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Machine Learning Paradigms: Theory and Application pp 169–187Cite as

Towards a Personalized Learning Experience Using Reinforcement Learning

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 801))

Abstract

Cognitive computing has become one of the most promising fields, especially in education, where building adaptive learning systems that provide different learning paths and material based on learners’ states and needs are developed. One of the most challenging issues in designing such systems is to correctly identify the factors that will influence the learning experience, especially when these factors highly differ from one learner to another. In addition, for one particular learner, the values of these factors change with time. In this paper, we present an approach that adapts to the most influential factors in learning in a way that varies from one learner to another and in different learning settings, including individual and collaborative learning. The approach utilizes reinforcement learning (RL) for building an intelligent environment that, not only does it provide a method for suggesting suitable learning materials, but it also provides a methodology for accounting for the continuously-changing students’ states and acceptance of the technology. We evaluate our system through simulations. The obtained results are promising and show the feasibility of the proposed approach. In addition, we propose a “rich” personalized learning system that relies on RL as its backend, while utilizing big data tools and learning analytics to continuously feed the system with new generated states.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Engineering Mathematics Department, Cairo University, Giza, Egypt

    Doaa Shawky

  2. Center for Learning Technologies, Zewail City of Science and Technology, Giza, Egypt

    Ashraf Badawi

Authors
  1. Doaa Shawky
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  2. Ashraf Badawi
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Corresponding author

Correspondence to Doaa Shawky .

Editor information

Editors and Affiliations

  1. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Shawky, D., Badawi, A. (2019). Towards a Personalized Learning Experience Using Reinforcement Learning. In: Hassanien, A. (eds) Machine Learning Paradigms: Theory and Application. Studies in Computational Intelligence, vol 801. Springer, Cham. https://doi.org/10.1007/978-3-030-02357-7_8

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