• Self-regulated studying behavior, and the social norms that influence it

      Eyink, Julie; Motz, Benjamin; Heltzel, Gordon; Liddell, Torrin
      Since the seminal studies of Asch (1956) and Sherif (1936), decades of work show how others' actions and beliefs powerfully influence our own behaviors. Generally, people conform to the behaviors of others to either gain social approval (normative social influence) or to find suitable, effective behaviors in uncertain situations (informational social influence; e.g. Deutsch & Gerard, 1955). These two different motives correspond to different types of normative information: injunctive and descriptive norms, respectively. Injunctive norms tell us what we should or ought to do, and therefore refer to actions that others in a group approve of. They both prescribe accepted actions and proscribe inappropriate be? haviors. If individuals adhere to these norms, they receive social acceptance; conversely, if one disregards these norms, the threat of social sanctions looms (Cialdini & Trost, 1998; Jacobson, Mortensen, & Cialdini, 2011). In contrast, descriptive norms provide information about the actions most others actually do in a given context, offering a consensus about which behaviors are likely to be effective (Jacobson et al., 2011; Kelley, 1967). Because individuals want to be accurate (Lundgren & Prislin, 1998), they adapt their behaviors to that of the group, particularly when situations are ambiguous, uncertain, or novel (Sherif, 1936). In educational contexts, it seems clear to us that teachers use injunctive norms when telling students what they should do (e.g. Dunlosky et al. 2013). But researchers sometimes find descriptive norms more powerfully influence behavior (e.g. Goldstein et al., 2008). In the present work, we examine which type of norm is more effective at increasing self?regulated studying and performance in an online college course across two semesters. To do this, we randomly assigned 751 undergraduate Introductory Psychology students to receive email messages at the start of every content unit that either contained descriptive norms, injunctive norms, information about the course, or a no message control. Using Bayesian estimation, we found injunctive norms increased study behaviors aimed at fulfilling course requirements (completion of assigned activities), but did not improve learning outcomes. Descriptive norms increased behaviors aimed at improving knowledge (ungraded practice with activities after they were due), and improved performance. These results suggest that norms more effectively influence behavior when there is a match, or a sense of fit, between the goal of the behavior (fulfilling course requirements vs. learning) and the pull of a stated norm (social approval vs. efficacy). Because the goal of education is learning, this suggests descriptive norms have a greater value for motivating self-regulated study in authentic learning environments.
    • Using Clickers in the Classroom

      Eyink, Julie
      Instructors often search for ways to increase student engagement and participation during class. Learning Response Systems, known colloquially as clickers, are one potential solution. Research shows students perceive clickers positively (Han & Finklestein, 2013) and that clickers facilitate learning and engagement (Morling et al., 2008; Hake, 1998). To see if clickers had similar positive effects in my classroom, I solicited feedback from the 108 students in my Introduction to Psychology course. During the Fall 2020 semester, I used the Acadly clicker app to take attendance, ask multiple choice poll questions to gain insight into which topics students understood, and conducted discussions via the app to help ensure social distancing. 55 of those students provided feedback. Overall, students agreed Acadly facilitated learning (M = 6.15 on a 7-point scale) and engagement (M = 6.24), and that it helped them to participate in the large lecture class in a less stressful/anxiety-producing manner (M = 6.37). Resources/References For more information on Acadly, see: https://www.acadly.com/ or their help page: https://help.acadly.com/en/ Hake, R. R. (1998). Interactive-engagement vs. traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66, 64–74. Han, J. H., & Finkelstein, A. (2013). Understanding the effects of professors' pedagogical development with Clicker Assessment and Feedback technologies and the impact on students' engagement and learning in higher education. Computers & Education, 65, 64-76. Morling, B., McAuliffe, M., Cohen, L., & DiLorenzo, T. M. (2008). Efficacy of personal response systems (“clickers”) in large, introductory psychology classes. Teaching of Psychology, 35(1), 45-50.