Data Analytics, Netlike Knowledge Structure, and Academic Performance

Abstract

ABSTRACT The first objective of this study was to investigate whether data analytics could form a netlike knowledge structure (NKS) of learned course materials in accounting. We tested a group of students that used data analytics to solve an asset misappropriation case study and a control group that did not. We found evidence that data analytics has formed such a structure. The second objective was to investigate whether NKS was associated with academic performance. We conducted regression analyses on the NKSs and test scores. We found evidence that NKS with high connectivity and processing efficiency was associated with better accounting test scores. Overall, the findings imply that integrating data analytics into accounting courses benefits the learning of course materials by forming an NKS positively associated with academic performance. This study makes several contributions, including extending the work on NKS conducted predominantly in the cognitive science domain to the accounting domain.