Machine Learning Algorithms for Recommendation of Learning CS Courses in E-Learning Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Intelligent Recommender Systems (RS) on conceptual learning of Computer Science (CS) have been widely applied in the teaching of universities, in order to provide a personalized education path, by automatically identifying the students' preferences and the situations of learning. This paper firstly reviews the applications in CS learning for non-CS majors, using the major recommendation techniques, and that analyzes the results of CS Learning for non-CS majors in Macao Polytechnic University (MPU). The results show that different specialties should adopt different recommendation algorithms, in order to achieve the desired teaching effect, since the different professional student on a concept of cognition, and have a specific learning style. For the same course outline, the teaching materials, learning paths and practice activity etc, will vary, according to their professionals.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Information Science and Systems, ICISS 2022
PublisherAssociation for Computing Machinery
Pages136-141
Number of pages6
ISBN (Electronic)9781450396837
DOIs
Publication statusPublished - 26 Aug 2022
Event5th International Conference on Information Science and Systems, ICISS 2022 - Virtual, Online, China
Duration: 26 Aug 202228 Aug 2022

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th International Conference on Information Science and Systems, ICISS 2022
Country/TerritoryChina
CityVirtual, Online
Period26/08/2228/08/22

Keywords

  • Computer Science
  • E-Learning Environments
  • Machine Learning Algorithms
  • Non-CS Majors
  • Personalized Learning Path
  • Recommender Systems

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