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A MOOC Courses Recommendation System Based on Learning Behaviours

Authors:

Hongzhi WangAuthors Info & Claims

ACM TURC '20: Proceedings of the ACM Turing Celebration Conference - China

Pages 133 - 137

https://doi.org/10.1145/3393527.3393550

Published: 26 October 2020 Publication History

Abstract

MOOC1 courses recommendation is an important and challenging task, especially in an era with a quick development of Internet which consists of gigantic and diverse education resources. Its challenge is due to its massive amount of education information in almost all academic fields and as a result, the inevitable negligence of personalized needs for certain knowledge. Therefore, the research on timely capturing of the learners' behaviours and then personalized guidance of their learning process becomes increasingly essential. In this paper, we analyse online learning behaviours to improve personalized recommendations in MOOC courses. Our main contribution is to utilize information from different sources and design a centralized framework to combine them, thus making superior recommendation. We propose two different models based on the above sources and a combined model, and then contrast the models with other traditional models to prove the superior performance of our models.

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Cited By

Zhang DZhang KWu LTian MHong RWang MBaeza-Yates RBonchi F(2024)Path-Specific Causal Reasoning for Fairness-aware Cognitive DiagnosisProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3672049(4143-4154)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3672049
Li JLiu QWang FLiu JHuang ZYao FZhu LSu YChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive ParadigmProceedings of the ACM Web Conference 202410.1145/3589334.3645437(3420-3431)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645437
liu qzhang l(2024)Multiview attention-based graph convolutional networks for course recommendation in MOOCsThird International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)10.1117/12.3032986(156)Online publication date: 5-Jul-2024
https://doi.org/10.1117/12.3032986
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Index Terms

A MOOC Courses Recommendation System Based on Learning Behaviours
1. Applied computing
  1. Education

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cover image ACM Other conferences

ACM TURC '20: Proceedings of the ACM Turing Celebration Conference - China

May 2020

220 pages

ISBN:9781450375344

DOI:10.1145/3393527

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Baidu Research: Baidu Research

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2020

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Funding Sources

NSFC grant U1866602

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ACM TURC'20

ACM TURC'20: ACM Turing Celebration Conference - China

May 22 - 24, 2020

Hefei, China

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Cited By

Zhang DZhang KWu LTian MHong RWang MBaeza-Yates RBonchi F(2024)Path-Specific Causal Reasoning for Fairness-aware Cognitive DiagnosisProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3672049(4143-4154)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3672049
Li JLiu QWang FLiu JHuang ZYao FZhu LSu YChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Towards the Identifiability and Explainability for Personalized Learner Modeling: An Inductive ParadigmProceedings of the ACM Web Conference 202410.1145/3589334.3645437(3420-3431)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645437
liu qzhang l(2024)Multiview attention-based graph convolutional networks for course recommendation in MOOCsThird International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024)10.1117/12.3032986(156)Online publication date: 5-Jul-2024
https://doi.org/10.1117/12.3032986
Dong YLiu YDong YWang YChen M(2024)Multi-knowledge enhanced graph convolution for learning resource recommendationKnowledge-Based Systems10.1016/j.knosys.2024.111521(111521)Online publication date: Feb-2024
https://doi.org/10.1016/j.knosys.2024.111521
El Mourabit IJai Andaloussi SOuchetto OMiyara M(2023)Exploring Collaborative Filtering Algorithms in MOOCs Recommender Systems: A Comprehensive OverviewProceedings of the 6th International Conference on Networking, Intelligent Systems & Security10.1145/3607720.3607742(1-5)Online publication date: 24-May-2023
https://dl.acm.org/doi/10.1145/3607720.3607742
ul Haque MKotaiah B(2023)A Cluster Based Recommendation System for MOOCs2023 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)10.1109/ICCCIS60361.2023.10425224(406-411)Online publication date: 3-Nov-2023
https://doi.org/10.1109/ICCCIS60361.2023.10425224
Sanguino JManrique RMariño O(2023)A Semantic Enhanced Course Recommender System via Knowledge Graphs for Limited User Information ScenariosSN Computer Science10.1007/s42979-023-02399-45:1Online publication date: 19-Dec-2023
https://dl.acm.org/doi/10.1007/s42979-023-02399-4
Mansouri NSoui MAbed M(2023)SFS feature selection with decision tree classifier for massive open online courses (MOOCs) recommendationJournal of Computers in Education10.1007/s40692-023-00291-x11:4(1089-1110)Online publication date: 31-Aug-2023
https://doi.org/10.1007/s40692-023-00291-x
Zhang JWang LMa YJiang QWang B(2023) Research on Personalized Video Matching Algorithm Based on Implicit Feature Transfer and PTransE IEEJ Transactions on Electrical and Electronic Engineering10.1002/tee.2385518:8(1303-1316)Online publication date: 23-Jul-2023
https://doi.org/10.1002/tee.23855
Ahmad HQi CWu ZMuhammad B(2022)ABiNE-CRS: course recommender system in online education using attributed bipartite network embeddingApplied Intelligence10.1007/s10489-022-03758-z53:4(4665-4684)Online publication date: 14-Jun-2022
https://dl.acm.org/doi/10.1007/s10489-022-03758-z
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