학력
Ph.D. University of Georgia, Department of Career and Information Studies
M.A. 서울대학교 교육학과
B.S. 서울대학교 교육학과
주요경력
2024-현재 서울대학교 산업인력개발학과 교수
2020-2024 성균관대학교 교육학과 교수
2018-2020 미국 University of Florida 교수
2017-2018 미국 Northern Illinois University 교수
주요 AI/기술 자문
2026-현재 SK mySUNI AI증강을 위한 내재화 방안 및 직무재설계
2025-현재 삼성바이오로직스 생성형 AI기반 채용시스템
2025-현재 한국교육과정평가원 AI기반 학력진단시스템-국가기초학력지원포털 구축
2025-현재 (주)이즈파크- AI 피플애널리틱스 기반 HR평가시스템 구축
2025-현재 NIA-(주)케이브레인 AI데이터기반행정 역량강화교육
2025-현재 (주)RAG AI기반 자동 서/논/구술형 채점 시스템 구축
2023-2025 (주)LG인화원 AI시대의 미래교육
2024 (주)삼성전자 리더십진단 애널리틱스
주요연구분야
AI시대의 일과 학습
일과 학습을 위한 다중 에이전틱 AI 시스템 오케스트레이션 (Multi-Agentic AI Orchestration for Learning and Work)
AI기반 맞춤형 경력개발 시스템
피플애널리틱스 (People Analytics)
주요 연구실적 (최근 5년)
김동호, 노석준, 박연정, 신서경, & 정한호. (2025). AI 시대의 평가 패러다임 전환: 교육공학적 지향점과 과제. 교육공학연구, 41(3), 1287-1327. |
강태훈, 김동호*, 박찬호, 최상범, & 이재화. (2025). AI 기반 논⋅ 서술형 평가 시스템의 국내⋅ 외 사례 및 향후 전망. 교육연구, 263-280. |
Kim, D., Ding, L., & Cho, T. (2025). Bridging theory and practice: the effects of experiential learning-based simulation training on technology integration competency among pre-service teachers. Journal of Research on Technology in Education, 1-19. [SSCI] |
Lee, J., & Kim, D*. (2025). Levelling up learning in higher education: Gamification of in‐video components to supercharge student learning and achievement in video‐based learning. British Journal of Educational Technology. https://doi.org/10.1111/bjet.13564 [SSCI] |
한은혜, 조태준, & 김동호. (2024). 영성지능이영역초월행동에미치는영향: 일의의미와자기효능감의매개효과를중심으로. 농업교육과인적자원개발, 56(3), 77-100. |
Zheng, H., Branch, R. M., Ding, L., Kim, D., Jung, E., Lu, Z., … & Yoon, M. (2024). The combination of segmentation and self-explanation to enhance video-based learning. Active Learning in Higher Education, 25(2), 285-302. [SSCI] |
김경리, & 김동호*. (2024). 몰입형가상시뮬레이션과학탐구학습효과분석: CAMIL (Cognitive Affective Model of Immersive Learning) 관점기반설계. 교육공학연구, 40(4), 915-953. |
Lee, J., & Kim, D*. (2024). From awareness to empowerment: self-determination theory-informed learning analytics dashboards to enhance student engagement in asynchronous online courses. Journal of Computing in Higher Education, 1-41. [SSCI] |
성은모, 김동호, 신서경, & 이영주. (2023). 인공지능(AI) 의교육적실천을위한가능성과과제. 교육공학연구, 39(스페셜), 1479-1508. |
최경환, & 김동호*. (2023). 동영상기반학습에서하위목표(Sub-goal) 제시와자기모니터링(self-monitoring) 이학습동기및몰입, 학습효과에미치는효과. 열린교육연구, 31(3), 93-120. |
Ding, L., Yoon, M., & Kim, D*.(2023). Unveiling the pedagogical advantage of tutoring‐style videos in an authentic biology class. Journal of Computer Assisted Learning. https://doi.org/10.1111/jcal.12930 [SSCI] |
김경리, & 김동호*.(2023). 3D MUVE (다중참여형가상공간) 를활용한초등연극수업이학습자의자기표현과사회성에미치는영향: 제페토를중심으로. 교육정보미디어연구, 29(3), 599-625. |
Jung, E., Lim, R., & Kim, D*. (2022). A Schema-Based Instructional Design Model for Self-Paced Learning Environments. Education Sciences, 12(4), 271.[SSCI] |
Huang, X., Bernacki, M. L., Kim, D., & Hong, W. (2022). Examining the role of self-efficacy and online metacognitive monitoring behaviors in undergraduate life science education. Learning and Instruction, 101577. [SSCI] |
김유경, 이정원, & 김동호*. (2022). Elastic net 회귀분석을활용한고등학생들의자기주도학습능력예측요인탐색. 한국교육문제연구, 40(2), 83-109. |
Jung, E., Zheng, H., Webster, N., Hamad, A., Demir, F., & Kim, D*. (2021). A Model of Learning Technology Partnership with Vendors: A Systematic Process. Contemporary Educational Technology, 13(4), ep321. |
이정원, & 김동호*(2021). 온라인평가전략상담챗봇개발및사용성평가. 열린교육연구, 29(3), 31-53. |
Kim, D., Jo, I. H., Song, D., Zheng, H., Li, J., Zhu, J., Huang, X., Yan, W., & Xu, Z. (2021). Self-regulated learning strategies and student video engagement trajectory in a video-based asynchronous online course: a Bayesian latent growth modeling approach. Asia Pacific Education Review, 1-13. [SSCI] |
Valle, N., Antonenko, P., Valle, D., Sommer, M., Huggins-Manley, A. C., Dawson, K., Kim, D., & Baiser, B. (2021). Predict or describe? How learning analytics dashboard design influences motivation and statistics anxiety in an online statistics course. Educational Technology Research and Development, 1-27. [SSCI] |
Leite, W. L., Jing, X., Kuang, H., Kim, D., & Huggins-Manley, A. C. (2021). Multilevel mixture modeling with propensity score weights for quasi-experimental evaluation of virtual learning environments. Structural Equation Modeling. https://doi.org/10.1080/10705511.2021.19 [SSCI] |
Kim, D ., Jung, E., Yoon, M., Chang, Y., Park, S., Kim, D., & Demir, F. (2021). Exploring the structural relationships between course design factors, learner commitment, self-directed learning, and intentions for further learning in a self-paced MOOC. Computers and Education, 166. https://doi.org/10.1016/j.compedu.2021.104171. [SSCI] |
Yoon, M., Hill, J., & Kim, D*. (2021). Designing supports for promoting self-regulated learning in the flipped classroom. Journal of Computing in Higher Education, 1-21. DOI: 10.1007/s12528-021-09269-z [SSCI] |