Taiwo Feyijimi is an AI researcher and doctoral candidate at the Engineering Education Transformations Institute (EETI), University of Georgia, Athens. With over 15 years of leadership experience across tech and education sectors – as Founder/Co-Founder, CEO, Technology Strategist, Technical Lead, and EdTech professional – he bridges industry and academia with a unique, interdisciplinary perspective. His expertise includes strategic system design, exploratory data analysis, machine learning, natural language processing, and prompt engineering for LLMs. His research enhances undergraduate engineering education by aligning student competencies with labor market needs. He uses computational intelligence and Q methodology to extract insights and understand student learning perspectives. Central to his work is the integration of AI tools to foster metacognition, self-regulation, and collaborative problem-solving. He is developing a framework that merges Q methodology with AI, grounded in learning theories and Vygotsky’s sociocultural theory of learning, to improve regulatory learning in STEM. He has also created two pioneering AI-integrated qualitative research frameworks, including an AI-assisted thematic analysis tool, both under review for U.S. copyright protection.
Taiwo Feyijimi is an AI researcher and doctoral candidate at the Engineering Education Transformations Institute (EETI), University of Georgia, Athens. With over 15 years of leadership experience across tech and education sectors – as Founder/Co-Founder, CEO, Technology Strategist, Technical Lead, and EdTech professional – he bridges industry and academia with a unique, interdisciplinary perspective. His expertise includes strategic system design, exploratory data analysis, machine learning, natural language processing, and prompt engineering for LLMs. His research enhances undergraduate engineering education by aligning student competencies with labor market needs. He uses computational intelligence and Q methodology to extract insights and understand student learning perspectives. Central to his work is the integration of AI tools to foster metacognition, self-regulation, and collaborative problem-solving. He is developing a framework that merges Q methodology with AI, grounded in learning theories and Vygotsky’s sociocultural theory of learning, to improve regulatory learning in STEM. He has also created two pioneering AI-integrated qualitative research frameworks, including an AI-assisted thematic analysis tool, both under review for U.S. copyright protection.