Abstract
Nowadays, it has been an important issue to adaptively recommend learning strategies for every learner in intelligent tutoring systems (ITS) that covers various areas and subjects. In this paper, three models for learners, learning strategies and learning strategy-oriented services are proposed. The C4.5 decision tree algorithm is adopted to construct a learning strategy tree which contain popular learning strategies used in ITS. Based on those models and the learning strategy decision tree, a learning strategy recommendation agent is proposed in our learning strategy recommendation system (BIT-LSS) to adaptively recommend learning strategies for learners. Questionnaire surveys and experiments are conducted to demonstrate the efficiency of the learning strategy recommendation agent in BIT-LSS.KeywordsIntelligent tutoring systemstrategy recommendation agentlearning strategylearning profile
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
