RL Techniques for Personalized Education through E-Learning
Information and communication technology (ICT ) is becoming more significant in education as a result of global education reform. We expand the idea of personalization from e-commerce to education, referred to as personalized education (PE ), to fully utilize the enormous amount of relevant and accessible hypermedia that can potentially be accessed on the Internet. PE includes identifying and comprehending the needs and competencies of each individual student before adopting and implementing the most effective teaching methods and multimedia content to close the knowledge gap. An agent-based framework for the construction of a personalized education system (PES ) has been presented in order to deploy the right personalization strategies and fulfill the learning needs of a wide range of learners in various methods [1]. Wu et al. [2] explored the use of reinforcement learning (RL ) to develop data-driven policies for tutorial planning in adaptive training systems. See also [3].
Example:
An example for personalized education through E-learning using RL is to learn and characterize user behavior from their interactions with a web-based learning system, see [3].
Reference:
[1] Fok, A.W.P.; Ip, H.H. Personalized Education (PE ) oe Technology Integration for Individual Learning. 2004. Available online https://citeseerx.ist.psu.edu/document repid=rep1&type=pdf&doi=0e4d60d16aec5ca0202f59957161c9a91a50d56a (accessed on
2 February 2023 )
[2] Wu, D.;Wang, S.; Liu, Q.; Abualigah, L.; Jia, H. An improved teaching-learning-based optimization algorithm with reinforcement learning strategy for solving optimization problems. Comput. Intell. Neurosci. 2022, 2022.
[3] Fahad Mon, B.; Wasfi, A.; Hayajneh, M.; Slim, A.; Abu Ali, N. Reinforcement Learning in Education: A Literature Review. Informatics 2023, 10, 74. https://doi.org/10.3390/informatics10030074
2 February 2023 )
[2] Wu, D.;Wang, S.; Liu, Q.; Abualigah, L.; Jia, H. An improved teaching-learning-based optimization algorithm with reinforcement learning strategy for solving optimization problems. Comput. Intell. Neurosci. 2022, 2022.
[3] Fahad Mon, B.; Wasfi, A.; Hayajneh, M.; Slim, A.; Abu Ali, N. Reinforcement Learning in Education: A Literature Review. Informatics 2023, 10, 74. https://doi.org/10.3390/informatics10030074
Author of the tip:
Ivo Nowak
HAW Hamburg