Learning Activity Sharing and Individualized Recommendation Based on Dynamical Correlation Discovery

Autor:	Jian Chen, Timothy K. Shih, Qun Jin, Xiaokang Zhou
Rok vydání:	2012
Předmět:	Cooperative learning Proactive learning Preference learning Computer science business.industry Active learning (machine learning) Collaborative learning Machine learning computer.software_genre Social learning Synchronous learning Artificial intelligence business computer Action learning
Zdroj:	Advances in Web-Based Learning-ICWL 2012 ISBN: 9783642336416 ICWL
Popis:	In this study, we concentrate on learning activity sharing and individualized recommendation based on dynamical user correlations, in order to support and facilitate the web-based learning process integrated with social streams. A user correlation-based learning activity model is built to demonstrate the relations among user, learning task and learning activity. Based on these, an integrated method is proposed to provide a target user with the possible learning activity as the next learning step, which is expected to enhance the learning efficiency. Finally, design of a Moodle-based prototype system is discussed.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c247a22122e8ccf078f2636fddd9723f https://doi.org/10.1007/978-3-642-33642-3_21 Zobrazit plný text záznamu