An Automatic Optimal Course Recommendation Method for Online Math Education Platforms Based on Bayesian Model
DOI:
https://doi.org/10.3991/ijet.v16i13.24039Abstract
Online education platforms inject new vitality into the field of education, and greatly improves the accessibility to high-quality education resources. However, the current online education platforms do not support independent course selection based on personal preferences. To solve this problem, this paper designs an automatic recommendation method of optimal courses for online math education platforms based on Bayesian model. The results show that the Bayesian model can simulate the causal relationship between real-world affairs by building a graphic model based on the graph theory and the probability theory; the model can effectively merge priori and posteriori information, and encode the causality between knowledge points; the model clearly outshines user-based collaborative filtering model, term-based collaborative filtering model, and SlopeOne model, and achieves a stable accuracy rate in automatic recommendation of courses. The research provides an empirical evidence to the improvement and innovation of professional online math course platforms.
Downloads
Published
How to Cite
Issue
Section
License
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.