2013International Journal of Distance Education TechnologiesRequires access

An Instructional and Collaborative Learning System with Content Recommendation

Xiangwei Zheng, Hongwei Ma, Yan Li

Open publisher page 3 citations

Abstract

With the rapid development of Internet, e-learning has become a new teaching and learning mode. However, lots of e-learning systems deployed on Internet are just electronic learning materials with very limited interactivity and diagnostic capability. This paper presents an integrated e-learning environment named iCLSR. Firstly, iCLSR provides an online environment for instruction and collaborative learning, which gets 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 algorithm. Third, the learning object lists can be recommended for learners based on online evaluation results and their learning history. The application of iCLSR demonstrates that it can recommend appropriate learning materials for learners, inspire communication between learners and instructors, save time for users and therefore improve the instructional effects and learning performance.

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What this paper is about

With the rapid development of Internet, e-learning has become a new teaching and learning mode. However, lots of e-learning systems deployed on Internet are just electronic learning materials with very limited interactivity and diagnostic capability. This paper presents an integrated e-learning environment named iCLSR. Firstly, iCLSR provides an online environment for instruction and collaborative learning, which gets 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 algorithm. Third, the learning object lists can be recommended for learners based on online evaluation results and their learning history. The application of iCLSR demonstrates that it can recommend appropriate learning materials for learners, inspire communication between learners and instructors, save time for users and therefore improve the instructional effects and learning performance.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

With the rapid development of Internet, e-learning has become a new teaching and learning mode. However, lots of e-learning systems deployed on Internet are just electronic learning materials with very limited interactivity and diagnostic capability. This paper presents an integrated e-learning environment named iCLSR. Firstly, iCLSR provides an online environment for instruction and collaborative learning, which gets 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 algorithm. Third, the learning object lists can be recommended for learners based on online evaluation results and their learning history. The application of iCLSR demonstrates that it can recommend appropriate learning materials for learners, inspire communication between learners and instructors, save time for users and therefore improve the instructional effects and learning performance.

Key concepts: Computer science, Interactivity, Multimedia, The Internet, Collaborative learning, Educational technology, Synchronous learning, Distance education

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