An Instructional and Collaborative Learning System with Content Recommendation

Abstract

n'ith the rapid development of Internet, e-learning bas become a new teaching and learning mode. However, lots oj e-learning systems deployed on Internet are just electronic learning materials with vety limited interactivity and diagnostic capability. This paper presents an integrated e-learning environment named iCLSR. hirstly, iCLSR provides an online environtnent for instruction and collaborative learning, which i;ets rid of the constraints of time and space. Second, online teaching and learning evaluation data from instructors and learners can be collected by iCLSR and can be analyzed with an improved PSK-means clustering alç^orithm. Third, the learning object lists can be recotntnendedfor learners based on online evaluation results and their learning iiistoiy. The application ofiCtSR demonstrates that it can recommend appropriate learning materials jor ¡earners, inspire comtuunication between learners and instructors, save time for users and therefore improve the instructional effects and learning performance.

Multi Strategies-Based Resources Recommendation in Learning Team

“…M. Aiken [7] studied task knowledge and task techniques in virtual team and found that task-technology fit mediates between knowledge sharing and team satisfaction. HP Andres [8] studied knowledge sharing in global virtual teams through collaborative engineering analysis; X. Zheng [9] built an Instructional and Collaborative Learning System using content recommendation. Zhang Z [10] studied the recommendation problem in statistical learning based on Ontology-Based collaborative filtering recommendation algorithm).…”

Study on Learning Resources Recommendation Based on Tasks in Team Collaboration

“…M. Aiken [5] studied task knowledge and task techniques in virtual team and found that task-technology fit mediates between knowledge sharing and team satisfaction. HP Andres [6] studied knowledge sharing in global virtual teams through collaborative engineering analysis; X. Zheng [7] built an Instructional and Collaborative Learning System using content recommendation. Zhang Z [8] studied the recommendation problem in statistical learning based on Ontology-Based collaborative filtering recommendation algorithm).…”