eCite Digital Repository
Data mining: will first-year results predict the likelihood of completing subsequent units in accounting programs?
Citation
Sithole, STM and Ran, G and De Lange, P and Tharapos, M and O'Connell, B and Beatson, N, Data mining: will first-year results predict the likelihood of completing subsequent units in accounting programs?, Accounting Education pp. 1-27. ISSN 1468-4489 (2022) [Refereed Article]
 | PDF Pending copyright assessment - Request a copy 474Kb | | PDF Pending copyright assessment - Request a copy 3Mb |
DOI: doi:10.1080/09639284.2022.2075707
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.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | academic performance, accounting students, classification algorithm, educational data mining, performance prediction |
| Research Division: | Commerce, Management, Tourism and Services |
| Research Group: | Accounting, auditing and accountability |
| Research Field: | Accounting, auditing and accountability not elsewhere classified |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding knowledge |
| Objective Field: | Expanding knowledge in commerce, management, tourism and services |
| UTAS Author: | Sithole, STM (Dr Seedwell Sithole) |
| UTAS Author: | Ran, G (Mr Guang Ran) |
| UTAS Author: | De Lange, P (Professor Paul De Lange) |
| ID Code: | 149996 |
| Year Published: | 2022 |
| Deposited By: | College Office - CoBE |
| Deposited On: | 2022-05-08 |
| Last Modified: | 2022-05-16 |
| Downloads: | 0 |
Repository Staff Only: item control page