Year: 2026 | Month: April-June | Volume: 10 | Issue: 2 | Pages: 61-77
DOI: https://doi.org/10.52403/gijash.20260209
Educational Robotics and Artificial Intelligence in Adaptive Learning: A Review of Current Advances, Challenges, and Research Opportunities
Baidyanath Sou
Department of Computer Science, Jagannath Kishore College, Purulia, India
Corresponding Author: Baidyanath Sou
ABSTRACT
The integration of Artificial Intelligence (AI) and Educational Robotics has created new opportunities for adaptive and personalized learning. Advances in Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Computer Vision (CV), and Reinforcement Learning (RL) have transformed educational robots into intelligent learning companions capable of adapting to individual learner needs. This review examines the role of AI-driven educational robotics in adaptive learning by synthesizing its theoretical foundations, enabling technologies, architectural frameworks, educational impacts, challenges, and future directions. The review highlights key adaptive learning concepts, including learner modelling, personalization, and continuous feedback, and discusses how AI technologies support intelligent perception, decision-making, and learner adaptation. The findings suggest that AI-driven educational robots can enhance personalized learning, learner engagement, accessibility, and instructional effectiveness. However, challenges related to data privacy, algorithmic bias, scalability, and teacher–robot collaboration remain significant. Future advances in generative AI, multimodal interaction, lifelong learning systems, and immersive technologies are expected to further strengthen the capabilities of educational robotics. Therefore, AI-driven educational robotics represents a promising pathway toward more adaptive, inclusive, and learner-centred education.
Keywords: Educational Robotics; Artificial Intelligence in Education; Adaptive Learning; Personalized Learning; Intelligent Tutoring Systems; Human–Robot Interaction.
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