eprintid: 2545
rev_number: 7
eprint_status: archive
userid: 290
dir: disk0/00/00/25/45
datestamp: 2017-07-02 14:43:13
lastmod: 2017-07-02 14:43:13
status_changed: 2017-07-02 14:43:13
type: article
metadata_visibility: show
creators_name: Tran, Thi Oanh
creators_name: Dang, Hai Trieu
creators_name: Dinh, Viet Thuong
creators_name: Truong, Thi Minh Ngoc
creators_name: Vuong, Thi Phuong Thao
creators_name: Phan, Xuan Hieu
creators_id: hieupx@vnu.edu.vn
title: Performance Prediction for Students: A Multi-Strategy Approach
ispublished: pub
subjects: IT
subjects: isi
divisions: fac_fit
abstract: This paper presents a study on Predicting Student Performance (PSP) in academic systems. In order to solve the task, we have proposed and investigated different strategies. Specifically, we consider this task as a regression problem and a rating prediction problem in recommender systems. To improve the performance of the former, we proposed the use of additional features based on course-related skills. Moreover, to effectively utilize the outputs of these two strategies, we also proposed a combination of the two methods to enhance the prediction performance. We evaluated the proposed methods on a dataset which was built using the mark data of students in information technology at Vietnam National University, Hanoi (VNU). The experimental results have demonstrated that unlike the PSP in e-Learning systems, the regression-based approach should give better performance than the recommender system-based approach. The integration of the proposed features also helps to enhance the performance of the regression-based systems. Overall, the proposed hybrid method achieved the best RMSE score of 1.668. These promising results are expected to provide students early feedbacks about their (predicted) performance on their future courses, and therefore saving times of students and their tutors in determining which courses are appropriate for students’ ability.
date: 2017-06
date_type: published
official_url: http://doi.org/10.1515/cait-2017-0024
id_number: doi:10.1515/cait-2017-0024
contact_email: hieupx@vnu.edu.vn
full_text_status: none
publication: Cybernetics and Information Technologies
volume: 17
number: 2
pagerange: 164-182
refereed: TRUE
issn: 1314-4081
funders: VNU
projects: QG.15.29
citation:   Tran, Thi Oanh and Dang, Hai Trieu and Dinh, Viet Thuong and Truong, Thi Minh Ngoc and Vuong, Thi Phuong Thao and Phan, Xuan Hieu  (2017) Performance Prediction for Students: A Multi-Strategy Approach.  Cybernetics and Information Technologies, 17  (2).   pp. 164-182.  ISSN 1314-4081