Publication details
Course Similarity Analysis
| Authors | |
|---|---|
| Year of publication | 2016 |
| Type | Article in Proceedings |
| Conference | Proceedings in Informatics and Information Technologies |
| MU Faculty or unit | |
| Citation | |
| Field | Informatics |
| Keywords | course similarity; student performance prediction; university information system |
| Description | Courses offered to students at universities have different characteristics. In this paper, we analyse course similarities to improve the students’ performance prediction. We utilize the item-to-item collaborative filtering approach that computes course similarities based on students’ grades. We also use content based techniques to compute course similarities based on the information from the course catalogue, e.g. the course content or prerequisites. Using the computed similarities and utilizing different clustering algorithms, we are able to reveal interesting course groups that can be used to improve the student performance prediction. Finally, we are able to predict the students’ final grades of the investigated course by examining grades of only three related courses. |
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