Motivation as a Complex System: Semester-Long Recursive Dynamics of Expectancy-Value Constructs in Undergraduate Biology

• In Event: Poster Session 15
  In Poster Session: Motivation in Education SIG Poster Session 1

Abstract

The predominant aggregate-statistical analyses in motivational research manifest assumptions that stand in tension with understandings of motivational phenomena as dynamic, contextual, and variable among individuals. Using constructs from expectancy-value theory, we collected 13 weekly waves of data from 145 undergraduate students during one semester of an introductory biology course. We analyzed the data using dynamic autoregressive mixed-effects modeling, which captures the individual-level recursive processes among constructs, and then examined patterns across individuals’ motivational trajectories to discern general principles by which the expectancy-value system operates. The findings contribute to robust theoretical understandings of expectancy-value processes, and demonstrate the application of an analytical approach to motivational research that is compatible with the nature of motivational phenomena.

Authors

• Avi Kaplan, Temple University

• Xi Hang Cao, Temple University

• Ting Dai, University of Illinois at Chicago

• Zoran Obradovich, Temple University

• Tony Perez, Old Dominion University

• Jennifer G. Cromley, University of Illinois at Urbana-Champaign

• Kyle R Mara, University of Southern Indiana

• Michael Balsai