A profile analysis of online assignment motivation: Combining achievement goal and expectancy-value perspectives

Abstract

Online assignment is a global and growing phenomenon in higher education that presents significant motivational challenges for many online students. Yet, little is known on the motivational beliefs of students towards online assignment, and none on how in combination they affect student behavior when it comes to online assignment. This present study aims to identify online assignment motivation profiles based on achievement goal theory (mastery- and performance-approach goals) and expectancy-value theory (expectancy and value components). Latent profile analysis (LPA) was used to examine if homogenous latent profiles exist within a sample of 612 college students in China. Our findings identified four distinct profiles: High Motivation, Moderate Motivation, Low Goal Orientation/Moderate Expectancy-Value, and Very High Goal Orientation/Very Low Expectancy-Value. Our findings further revealed that profile membership was associated with self-regulation of online assignment behavior, including handling distraction, arranging the environment, managing time, monitoring motivation, emotion management, and cognitive reappraisal. Finally, supplemental analyses showed the added benefit of integrating both achievement goal and expectancy-value theories when forming online assignment motivation profiles. These findings indicated the importance of promoting multiple motivational beliefs to better support self-regulation of online assignment behavior. The present study suggests that understanding online assignment motivation profiles can provide new insights into promoting an adaptive online learning environment and help online instructors enhance and sustain their students’ motivation with online assignment (e.g., to provide differentiated support based on the motivational needs of online students in each profile).