03634520600748573
Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus
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(Eds.), Social influence: The Ontario symposium (Vol. 5, pp. 3–39). Hillsdale, NJ: Lawrence
Erlbaum.
Finn, A. N., & Ledbetter, A. M. (2013). Teacher power mediates the effects of technology policies on
teacher credibility. Communication Education, 62, 26–47. doi:10.1080=03634523.2012.725132
Fiske, S. T., & Taylor, S. E. (1991). Social cognition (2nd ed.). New York, NY: McGraw-Hill.
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Kuznekoff, J. H., & Titsworth, S. (2013). The impact of mobile phone usage on student learning.
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Communication Research Reports 111
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- Method
Results
Discussion
References
COMM3023 Proposed Study Modification Paper (Revised for Spring 2020)
Title Page & Abstract (DOES NOT COUNT TOWARD PAGE LIMITS)
1. The title page should include the:
· Title of your paper (e.g., COMM 3023 Proposed Study Modification Paper)
· Names of your group member(s)
· Name of the university
2. The abstract provides a ‘nutshell’ summary of the ENTIRE PAPER.
It must be between 100-150 words long
.
Literature Review
1. Summarize the original article by provide the following 2 pieces of information:
· Purpose of the original study (i.e., what overarching research question(s) were the researchers interested in answering?)
· Variables examined in the original study (identify & define the independent and dependent variables, and also specify any mediating or moderating variables as well).
2. Summarize the method and sample used to carry out the experiment (i.e., what did the researchers do, and who did they recruit to participate in the study?)
Proposed Modifications
1. Describe your
proposed modifications
to the study. You are required to come up with 2 modifications to the original study itself.
· Modification #1: You are to modify the design of the original study by
developing a new way of manipulating one of independent variables in the original study (e.g., in the original study, participants received different types of humor appeals via text only. A proposed modification may be to compare humor appeals delivered via video vs. text).
· Modification #2: You are to modify the sample of the original study by proposing to recruit either: (A) an entirely different target population (e.g., older adults instead of college students) or (B) a more targeted segment of the same target population
(e.g., fraternity/sorority members instead of all college students). In either case, provide a justification for why your proposed sample is an IMPROVEMENT over the original sample recruited for the study (e.g., more representative, topic is of greater relevance to them, etc.).
Proposed New Hypothesis
1. Come up with a new hypothesis that your group could test using the existing variables found in the original study (e.g., Exposure to self-deprecating humorous messages about binge drinking will yield more negative attitudes about binge drinking than exposure to either an other-deprecating humorous, or non-humorous message about binge drinking) or based on your modification (e.g., Humorous appeals delivered via video will yield more negative attitudes about binge drinking than those delivered via text).
· Make an argument for your prediction. Justify why you feel your prediction is correct.
· You can look for empirical support for your argument if you choose, but it is not required.
Methods (Divided into 4 subsections):
1.
Participants
· Clearly identify the target population you plan to recruit from for your proposed modified study.
· Identify the
specific sampling frame
from which you’ll recruit your sample (i.e., where will you recruit your sample from? How will you identify potential study participants?)
· Identify the
sampling strategy/technique to be used in selecting the final participants for your proposed modified study.
· Note any restrictions, if any, for participation in your study (e.g., study is only open to females). If there are no restrictions, state this clearly in the paper.
2.
Design
· Specify the
experimental design
you will be using for the study.
· Are you doing a quasi- or true experiment?
· Are you using a special research design? (i.e., factorial design, longitudinal design, repeated measures design)
· Clearly describe the independent variables in the study.
· Discuss what independent variables you will manipulate.
· Discuss what independent variables will simply be measured (i.e., individual difference variables such as personal commitment to binge drinking).
· For each manipulated independent variable examined in your proposed study, describe in detail the nature of the manipulation (i.e., what stimulus will be the participants be exposed to, what will you ask the participants asked to do, etc.).
3.
Procedures
· Provide a
step-by-step breakdown of what participants will do from the moment they start your study to the completion of your study. The more details the better. Discuss the different tasks participants will perform as part of the experiment, and describe the sequencing of tasks as well (e.g., First, participants will read over the consent form document and provide consent by checking the box…. Second,…)
4.
Measures
· For each dependent variable you plan to test in your proposed modified study, you will need to state clearly how you plan to measure it (e.g., are you using an existing scale or are you developing your own questions?)
·
Use of an existing scale
(e.g., Attitudes will be measured with four 11-point semantic differential scale items taken from Ajzen & Fishbein, 1980).
·
Developing your own questions
(e.g., Attitudes will be measured with four 7-point Likert scale items developed by the researchers). Be sure to
include sample items
if you are developing your own questions (e.g., Specifically, participants will be asked whether they think (a) Drinking excessively is a good idea (1=strongly disagree to 7=strongly agree).
· For measured independent variables, you will need to describe the survey items. Follow the same procedure as you did for the dependent variables.
· For manipulated independent variables, you will need to describe how you plan to check if the manipulation was carried out effectively (e.g., to check for self-deprecating vs. other-deprecating humor, you can ask: The message I was exposed to about binge drinking made fun of the speaker’s friend – Yes or No?)
References (DOES NOT COUNT TOWARD PAGE LIMITS)
1. Provide a complete set of references for all work cited in the paper. Be sure that the formatting adheres to APA format.
The paper should be between 6-7 pages (not including title, abstract, and reference page). Paper needs to be uploaded onto Canvas by Monday, April 20 @ 5 p.m. CST.