Abstract
Virtual education combines didactic strategies with information and communication technologies to facilitate student access, interaction, and active participation. Academic monitoring and tutoring should be conducted within virtual learning environments (VLE) with the support of a virtual tutor to provide personalized advice and feedback. The review integrates theories, didactic strategies, learning styles, and computational models. This research presents a systematic review of literature on tutoring models in virtual education. The objective is to identify intelligent tutoring systems (ITS) models that use autonomous agents and expert systems in virtual learning environments. Additionally, strategies for implementing ITS in VLEs are presented. The identified models focus on adaptive learning, learning styles, and student skills for developing a specific course. It is proposed to design an architecture in the Moodle platform for academic monitoring of students in the online modality using autonomous agents. A holistic approach is considered, combining the efficiency of AI with didactic strategies that personalize learning through friendly human-machine interaction. The research on ITS models focuses on adaptive learning, considering new technological trends, while also considering the interaction between the student and the virtual tutor.
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This work has been supported by the Ministry of Science and Innovation, the State Research Agency (AEI) of the Government of Spain, and by the European Regional Development Fund (ERDF) of the European Commission under the COordinated intelligent Services for Adaptive Smart areaS (COSASS) project (Ref: PID2021-123673OB-C33) Group.
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López-Goyez, J.P., González-Briones, A., Chamorro, A.F. (2025). Models of Intelligent Tutoring Systems Based on Autonomous Agents for Virtual Learning Environments: A Systematic Literature Review. In: Mathieu, P., De la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Digital Twins: The PAAMS Collection. PAAMS 2024. Lecture Notes in Computer Science(), vol 15157. Springer, Cham. https://doi.org/10.1007/978-3-031-70415-4_16
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