Students' Motivational Profiles in Science: Exploring Profile Predictors and Associations With Classroom Engagement

• In Event: AERA Poster Session 11
  In Poster Session: Motivation in Education SIG Poster Session: Motivational Processes and Effects (San Diego)

Abstract

Grounded in expectancy-value theory and implicit theories of intelligence, this study used latent profile analysis to identify unique profiles representing students’ motivational beliefs at the beginning of the semester among a diverse sample of 560 middle- and high school students. We examined whether student characteristics (e.g., gender, grade level, and underrepresented minority status) were predictors of profile membership, and whether profile membership predicted students’ behavioral, cognitive, and affective engagement in science. Students completed an initial survey on their motivational beliefs about science and in subsequent weeks recorded their engagement using end-of-class reports. Results suggest five unique motivational profiles, which are differentially predictive of students’ engagement in science, and certain student characteristics associated with profile membership.

Authors

• Vicky Phun, Michigan State University

• Matthew James Schell, Michigan State University

• Jennifer A. Schmidt, Michigan State University