Hye Rin Lee

Lee’s courses include Cognition and Motivation Science in Learning. Her Achievement, Identity, and Motivation (A.I.M.) Lab focuses on understanding psychological processes that are foundational to learning but can also become barriers to success. The lab primarily examines motivation, defined as task-related beliefs that energize and direct individuals toward action, and metacognition, defined as the beliefs and processes involved in understanding, monitoring, and regulating one’s own learning.

Hye Rin Lee

Hye Rin Lee

Visiting Assistant Professor of Cognitive and Behavioral Science

Curriculum Vitae

Program Affiliations

Education

  • National Science Foundation STEM Education Organizational Postdoctoral Research Fellow, University of Georgia, 2026 
  • National Science Foundation STEM Education Individual Postdoctoral Research Fellow, University of Delaware, 2024 
  • Ph.D. Education with a Specialization in Human Development in Context, University of California, Irvine, 2022 
  • B.A. Psychology and Sociology, Franklin and Marshall College, 2018 

Research 

Hye Rin Lee’s research examines self-regulated learning processes, with a focus on motivation and metacognition, both independently and jointly. Situated primarily within STEM contexts, her work spans three interconnected lines of research: (a) designing interventions to promote motivation and metacognition; (b) examining how motivation, metacognition, or both relate to academic outcomes over time; and (c) developing innovative approaches that advance understanding of motivation and metacognition by challenging traditional assessment paradigms. Through this work, she aims to foster more inclusive and equitable learning environments in which all students can thrive and excel in STEM. 

Teaching 

  • Cognition (CBSC 1120) 
  • Motivation Science in Learning (CBSC 2500) 

Selected Publications

  • Rodriguez, F., Lee, H., Holton, A., Li, Q., & Rutherford, T. (in press). How do college students prepare for exams? A learning analytics approach to observing self-regulation, cramming behaviors, and exam performance. Journal of Educational Psychology. 
     
  • Lee, H., Chen, X.-Y., & Ramirez, K. F. (in press). The motivational benefits of observing and serving as a role model for minoritized college students. In H. Watt, E. Mackenzie, & B. Reid O’Connor (Eds.), Research handbook on gender and STEM. Elgar Publishing. 
     
  • Lee, H., Ramirez, K. F., Rutherford, T., Veng, S., & Eccles, J. S. (2026). In their own words: How engineering transfer students discuss expectancies, values, and self-regulation when giving advice to peers. Contemporary Educational Psychology, 86, 102466. https://doi.org/10.1016/j.cedpsych.2026.102466 
     
  • Cao, Z., Zhao, Y., Dicke, A., Eccles, J. S., & Lee, H. (2026). Does filming peer-support videos benefit the peer models? Examining engineering transfer students’ emotional experiences when creating advice videos for community college students. Community College Journal of Research and Practice, 1–19. https://doi.org/10.1080/10668926.2026.2656668
     
  • Tang, X., Zhang, J., Zhang, Y., & Lee, H. (2026). Psychometric network analyses and directed acyclic graphs for developmental and educational science: A tutorial. In B. Laursen (Ed.), Cambridge elements: Research methods for developmental science. Cambridge University Press. https://doi.org/10.1017/9781009645911 
     
  • Lee, H., Student, S. R., Rutherford, T., Collie, R. J., & Bart, A. C. (2025). Exploring subject-specific and course-specific latent profiles of motivation in computer science. Learning and Individual Differences, 120, 102686. https://doi.org/10.1016/j.lindif.2025.102686
     
  • Gaspard, H., von Keyserlingk, L., Parrisius, C., Rubach, C., Yamaguchi-Pedroza, K., Lee, H., Spengler, M., Fischer, C., Heckhausen, J., & Eccles, J. S. (2025). Reciprocal associations between confidence in getting social support and academic expectancies and subjective task values: Stronger for first-generation and transfer students. British Journal of Educational Psychology, 95(4), 1023–1046. https://doi.org/10.1111/bjep.12751 
     
  • Rutherford, T., Lee, H., Bart, A. C., Rodrigues, A., & Englert, B. (2024). How self-beliefs, values, and belonging change and relate with performance during introductory computer science. Computer Science Education, 36(1), 166–202. https://doi.org/10.1080/08993408.2024.2429058 
     
