Predicting Student Performance in Higher Education
| Authors | |
|---|---|
| Year of publication | 2013 |
| Type | Article in Proceedings |
| Conference | 24th International Workshop on Database and Expert Systems Applications - Dexa 2013 |
| MU Faculty or unit | |
| Citation | |
| Doi | http://dx.doi.org/10.1109/DEXA.2013.22 |
| Field | Informatics |
| Keywords | student performance; recommender system; data mining; social network analysis |
| Description | In this work, we focus on predicting student performance using educational data. Students have to choose elective and voluntary courses for successful graduation. Searching for suitable and interesting courses is time-consuming and the main aim is to recommend students such courses. Two beneficial approaches are thoroughly discussed in this paper. The results were achieved by analysis of study-related data and structural attributes computed from the social network. To validate the proposed method based on data mining and social network analysis, we evaluate data extracted from the information system of Masaryk University. However, the method is quite general and can be used at other universities. |
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