AI-TRANSFORMATIVE TOOLS IN TACKLING CHALLENGES IN TEACHING OF PHYSICS IN TERTIARY INSTITUTIONS

Abstract

The paper explores AI-Transformative tools in tackling challenges in teaching and learning physics in tertiary institutions. Adopting a typology design and conceptual approach, the study examines the available literature on AI-driven tools and their adoption in physics education. Artificial Intelligence can provide personalized learning experiences, instant feedback, and adaptive assessments, addressing traditional teaching methods’ limitations. The study highlights three key benefits of AI in physics education: enhanced student engagement, increased accuracy, and improved teacher support. The paper identifies various AI-driven tools, such as Robot motor, drone, High Performance Computing (HPC), ChatGPT, Chatbot Einstein, and physics learning tutor, that can help address teaching physics challenges. However, it also acknowledges AI implementation challenges like validity and reliability concerns, technology dependence, data security issues, and biased discrimination. The study emphasizes the need for teachers to effectively integrate AI tools with traditional teaching methods and suggests that governments and institutions should provide necessary equipment and support for this technological advancement. Overall, the study concludes that AI, combined with basic computer tools, can significantly improve learning outcomes in physics education if carefully implemented and monitored to ensure effectiveness and fairness.