Exploring Variation in Student Academic Performance: Can Achievement in an Immersive Case Study Project Predict Exam Score in an Introductory Accounting Course?

Abstract

In modern university education, quantitative analytical skills seem best acquired through deep learning of complex, multi-faceted problems. Our quasi-experimental design tested whether student achievement in an immersive classroom case study might affect subsequent academic performance, presumably reflecting deeper learning of fundamental principles in an accounting course. We analyzed exam scores of three behavior-based student groups: (a) “OOP,” who Opted Out of the immersive case study Project, (b) “BMP,” who earned Below Median marks on the Project, and (c) “AMP,” who scored At least the Median on the Project. Results indicate that student academic performance declined at effectively equal rates among the three student groups in any given semester. Surprisingly, students’ self-reported deep strategy more strongly predicted their academic performance, accounting for more than 30% of exam score variation; group membership explained only 1.93% of exam score variation. These results underscore the need to document student learning approaches explicitly in order to complement observations of student classroom behaviors and academic performance.

Keywords

• accounting cycle, student approach to learning (SAL), repeated-measures ANOVA