Using implicit psychological mechanisms to predict student success in digital higher education

This longitudinal study investigates the role of implicit psychological processes in student success in digital higher education (DHE). In traditional study formats, implicit academic attitudes, as measured with implicit association tests (IAT), were excellent predictors of student success. Since no such findings exist for DHE, we conducted two separate IATs to predict study behavior in a large sample of students over six months. To gain a more detailed understanding of student success in DHE, analyses differentiated between the engagement and persistence of students, which were operationalized by the completion of examinations and dropping out of university, respectively. Predictors primarily included the student's implicit and explicit academic identification and -attitude. An Attitude-IAT (study + good) predicted engagement (completed examinations) in a logistic regression model, and an Identification-IAT (study + me) correlated with factors that are indirectly associated with persistence (educational background, self-efficacy, identification). The effect of the Attitude-IAT also remained significant after accounting for explicit measures. This shows that student success in DHE is predictable based solely on students' reaction times in a simple cognitive-psychological test. This test could potentially become part of a battery of items to identify students at risk of dropout. The findings also have important implications for understanding the relationship between student success and student motivation in DHE.