relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3657/
title: A Model to Forecast the Student's Grade and Course Recommendation: A Case Vietnamese Students
creator: Nho, Minh Tu
creator: Nguyen, Hoa-Huy
creator: Ton, Quang Cuong
creator: Nguyen, Viet Anh
subject: Information Technology (IT)
description: This paper presents a model for forecasting the learning outcomes and suggesting the recommend courses for undergraduate students. In this research, we propose methods based on machine learning techniques and recommender systems to answer three research questions of forecasting student’s outcomes problem: 1) How to forecast the course’s grade for the next subject. 2) How to predict the final grade point average basing on the subjects students have studied. 3) How to suggest a list of subjects that students should learn in the next semester. The model has been tested with the grade data in 22-course subjects with the participation of 580 students. The results, in the best case, for predicting the missing subject grades with the tested data set were 0.656, a good result for scores in the range [0, 10]. Assessing the user’s satisfaction of the model through the survey, the results show that 68.2% of students think that the system is useful for them.
date: 2019
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Nho, Minh Tu and Nguyen, Hoa-Huy and Ton, Quang Cuong and Nguyen, Viet Anh  (2019) A Model to Forecast the Student's Grade and Course Recommendation: A Case Vietnamese Students.  In: First International Conference on Innovative Computing and Cutting-edge Technologies (ICICCT 2019), Oct 30-31, 2019, Istanbul, Turkey.