Data mining: will first-year results predict the likelihood of completing subsequent units in accounting programs?

ABSTRACT

This study introduces data mining methods to accounting education scholarship to explore the relationship between accounting students’ current academic performance (grades), demographic information, pre-university entrance scores and predicted academic performance. It adopts a C4.5 classification algorithm based on decision-tree analysis to examine 640 accounting students enrolled in an undergraduate accounting program at an Australian university. A significant contribution of this study is improved prediction of academic performance and identification of characteristics of students deemed to be at risk. By partitioning students into sub-groups based on tertiary entrance scores and employing clustering of study units, this study facilitates a more nuanced understanding of predictor attributes. Key findings were the dominance of a cluster of second year units in predicting students’ later academic performance; that gender did not influence performance; and that performance in first year at university, rather than secondary school grades, was the most important predictor of subsequent academic performance.

KEYWORDS:

• Academic performance
• accounting students
• classification algorithm
• educational data mining
• performance prediction

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Socialisation in this context employs the definition of Bragg (1976) as a learning process of adopting the values, norms, and social roles involving a number of steps: (1) observation – the identification of a role model(s); (2) imitation – the ‘trying on’ (3) feedback – the evaluation of the ‘trying on’ (4) modification-the alteration or refinement as a result of evaluation; and (5) internalisation--incorporation patterns into the individual. When such socialisation processes occur in group settings, there exists a strong tendency towards uniformity (Goethals, 1999).