Kyungbin Kwon

Papers

Total Citations

124

H-Index

About

Kyungbin Kwon is an educational technology researcher whose work sits at the intersection of artificial intelligence education, computational thinking, and innovative pedagogical approaches for K-12 learners. Kwon's most influential contribution examines middle school students' naive conceptions of artificial intelligence, uncovering common misconceptions that shape how young learners understand AI — a timely and widely recognized study that has accumulated 79 citations since its 2023 publication. Equally compelling is Kwon's sustained investigation into embodied learning as a vehicle for making abstract computational thinking concepts accessible to young children. A 2022 study involving first and second graders demonstrated how physical, movement-based activities simulating robot programming tasks can scaffold early understanding of foundational CT concepts, earning 36 citations and establishing Kwon as a meaningful voice in early childhood computing education. Building on this thread, a 2024 study extended the embodied learning framework into mixed-reality environments, where students mapped computational concepts like sequencing and loops onto their own bodily movements. Together, Kwon's body of work advances a learner-centered vision for technology education, emphasizing that even the most abstract digital concepts can be made tangible and meaningful through thoughtful, embodied instructional design.