Keunjae Kim

Papers

Total Citations

124

H-Index

About

Keunjae Kim is an educational researcher whose work sits at the intersection of emerging technologies, artificial intelligence literacy, and computational thinking (CT) education. Kim's scholarship focuses on how young learners conceptualize and engage with complex abstract concepts in computer science and AI, with particular attention to innovative pedagogical approaches that make these ideas accessible across grade levels. Among Kim's most recognized contributions is an exploration of middle school students' naive conceptions of AI concepts, examining how these mental models evolve over time — a study that has garnered 79 citations and established Kim as a meaningful voice in K-12 AI literacy research. Complementing this work, Kim has pioneered the use of embodied learning as a bridge to computational thinking, demonstrating through classroom-based studies how physical, movement-driven activities can help early primary students internalize abstract CT concepts such as sequencing and loops. This line of inquiry extends into mixed-reality environments, where Kim has explored how blending physical and digital experiences further supports CT problem-solving skills. With cumulative citations surpassing 120 across these key works, Kim's research offers practical, evidence-based strategies for educators seeking to introduce foundational computer science concepts to students at the earliest stages of their academic journey.