Ji Hyun Yu

Previous Scheduled Teaching

Published Intellectual Contributions

Journal Article

• Yu, J., Kim, H., Hsieh, C., Dong, L., Duan, S., Watson, S.L. (2025). Linguistic patterns in reflective writing: Analyzing graduate students’ professional aspirations. Educational Technology Research and Development.
• Yu, J., Park, Y., Kye, B. (2025). Identifying learner profiles and predicting performance in a digital textbook: A case study of K-8 schools in South Korea. Educational Media International.
• An, Y., Yu, J., James, S. (2025). Investigating the higher education institutions’ guidelines and policies regarding the use of generative AI in teaching, learning, research, and administration. 22 (Article number: 10) International Journal of Educational Technology in Higher Education. https://doi.org/10.1186/s41239-025-00507-3
• Yu, J., Rho, J. (2025). Just seeing can be deceiving: GenAI-supported design case for critical visual literacy. International Journal of Designs for Learning.
• Dong, L., Watson, S.L., Yu, J., Lowell, V. (2025). Revisiting the interrelationships between social presence and cognitive presence in asynchronous online courses: Insights from epistemic network analysis. Online Learning Journal.
• Olesova, L., Garcia, B., Yu, J. (2025). Integrating care ethics in GenAI-enhanced instructional design: A framework for inclusive and equitable higher education practices. The Journal of Applied Instructional Design.
• Yu, J., Dong, L., Hsieh, C., Tan, Y., Duan, S., Watson, S.L. (2024). Instructional designers’ professional futures: Insights from Best Possible Self and epistemic network analysis. Educational Technology Research and Development. 1-35.
• Yu, J. (2024). Integrating actionable analytics into learning design for MOOCs: A design-based research. Journal of Computing in Higher Education.
• Yu, J., Chauhan, D., Iqbal, R., Yeoh, E. (2024). Mapping academic perspectives on AI in education: trends, challenges, and sentiments in educational research (2018–2024). Educational Technology Research and Development.
• Yu, J., Chauhan, D. (2024). Trends in NLP for personalized learning: LDA and sentiment analysis insights. Education and Information Technologies.
• Duan, S., Hsieh, C., Dong, L., Jiang, S., Xu, F., Watson, S.L., Yu, J. (2024). Unveiling novice instructional designers’ professional identity: Exploring dispositions through future-oriented reflections. Higher Education. 1-21. https://doi.org/10.1007/s10734-024-01366-z
• Yu, J. (2023). Learning experience design as collective praxis: Two design cases from higher education.
• Nawaz, S., Srivastava, N., Yu, J., Baker, R., Khan, A., Kennedy, G., Bailey, J., Baker, R. (2022). How difficult is the task for you? Modeling and analysis of students' task difficulty sequences in a simulation-based POE environment.
• Watson, W., Watson, S., Fehrman, S., Yu, J., Janakiraman, S. (2020). Examining international students’ attitudinal learning in a higher education course on cultural and language learning.
• Yu, J., Watson, S. (2020). Identifying subtypes of attitudinal learning among MOOCs learners: A latent profile analysis.
• Watson, S., Yu, J., Alamri, H., Watson, W. (2020). Preservice teachers’ technology integration attitude change in a course implementing digital badges.
• Watson, W., Yu, J., Watson, S. (2018). Perceived attitudinal learning in a self-paced versus fixed-schedule MOOC.
• Watson, S., Watson, W., Yu, J., Caskurlu, S., Janakiraman, S., Fiosk, H. (2018). Attitudinal learning and its relation to gender, age, ethnicity, enrolment purpose, and most impactful learning activity in the science of happiness MOOC.
• Watson, S., Watson, W., Yu, J., Alamri, H., Mueller, C. (2017). Learner profiles of attitudinal learning in a MOOC: An explanatory sequential mixed-methods study.
• Park, Y., Yu, J., Jo, I. (2016). Clustering blended learning courses by online behavior data: A case study in a Korean higher education institute.
• Capobianco, B., Yu, J., French, B. (2015). Effects of engineering design-based science on elementary school science students’ engineering identity development across gender and grade.
• Capobianco, B., Yu, J. (2014). Using the construct of care to frame engineering as a caring profession toward promoting young girls' participation.
• Yu, J., Sun, Y., Strobel, J. (2012). A conceptual K-6 teacher competency model for teaching engineering.
• Ertmer, P., Newby, T., Yu, J., Liu, W., Tomory, A., Lee, Y., Sendurur, E., Sendurur, P. (2011). Facilitating students’ global perspectives: Collaborating with international partners using Web 2.0 technologies.
• Ertmer, P., Newby, T., Liu, W., Tomory, A., Yu, J., Lee, Y. (2011). Students’ confidence and perceived value for participating in cross-cultural wiki-based collaborations.
• Yu, J., Park, B. (2006). Development of the personal learning blog system for supporting self-regulated learning.

Contracts, Grants and Sponsored Research

Grant - Research

• Yuan, X., Guo, X. (Co-Principal), Keathly, D.M. (Co-Principal), Morozov, K. (Co-Principal), Maharjan, A. (Co-Principal), Zaruba, G. (Co-Principal), Yu, J. (Supporting), "Supplement Funding: Attracting and Cultivating AI Scholars through Multi-faceted Mentoring, Research Experiences, and Cohort Building," sponsored by NSF, Federal, $25000 Funded. (2026 - 2027).
• Yu, J., Chen, H. (Co-Principal), "Partner, Not Crutch: Designing a Metacognitive Nudge to Promote AI Co-Regulation," sponsored by Learning Institute, University of North Texas, $5000 Funded. (2026 - 2026).

Grant - Teaching

• Yu, J. (Principal), "2025 UNT Open Educational Resources (OER) Grant Program: Instructional Material Development for LTEC 5601: Introduction to Learning Analytics," sponsored by University of North Texas, University of North Texas, $4000 Funded. (2025 - 2025).