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Finally, our mostly African American sample may be different from other student samples insofar as cultural background might influence cell phone use patterns. Checking the time on a cell phone for 1 second might be far less distracting than scrolling though Instagram for 10 minutes. Our observations of cell phone use only recorded number of instances of use, not duration of use. We do not have any means of knowing how seating arrangement or class size might have affected our results. There may have been carry-over effects of the prior policy that affected our results. A related limitation was the fact that the new policy was introduced midway though the semester. Research should examine how long policies need to be in place before they show behavioral changes. Students may need more than one class period to adapt to a professor's policy before making substantial behavior changes. One major limitation was the short time frame of the policy manipulation. Research suggests that individuals who have better delay of gratification skills also succeed better academically and socially throughout life ( Yang & Wang, 2007). Interventions might focus on increasing self-regulation of cell phone use.

Perhaps delaying the gratification of phone use can be trained ( Murray, Theakston, & Wells, 2016). Moreover, students may be unable to focus on the long-term rewards of paying attention in class (e.g., gaining knowledge, better test scores, and an eventual degree) and instead give in to the immediate temptation to use their phones. Rather, the positive reinforcements (e.g., social connectivity) inherent in phone use might increase the behavior ( Puente & Balmori, 2007). However, our data did not show that anxiety was associated with cell phone use. Compulsive cell phone use suggests an association with anxiety, in which a student might experience anxiety relief from engaging in phone use. Students using cell phones in class realize that the behavior has a negative impact on their grades, yet the activity seems difficult to control ( Roberts et al., 2014 Sunthilia et al., 2016). Indeed, our data show consistently high cell phone use in both groups. Students report having trouble not using their phones during class ( Roberts et al., 2014 Sunthilia, Ahmad, & Singh, 2016). Our results contribute to a body of literature showing that electronic devices distract students and decrease the efficacy of the learning environment. Students operated their phones an average of about seven times during the 50-minute class period, mostly for non-academic purposes. In the restrictive policy condition, students used their cell phones in class at a similar rate as in the lenient policy condition, suggesting that the restrictive cell phone policy was ineffective. Afterward, they were given a survey that measured demographics, attitudes about cell phone use in class, academic motivation, cell phone use domains, and anxiety. At the end of the class period, students took a short quiz over the lecture material. We observed how often students used their phones during class in both conditions. We gave one introductory psychology section a restrictive cell phone use policy while another section was given a lenient policy. Additionally, we expected students to self-report using their phones mostly for non-academic purposes. We expected that a lenient policy would be associated with lower quiz scores, greater anxiety, and lower GPA. Our study examined the efficacy of lenient and restrictive cell phone policies.
