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A Survey of Learner and Researcher Related Challenges in E-learning Recommender Systems

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Learning Technology for Education Challenges (LTEC 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 734))

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Abstract

In recent years, recommender systems have been widely used to support online learning in educational institutions. However, there are still some challenges experienced by learners and researchers hindering the full implementation and utilization of recommender systems in e-learning environments. In this paper, we review the main learner and researcher related challenges of e-learning recommender systems. This was achieved by carrying out a systematic literature review of relevant journal papers on e-learning recommender systems with a view to identifying and classifying the challenges as either learner or researcher challenges. The results of the survey reveal that successful implementation and utilization of e-learning recommender systems is hindered by some challenges categorized in this review as learner and researcher challenges. The paper also identifies some possible solutions from different studies for alleviating the challenges as well as the limitations. The implications of this study will be vital in assisting learners and educational institutions utilize recommender systems to support online teaching and learning.

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Notes

  1. 1.

    https://www.coursera.org/.

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Acknowledgment

This work is supported by the National Natural Science Foundation of China (No. 61370137), China Mobile Research Foundation Project (Nos. 2015/5-9 and 2016/2-7) and the 111 Project of Beijing Institute of Technology.

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Authors and Affiliations

  1. School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China

    John K. Tarus & Zhendong Niu

  2. Directorate of ICT, Moi University, Eldoret, Kenya

    John K. Tarus

  3. School of Information Sciences, University of Pittsburgh, Pittsburgh, PA, USA

    Zhendong Niu

Authors
  1. John K. Tarus
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  2. Zhendong Niu
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Correspondence to Zhendong Niu .

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Editors and Affiliations

  1. University of Staffordshire, Stoke-on-Trent, Staffordshire, United Kingdom

    Lorna Uden

  2. Universidad Tecnica Federico Santa Maria, Valparaiso, Chile

    Dario Liberona

  3. Electronic, Beijing Jiaotong University, Beijing, China

    Yun Liu

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Tarus, J.K., Niu, Z. (2017). A Survey of Learner and Researcher Related Challenges in E-learning Recommender Systems. In: Uden, L., Liberona, D., Liu, Y. (eds) Learning Technology for Education Challenges. LTEC 2017. Communications in Computer and Information Science, vol 734. Springer, Cham. https://doi.org/10.1007/978-3-319-62743-4_11

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  • DOI: https://doi.org/10.1007/978-3-319-62743-4_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-62742-7

  • Online ISBN: 978-3-319-62743-4

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