Youngjin Lee

Previous Scheduled Teaching

Published Intellectual Contributions

Book Chapter

• Hsu, Y., Meyen, E., Lee, Y. (2018). Understanding emotional analytics for student engagement: An instructional visual design perspective. Student-centered virtual learning environments in higher education. 70-102. Hershey, PA,

Conference Proceeding

• Carter, E.S., Cockerham, D.P., Lee, Y. (2024). Gamification in the Undergraduate Chemistry Course: A Systematic Review. Society for Information Technology & Teacher Education International Conference. 1808–1811. Waynesville, NC, Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/primary/p/224214/

Journal Article

• Goodman, A., Lee, Y., Elieson, S., Knezek, G. (2024). Using self-regulated learning theory and learning analytics to identify explanatory variables affecting learning outcomes in online/hybrid undergraduate calculus. Journal of Computers in Mathematics and Science Teaching. 42 (2) 125-154. Waynesville, NC, Association for the Advancement of Computing in Education.
• Lee, Y. Exploring educators' sentiments towards the use of ChatGPT in education.
• Lee, Y. Assessing accuracy and utility of an intelligent tutor employing Retrieval-Augmented Generation (RAG) for statistics education.
• Lee, Y. (2023). The effect of course format change on learning behaviors and performance of students. International Journal on E-Learning. 22 (2) 159-176. Waynesville, NC, Association for the Advancement of Computing in Education.
• Lee, Y. (2022). Identifying prerequisite courses in undergraduate biology using machine learning. Journal of Data Science. (1-16) 1–16.
• Wang, X., Lee, Y., Lin, L., Mi, Y., Yang, T. (2021). Analyzing instructional design quality and students’ reviews of 18 courses out of the Class Central Top 20 MOOCs through systematic and sentiment analyses. The Internet and Higher Education. 50 100810.
• A, L., Lee, Y. A Confirmatory Factor Analysis (CFA) on Pleasurable Learning Experiences (PLLEX) Scale.
• A, L., Lee, Y. (2020). College students' perception of pleasure in learning: Designing gameful educational gamification. International Journal on E-Learning. 19 (2) 93–123.
• Lee, Y. (2019). Estimating student ability and problem difficulty using Item Response Theory (IRT) and TrueSkill. Information Discovery and Delivery. 47 (2) 67-75.
• Gu, P., Lee, Y. (2019). Promoting students' motivation and use of SRL strategies in the Web-based mathematics learning environment. Journal of Educational Technology Systems. 47 (3) 391-410.
• Lee, Y. (2018). Effect of uninterrupted time-on-task on students’ success in Massive Open Online Courses (MOOCs). Computers in Human Behavior. 86 174-180.
• Lee, Y. (2018). Using Self-Organizing Map (SOM) and clustering to investigate problem solving patterns in the Massive Open Online Course (MOOC): An exploratory study. Journal of Educational Computing Research. 57 (2) 471-490.
• Lee, Y. (2017). Modeling students’ problem solving performance in the computer-based mathematics learning environment. International Journal of Information and Learning Technology. 34 (5) 385-395.
• Sullivan, D.K., Goetz, J.R., Gibson, C.A., Mayo, M.S., Washburn, R.A., Lee, Y., Ptomey, L.T., Donnelly, J.E. (2016). A virtual reality intervention (Second Life) to improve weight maintenance: Rationale and design for an 18-month randomized trial. Contemporary Clinical Trials. 46 77–84.
• Lee, Y. (2016). Predicting students' problem solving performance using Support Vector Machine. Journal of Data Science. 14 231–244.
• Lee, Y. (2015). Analyzing log files to predict students’ problem solving performance in a computer-based physics tutor. Educational Technology & Society. 18 (2) 225–236.
• Lee, Y. (2015). Developing iPad-based physics simulations that can help people learn Newtonian physics concepts. The Journal of Computers in Mathematics and Science Teaching. 34 (3) 299–325.