The process of testing the hypotheses

Before testing the hypotheses, all data were included in a manipulation check for the
number of arguments conditions. The manipulation was successful, t(113) ¼ 2.098,
p < .05. Participants in the more-arguments group (M ¼ 1.92) reported that the
speaker used more arguments than participants in the fewer-arguments group
(M ¼ 1.63).
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 supported. 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 (M ¼ 4.21) had more favorable
attitudes toward the cell phone policy than individuals in the more-arguments condition (M ¼ 3.45). 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) ¼ 1.813, 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 conducted. The first revealed a positive relationship between participants’ attitudes
toward cell phone policies and their attitudes toward the cell phone policy in the
experiment (r ¼ .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 (r ¼ .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 supporting 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 interpreted 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) perspective, 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 negative 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, cheating, and classroom policies. Communication Education, 55, 280–294. doi:10.1080=
Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus
message cues in persuasion. Journal of Personality and Social Psychology, 39, 752–766.
Chaiken, S. (1987). The heuristic model of persuasion. In M. P. Zanna, J. M. Olson & C. P. Herman
(Eds.), Social influence: The Ontario symposium (Vol. 5, pp. 3–39). Hillsdale, NJ: Lawrence
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.
Griffin, R. J., Neuwirth, K., Giese, J., & Dunwoody, S. (2002). Linking the heuristic-systematic
model and depth of processing. Communication Research, 29, 705–732. doi:10.1177=
Johnson, D. I. (2013). Student in-class texting behavior: Associations with instructor clarity and
classroom relationships. Communication Research Reports, 30, 57–62. doi:10.1080=
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apprehension as predictors of learner empowerment. Communication Education, 62,
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Petty, R. E., Cacioppo, J. T., & Schumann, D. (1983). Central and peripheral routes to advertising
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Communication Research Reports 111
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Association and its content may not be copied or emailed to multiple sites or posted to a
listserv without the copyright holder’s express written permission. However, users may print,
download, or email articles for individual use.

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