Artificial intelligence in smart learning environments: an overview and case studies
Date Issued
March 2024
Author(s)
Advisor
Abstract
This thesis provides a review of research work on smart classroom technologies, with a focus on emerging and Artificial Intelligence (AI)-related technologies. Smart classroom technologies related to the effective class management that enhance the convenience of classroom environments, the use of teaching aids during the educational process and the use of performance assessment technologies are presented. Apart from discussing the range of technological achievements in each of the aforementioned areas, the role of AI in smart learning environments is thoroughly discussed. Furthermore, the development of two automated artificial intelligence systems that aim to address modern education issues and enhance the professional skills of educators are presented.
The first system aims to maximise the interaction between educators and students during tele-education, by monitoring the actions of the students in online courses while protecting as much as possible students' privacy. In addition, as an attempt to assist educators to improve their teaching style, a second system that assesses the body language of educators was developed. Furthermore, the operation, role and impact of these two proposed systems was assessed with comprehensive quantitative and qualitative evaluations. Conclusions derived from this thesis indicate the acceptance of stakeholders for AI-based systems that can facilitate the educational process through the provision of tools that enhance the educator-student interaction, and tools that help educators improve their teaching style.
The first system aims to maximise the interaction between educators and students during tele-education, by monitoring the actions of the students in online courses while protecting as much as possible students' privacy. In addition, as an attempt to assist educators to improve their teaching style, a second system that assesses the body language of educators was developed. Furthermore, the operation, role and impact of these two proposed systems was assessed with comprehensive quantitative and qualitative evaluations. Conclusions derived from this thesis indicate the acceptance of stakeholders for AI-based systems that can facilitate the educational process through the provision of tools that enhance the educator-student interaction, and tools that help educators improve their teaching style.
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