Jaehwa Choi

Jaehwa Choi is an Associate Professor and Director of the Assessment, Testing, and Measurement Program in the Department of Educational Leadership at George Washington University. Recently, Dr. Choi has been at the forefront of Generative AI research, especially with Large Language Models (LLM) such as Generative Pre-trained Transformer (GPT), where he has been actively developing and training Generative AI-based approaches in Assessment Engineering. This includes groundbreaking work in Prompt Engineering for Adaptive and Responsible Learning (PEARL), Prompt Engineering for Academic Research (PEAR), and Prompt Engineering for Advanced Knowledge and Skill (PEAKS).

Dr. Choi received his Ph.D. from the University of Maryland in the Department of Measurement, Statistics, and Evaluation in 2006. His extensive research interests span both traditional and modern Assessment Engineering techniques and methods. This spectrum includes Generative Adaptive Learning Modeling (GALM), Automatic Item Generation (AIG), Bayesian Learning, Markov chain Monte Carlo (MCMC) optimization, and the aforementioned Generative AI-driven methodologies employing LLMs like GPT. For details on his course teachings, academic program affiliations, and publication list, please refer to his GW faculty page.

As the principal investigator of the Computer Adaptive Formative Assessment (CAFA) project since 2012, Dr. Choi has conducted numerous Assessment Engineering projects in partnership with esteemed global corporate and institutional entities. These include Samsung Electronics, Korea Institute of Curriculum and Evaluation, Cisco Systems, Children’s Hospital in Southern California, Ministry of Education in Singapore, Singapore Examinations and Assessment Board, Graduate Management Admission Council, and Amazon Web Services, Inc.