Chungnam National University · Department of Sports Science
Haeyong Chun
Research Assistant Professor · Chungnam National University
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Publications
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Presentations
6
Grants
Research Assistant Professor · Chungnam National University
I am a Research Assistant Professor at Chungnam National University (CNU), South Korea. I received my Ph.D. in Kinesiology from Michigan State University, where I specialized in the Psychosocial Aspects of Sport and Physical Activity under the guidance of Dr. Nicholas D. Myers. I also hold a Sports Analytics Graduate Certificate from MSU.
The central mission of my research is to advance and apply psychometric methodology to solve critical measurement challenges in health research. A complementary mission is to develop computational psychometrics and physical-activity intervention models that leverage artificial intelligence, including large language models (LLMs), to improve measurement quality and enable scalable, personalized behavior change support.
I earned a Master of Sport Science and dual Bachelor's degrees in Mathematics Education and Sport Science from Chungnam National University in South Korea.
Developing scalable, personalized PA intervention models, including conversational agents powered by AI and LLMs, to support behavior change in diverse populations.
Developing reporting and estimator guidance that strengthens construct validity in applied health research, with focus on physical activity self-efficacy measurement.
Factor analysis with ordered categorical indicators (CFA/ESEM), measurement invariance, and simulation-based evaluation of factor enumeration and latent vs. sum scoring for defensible, interpretable scores.
Applying advanced analytic methods to population-level health data, including NHANES datasets, to understand relationships between physical activity, sedentary behavior, and health outcomes.
Designing and conducting simulation studies to evaluate the performance of psychometric methods under varied conditions, informing best practices for applied researchers.
Incorporating AI—especially LLM-based persona generation and computational psychometrics—to stress-test measurement models and support the development of scalable, personalized PA intervention models.