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A Hybrid Model for E-Learning Resources Recommendations in the Developing Countries

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Published:21 September 2020Publication History

ABSTRACT

E-learning has changed the education style in the developed countries. However, in the developing nations such as the East African (EA) countries, the students are still challenged by the accessibility of online learning materials. In this paper, we sought to alleviate this issue by proposing a recommendation method that helps the students from the developing countries in selecting more appropriate e-learning resources. To achieve this goal, an e-learning dataset composes of 1237 students from three different universities in East Africa is used and the learners' information including contextual, demographic, and ratings predictions are hybridized by applying a developed knowledge-based computational model to generate the recommendations in a unified manner. Results from experimental evaluations are presented and discussed to demonstrate the benefits of the proposed system.

References

  1. Garrison D. R. E-learning in the 21st century: A framework for research and practice. Routledge, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  2. Clark R. C. and Mayer R. E. E-learning and the science of instruction: Proven guidelines for consumers and designers of multimedia learning. John Wiley & Sons, 2016.Google ScholarGoogle ScholarCross RefCross Ref
  3. Bhuasiri W., Xaymoungkhoun O., Zo H., Rho J. J., and Ciganek A. P. Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58, 2 2012), 843--855.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Niyigena J.-P., Jiang Q., Ziou D., Shaw R.-S., and Hasan A. Modeling the Measurements of the Determinants of ICT Fluency and Evolution of Digital Divide Among Students in Developing Countries---East Africa Case Study. Applied Sciences, 10, 7 2020), 2613.Google ScholarGoogle ScholarCross RefCross Ref
  5. Tarus J. K., Niu Z., and Yousif A. A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining. Future Generation Computer Systems-the International Journal Of Escience, 72(Jul 2017), 37--48.Google ScholarGoogle Scholar
  6. Niyigena J.-P., Jiang Q., Hasan A. T., Ziou D., Chen H., and Wang P. ICT Usage and Attitudes Among EAC Undergraduate Students---A Case Study. IEEE Access, 62018), 42661--42674.Google ScholarGoogle ScholarCross RefCross Ref
  7. Niyigena J. P., Jiang Q., Shaw R.-S., and Cai X. A Descriptive Analysis of E-Learning in East Africa. International Conference on Information Technology and Industrial Applications (ITIA), Taiwan, City, 2018.Google ScholarGoogle Scholar
  8. Hirate Y. and Yamana H. Generalized Sequential Pattern Mining with Item Intervals. JCP, 1, 3 2006), 51--60.Google ScholarGoogle Scholar
  9. Adomavicius G. and Zhang J. Classification, ranking, and topic stability of recommendation algorithms. INFORMS Journal on Computing, 28, 1 2016), 129--147.Google ScholarGoogle ScholarCross RefCross Ref
  10. Peterson L. E. K-nearest neighbor. Scholarpedia, 4, 2 2009), 1883.Google ScholarGoogle ScholarCross RefCross Ref
  11. Willmott C. J. and Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Climate research, 30, 1 2005), 79--82.Google ScholarGoogle Scholar

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  1. A Hybrid Model for E-Learning Resources Recommendations in the Developing Countries

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        cover image ACM Other conferences
        ICDLT '20: Proceedings of the 2020 4th International Conference on Deep Learning Technologies
        July 2020
        147 pages
        ISBN:9781450375481
        DOI:10.1145/3417188

        Copyright © 2020 ACM

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        Publication History

        • Published: 21 September 2020

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