  • Karamarkovich, S. M., Lee, H., & Rutherford, T. (2024). It’s not quite linear for all: Examining changes in mathematics expectancies and values across two years in elementary school. The Elementary School Journal, 125(2), 1–33. https://doi.org/10.1086/732866
     
  • Lee, H., Safavian, N., Dicke, A., & Eccles, J. S. (2024). Investigating engineering undergraduates’ agentic and communal career values in writing responses. Journal of Engineering Education, 113(2), 308–329. https://doi.org/10.1002/jee.20584 
     
  • Denaro, K., Molinaro, M., Fiorini, S., Matz, R. L., Mead, C., Motika, M., Tarchinski, N., Valdivia Medinaceli, M., Carson Byrd, W., Koester, B., Lee, H., McKay, T., & Sato, B. K. (2024). A multi-institutional cluster analysis to identify groups of courses with exemplary opportunity gaps for undergraduate students in the biological sciences. CBE—Life Sciences Education, 23(4), ar53. https://doi.org/10.1187/cbe.24-02-0051
     
  • Lee, H., Rutherford, T., Hanselman, P., Rodriguez, F., Ramirez, K. F., & Eccles, J. S. (2024). Role models in action through YouTube videos for engineering community college students. Research in Higher Education, 65(5), 1007–1039. https://doi.org/10.1007/s11162-023-09772-5 
     
  • Bart, A. C., Englert, M., Aromando, J., Lee, H., & Rutherford, T. (2024). The CS1 Python bakery: A modern “batteries included” open-source curriculum with all the fixings. In Proceedings of Innovation and Technology in Computer Science Education. https://doi.org/10.1145/3649217.3653630 
     
  • Glandorf, D., Lee, H., Orona, G., Pumptow, M., Yu, R., & Fischer, C. (2024). Temporal and between-group variability in college dropout prediction. In Proceedings of the 14th International Conference on Learning Analytics and Knowledge. https://doi.org/10.1145/3636555.3636906
     
  • Lee, H., Tang, X., Alvarez-Vargas, D., Yang, J., Bailey, D. H., Simpkins, S., Safavian, N., Gaspard, H., Salmela-Aro, K., Moeller, J., Eccles, J. S., & Wigfield, A. (2023). Networks and directed acyclic graphs: Initial steps to efficiently examine causal relations between expectancies, values, and prior achievement. Current Psychology, 43(8), 7547–7563. https://doi.org/10.1007/s12144-023-04871-z
     
  • Lee, H., Santana, L. M., McPartlan, P., & Eccles, J. S. (2023). Components of engagement in a saying-is-believing exercise. Current Psychology, 42(17), 14903–14918. https://doi.org/10.1007/s12144-022-02782-z
     
  • Lee, H., Yang, K., Rutherford, T., Ramirez, K. F., & Eccles, J. S. (2023). Low-income transfer engineering undergraduates’ perceived benefits and costs of online learning during COVID-19. Frontiers in Education, 8, 1–12. https://doi.org/10.3389/feduc.2023.1233978
     
  • Fiorini, S., Tarchinski, N., Pearson, M., Valdivia Medinaceli, M., Matz, R. L., Lucien, J., Lee, H., Koester, B., Denaro, K., Caporale, N., & Carson Byrd, W. (2023). Major curricula structures for disciplinary acculturation that contribute to student minoritization. Frontiers in Education, 8, 1–16. https://doi.org/10.3389/feduc.2023.1176876
     
  • Rutherford, T., Lee, H., & Duck, K. (2023). Dynamic relations between motivation and performance in a mathematics learning technology. Learning and Individual Differences, 107, 102346. https://doi.org/10.1016/j.lindif.2023.102346
     
  • Copp, D. A., Dicke, A., Denaro, K., Lee, H., Wolken, M., Rao, A. E., & Valdevit, L. (2023). Exploring the impact of a supportive scholarship program on engineering transfer students’ learning strategies. In Proceedings of IEEE Frontiers in Education. https://doi.org/10.1109/FIE58773.2023.10343327
     
