How does expectancy-value-cost motivation vary during a semester? An intensive longitudinal study to explore individual and situational sources of variation in statistics motivation

We measured expectancy, value, and cost 10 times over a 10-week introductory statistics course (N = 219) to examine their overall trajectory as well as individual (between-student) differences and situational (within-student) variability. First, our findings revealed an initial decline in expectancy and value and an initial increase in cost. Second, expectancy, utility value, and cost demonstrated individual and situational variability of comparable size, while intrinsic value had higher individual variability. Third, individual and situational variability in expectancy and value predicted variability in performance. Lastly, the relation of situational variability in expectancy and utility value with performance was stronger for Black, Latinx, and other racially marginalized students than for White/Asian students. Our findings provide empirical evidence for the situational nature of motivational beliefs and have implications for practitioners, course curriculum designers, and policymakers who aim to create more supportive and motivation-enhancing environments, particularly for statistics courses and students from racially marginalized and underserved backgrounds.

Educational relevance and implications statement

The aim of this research was to better understand the dynamic and situational nature of motivational beliefs (expectancy, value, and cost) in a college statistics course by measuring them 10 times over a 10-week term in an introductory statistics course. We found an initial decline in expectancy for success and values for statistics and an initial increase in perceived cost. We also found these beliefs fluctuated depending on the learning situation, which in turn, predicted their performance in that situation. Lastly, for students from racially marginalized and underserved groups (e.g., Black, Latinx, and Native-American students), we found that the learning situation played a key role in influencing their motivational beliefs and performance, highlighting the importance of taking the learning context into account when designing motivation-enhancing environments for students in statistics courses. These findings have implications for practice in that they (a) allow curriculum developers to redesign certain chapters based on motivational declines, and (b) help us identify the student groups whose motivational beliefs varies the most with contextual factors, and as such, any context-relevant interventions for creating more equitable learning contexts that support students of all backgrounds, particularly those who are historically marginalized by our education systems.