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Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 39

Reinforcement Learning based Intelligent System for Personalized Exam Schedule

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DOI: http://dx.doi.org/10.15439/2024F302

Citation: Proceedings of the 19th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 39, pages 549–553 ()

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Abstract. Personalized learning has been proving to be useful concept in the learning of a student. Artificial Intelligence (AI) which has revolutionized many aspects of our lives has also been glowingly used in the education sector. One of the fascinating AI technique, the Reinforcement Learning (RL) is considered as the perfect tool to develop personalized solution in the education. RL algorithms have the ability to take into account personal characteristics of each student. This work presents the development of personalized exam scheduler using RL. The intelligent examination scheduler consider several parameters for training such as age, academic year, past education performance, discipline, number of courses, and gap between two exams. The trained RL agent then able to provide examination schedule to a student depending on a student personal record, interests and abilities. The preliminary results are encouraging and more research would bring useful contribution of AI in various aspects of learning process of a student

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