  • Lee, H., Veng, S., Cao, Y., Baer, J., Rutherford, T., & Bart, A. C. (2023). Work-in-progress: Exploring the computer science curriculum from undergraduate students’ perspectives. In Proceedings of the American Society for Engineering Education—ASEE 2023. https://doi.org/10.18260/1-2–44419
     
  • Lee, H., Ramirez, K. F., Forde, N. Q., Cao, Z., Dicke, A., & Denaro, K. (2023). Work-in-progress: Guidelines on developing writing prompts and exploring how its quality predicts outcomes in a YouTube role model intervention. In Proceedings of the American Society for Engineering Education—ASEE 2023. https://doi.org/10.18260/1-2–44271
     
  • Dicke, A., Copp, D. A., Nikkhah, D., Denaro, K., Lee, H., & Valdevit, L. (2023). Work-in-progress: Exploring the use of faculty and peer mentoring as a tool to support engineering transfer students’ transition. In Proceedings of the American Society for Engineering Education—ASEE 2023. https://doi.org/10.18260/1-2–44465
     
  • Dicke, A., Denaro, K., Rao, A. E., Copp, D., Lee, H., Diggs-Yang, G., & Valdevit, L. (2023). Supporting low-income engineering transfer students’ transition from community college to a 4-year university through a comprehensive scholarship program. In Proceedings of the American Society for Engineering Education—ASEE 2023. https://doi.org/10.18260/1-2–43107
     
  • Lee, H., Rutherford, T., & Bart, A. C. (2023). Logs and surveys of reviewing behaviors in an introductory computer science course: Their motivational antecedents and relation to performance. In Proceedings of the 7th Educational Data Mining for Computer Science Education (CSEDM) Workshop. 
     
  • von Keyserlingk, L., Rubach, C., Lee, H., Heckhausen, J., & Eccles, J. S. (2022). College students’ motivational beliefs and use of goal-oriented control strategies integrating two theories of motivated behavior. Motivation and Emotion, 46(5), 601–620. https://doi.org/10.1007/s11031-022-09957-y
     
  • Tang, X., Lee, H., Wan, S., Gaspard, H., & Salmela-Aro, K. (2022). Situating expectancy and subjective task values across grades, domains, and countries: A network approach. AERA Open, 8, 1–16. https://doi.org/10.1177/23328584221117168
     
  • Moeller, J., von Keyserlingk, L., Spengler, M., Gaspard, H., Lee, H., Yamaguchi-Pedroza, K., Yu, R., Fischer, C., & Arum, R. (2022). Risk and protective factors of college students’ psychological well-being during the COVID-19 pandemic: Emotional stability, mental health, and household resources. AERA Open, 8, 1–26. https://doi.org/10.1177/23328584211065725
     
  • Nikkhah, D., Copp, D. C., Denaro, K., Buswell, N. T., Diggs, G., Lee, H., Valdevit, L., & Dicke, A. (2022). Experiences of faculty mentoring engineering transfer students. In Proceedings of the American Society for Engineering Education—ASEE 2022. https://doi.org/10.18260/1-2–40597
     
  • Lee, H., von Keyserlingk, L., Arum, R., & Eccles, J. S. (2021). Why do they enroll in this course? Undergraduates’ course choice from a motivational perspective. Frontiers in Education, 6, 1–9. https://doi.org/10.3389/feduc.2021.641254
     
  • Rodriguez, F., Lee, H., Rutherford, T., Fischer, C., Potma, E., & Warschauer, M. (2021). Using clickstream data mining techniques to understand and support first-generation college students in an online chemistry course. In Proceedings of the 11th International Conference on Learning Analytics and Knowledge. https://doi.org/10.1145/3448139.3448169
     
  • Lee, H., McPartlan, P., Umarji, O., Li, Q., & Eccles, J. S. (2020). Just a methodological cautionary note: The jingle jangle of self-related beliefs in motivational measures. Journal of Educational and Psychological Research, 2(2), 72–95. https://doi.org/10.33140/JEPR
     
  • Salgado, L., Artis, S., Lee, H., & Valdevit, L. (2020). Low-income community transfer students’ motivation to pursue an engineering degree. In Proceedings of the American Society for Engineering Education—ASEE 2020. https://doi.org/10.18260/1-2–35349