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Automation of Teaching Processes on e-Learning Platforms Using Recommender Systems

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1037))

Abstract

The aim of this paper is to present the difficulties and limitations of working on e-learning platform. Two models of e-learning applications will be discussed: the classical model and the model realized by the new teaching paradigm in distance learning aspect. Next, the areas of automation of teaching processes on e-learning platforms will be presented as well as problems which result from the implementation of such models. Next, the concept of using recommendation systems in the extended version of the application will be presented. After a brief description of the recommendation algorithms, the principles of positioning the system user in accordance with his knowledge and methods for recommending content for him will be described. The solutions provided are proprietary solutions. The most important relationships between the user’s behavior and the construction of his knowledge model will be described. In the last step, conclusions will be drawn regarding the selection of the best solution for the processes of knowledge automation on distance learning platforms.

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Notes

  1. 1.

    http://www.knowledgegrid.net/~h.zhuge/Knowledge_Flow.htm.

  2. 2.

    https://Vikas.Sindhwani.Org/Recommender.Pdf.

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Correspondence to Marcin Albiniak .

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Albiniak, M. (2020). Automation of Teaching Processes on e-Learning Platforms Using Recommender Systems. In: Bi, Y., Bhatia, R., Kapoor, S. (eds) Intelligent Systems and Applications. IntelliSys 2019. Advances in Intelligent Systems and Computing, vol 1037. Springer, Cham. https://doi.org/10.1007/978-3-030-29516-5_81

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