Investigating the Incorporation of Robotics, Artificial Intelligence, and Machine Learning Algorithms to Support Hands-on Learning and Adaptive Tutoring Systems in Education

Abstract

The integration of robotics, artificial intelligence (AI), and machine learning (ML) algorithms
in education aims to revolutionise the learning experience by providing enhanced handson
learning opportunities and adaptive tutoring systems. This investigation explores the
various ways in which these advanced technologies can be harnessed to support and
improve educational outcomes. Combining these technologies offers a transformative
approach to education, enriching traditional pedagogical methods with interactive,
personalised learning opportunities. Robotics enables experiential learning, bridging
theory with practice through tangible engagement with robots. AI and ML algorithms,
on the other hand, facilitate adaptive tutoring systems that customise educational
content and feedback in real-time based on student’s unique needs. This paper explores
the potential of such integration, examining its impact on learning outcomes and
the development of critical skills. Additionally, it addresses the challenges inherent in
implementing these innovations and proposes strategies for effective integration. By
investigating the fusion of robotics, AI, and ML in education, this study contributes
significantly to understanding how technology can revolutionise teaching and learning
processes. It highlights the potential of these advanced technologies to create more
dynamic, inclusive, and effective educational experiences.