Longitudinal Expectancy-Value Profiles in Engineering and Science: A Cross-Domain Analysis of Motivation and STEM-Related Outcomes

• In Event: Diverse Methodological Approaches to Exploring Cognitive and Motivational Processes

Abstract

A person-oriented approach was used to estimate joint developmental trajectories of college students’ expectancies, values, and costs in engineering (EGR) and science (SCI). Four distinct profiles were identified using Longitudinal latent profile analysis (Declining EGR; Changing EGR & stable SCI; Declining EGR & rising SCI; High & stable all). Two profiles displayed divergent trajectories across domains, whereas others displayed similar trajectories across science and engineering. Each profile uniquely predicted differential intentions to pursue careers in science and engineering. In contrast to other cross-domain analyses, we did not detect significant differences in demographic composition of profiles. Our findings provide evidence for dimensional comparison theory, suggesting students’ intentions to pursue a domain are influenced by motivational developments in adjacent domains.

Authors

• John Keane, Michigan State University

• Garam Lee, Michigan State University

• Arianna C White-Levatich, Old Dominion University

• Tony Perez, Old Dominion University

• S. Patrick Walton, Michigan State University

• Daina Breidis

• Lisa Linnenbrink-Garcia, Michigan State University