Рогушина, Юлія Віталіївна (orcid.org/0000-0001-7958-2557) and Гришанова, І.Ю. (orcid.org/0000-0003-4999-6294) (2025) Chapter ХІV. Use of semantic technologies and reinforcement learning in construction of personal learning pathways . ФОП Ямчинський О.В., м. Київ, Україна, pp. 182-197. ISBN 978-617-8830-09-0
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Abstract
This study explores the challenges of personalizing the learning process in the context of digital transformation and the use of modern semantic technologies that support this process. We consider existing semantic-based standards and tools for storing, retrieval and reuse learning objects. Their semantic analysis focuses on construction personal learning pathways (PLPs) accordinf to individual needs, knowledge and learning goals of students. We propose the application of reinforcement learning methods for PLP constructing based on the concept of service composition: learning objects are interpreted as services with quality of service (QoS) parameters. A modified reinforcement learning method, Rule-based QoS-based Q-Learning, is developed to enable adaptive improvement of strategy selection in dynamic environments, prevent looping and eliminate inefficient actions. The study also represents a software implementation of the proposed method and analyzes prospects for further research, including deep Q-learning and enhanced mechanisms for handling dynamic environments.
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