Student performance prediction in educational data mining aims at predicting the correctness in performing a given task of a student based on historical data. Accurately predicting the performance allows helpful intervention and useful feedback by instructors to improve students’ learning. This paper presents a framework for tackling the student performance prediction problem using collaborative filtering, which collectively considers behaviour of students as well as the nature and difficulty of questions. Experiments on real-world data of an intelligent tutoring system were conducted to evaluate the effectiveness of our framework.
|Publication status||Published - Jul 2014|
|Event||International Conference on Technology in Education 2014: "Transforming Educational Practices with Technology" - The Open University of Hong Kong, Hong Kong|
Duration: 02 Jul 2014 → 04 Jul 2014
|Conference||International Conference on Technology in Education 2014: "Transforming Educational Practices with Technology"|
|Abbreviated title||ICTE 2014|
|Period||02/07/14 → 04/07/14|
CitationWong, T.-L., Tang, J. K. T., Pang, W. M., Ho, W. S., Chiu, C. H., & Poon, L. (2014, July). Collaborative filtering for student performance prediction. Paper presented at the Inaugural International Conference on Technology in Education, The Open University of Hong Kong, China.
- Educational data mining
- Student performance prediction
- Collaborative filtering