Learning recommendation with formal concept analysis for intelligent tutoring system
Journal article
Authors/Editors
Strategic Research Themes
Publication Details
Author list: Muangprathub J., Boonjing V., Chamnongthai K.
Publisher: Elsevier
Publication year: 2020
Journal: Heliyon (2405-8440)
Volume number: 6
Issue number: 10
Start page: 1
End page: 10
Number of pages: 10
ISSN: 2405-8440
eISSN: 2405-8440
Languages: English-Great Britain (EN-GB)
View in Web of Science | View on publisher site | View citing articles in Web of Science
Abstract
Computer Science; Learning recommendation; Formal concept analysis; Intelligent tutoring system; Adaptive learning © 2020 The Author(s)The aim of this research was to develop a learning recommendation component in an intelligent tutoring system (ITS) that dynamically predicts and adapts to a learner's style. In order to develop a proper ITS, we present an improved knowledge base supporting adaptive learning, which can be achieved by a suitable knowledge construction. This process is illustrated by implementing a web-based online tutor system. In addition, our knowledge structure provides adaptive presentation and personalized learning with the proposed adaptive algorithm, to retrieve content according to individual learner characteristics. To demonstrate the proposed adaptive algorithm, pre-test and post-test were used to evaluate suggestion accuracy of the course in a class for adapting to a learner's style. In addition, pre- and post-testing were also used with students in a real teaching/learning environment to evaluate the performance of the proposed model. The results show that the proposed system can be used to help students or learners achieve improved learning. © 2020 The Author(s)
Keywords
Formal concept analysis, Intelligent tutoring system, Learning recommendation
Contact Information