Dynamics of Expectancies, Values, and Costs among College Students and their Relation to Motivational Development

• In Event: New Opportunities in Motivation and Emotion Research Through Advanced Statistics

Abstract

Objectives and Theory: Situated Expectancy Value Theory (SEVT; Eccles & Wigfield, 2020) suggests that students' academic engagement, persistence, and choices are influenced by their expectancies, values, and costs. Existing research on motivational development has mainly examined these factors over extended periods of months or years, overlooking the detailed, shorter-term experiences that SEVT claims to influence long-term motivation. This study explores how students' motivations fluctuate over much shorter periods (e.g., class to class) and how these momentary changes connect to broader developmental patterns. Using intensive, longitudinal data from 1,125 college students enrolled in a statistics course, we analyzed 26,978 in-the-moment reports of expectancies, values, and costs collected via mobile apps, along with pre- and post-course surveys measuring students’ domain-level motivation for statistics.

Methods and Data: We aimed to address two research questions: (RQ1) How do momentary beliefs operate across daily experiences in a statistics course? (RQ2) How do dynamics of students’ momentary beliefs relate to broader domain-level motivational development?
Dynamic structural equation models (DSEM; Asparouhov et al., 2018) estimated situated motivational levels (Y_B), residual variances (ψ), carryover effects (ϕ), and trends (ζ) for students’ in-the-moment expectancies, values (attainment, interest, utility), and costs (effort, opportunity, psychological, emotional). We tested whether these dynamics mediated the relationship between initial and end-of-course domain-level statistics motivation (see Figure 1 for conceptual model).

Results: Table 1 shows standardized estimates averaged across participants (Schuurman et al., 2016). Addressing RQ1, all constructs displayed significant but small carryover effects (posterior medians ranging from 0.120 to 0.221). On average, momentary values and expectancies slightly declined (-0.022 to -0.137) and costs increased (0.179 to 0.264). All constructs displayed large within-person residual variance (0.760 to 0.905), suggesting that large portions of daily beliefs could not be explained via carryover or trend effects and instead are likely due to unique characteristics of daily experiences.
Table 2 provides correlations between students’ levels, carryover, trends, and residual variances in momentary beliefs. Carryovers and variances were negatively correlated across all eight models, reflecting the fact that momentary beliefs with higher carryover necessarily have smaller unexplained variances. Interestingly, students who tended to report higher values and expectancies varied less in their responses; in contrast, students who tended to report high costs had more variable responses across timepoints.
Table 3 provides estimates related to RQ2, which explored momentary beliefs as mediators of the association between students’ domain-level motivation for statistics at the beginning and end of the course. Results showed that momentary levels mediated domain-level change in all eight constructs. Although interesting patterns were observed among other A and B pathways, models did not detect mediation by momentary carryover, trends, or residual variances.
Significance: This study highlights the importance of understanding daily motivational dynamics, specifically regarding how immediate experiences can predict and influence long-term motivational changes. We discuss modeling and measurement issues associated with intensive, longitudinal data and their implications for research on the situated nature of motivational ontogeny. This knowledge is vital for validating the SEVT framework and developing more effective interventions aimed at sustaining positive student motivation (Eccles & Wigfield, 2020; Moeller et al., 2022).

Authors

• John Keane, University of Michigan

• Lisa Linnenbrink-Garcia, Michigan State University