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Showing results for supervisor “TING, Fridolin Sze Thou”

Developing Collaborative Generative AI Pedagogies to Enhance Student Learning Outcomes Across Disciplines

Current use of generative AI in education is often a lonely, isolated experience, with a single student interacting with a chatbot. This limits collaboration and leaves teachers out of the learning process. However, teachers themselves often feel unprepared to integrate AI into their teaching, lacking the digital competencies, pedagogical knowledge, and confidence needed to useContinue reading “Developing Collaborative Generative AI Pedagogies to Enhance Student Learning Outcomes Across Disciplines”

Prompt Engineering for Effective Personalized Learning: Unlocking the Potential of Large Language Models for Science and Mathematics Education

Large language models (LLMs) like ChatGPT demonstrate a remarkable ability to generate personalized and contextualized content by relating disparate ideas. This project proposes harnessing LLMs to make learning in science and mathematics more captivating and comprehensible. We will develop techniques for students to interact with LLMs to create customized conceptual descriptions and examples connecting courseContinue reading “Prompt Engineering for Effective Personalized Learning: Unlocking the Potential of Large Language Models for Science and Mathematics Education”