Dr. Choi Presented to the Training and Certification Team at Amazon Web Services
Dr. Jaehwa Choi gave an invited presentation entitled, "n-Layer Computerized Item Modeling Practice with CAFA AIG: Period Four Implies Innovation."
Dr. Jaehwa Choi
Dr. Jaehwa Choi
Associate Professor, Educational Research
School: Graduate School of Education and Human Development
Department: Educational Leadership
Contact:
Email:
Dr. Jaehwa Choi
Office Phone:
(202) 994-2602
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.
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. To delve deeper into his contributions to the CAFA project, including access to sample codes, articles, and live demonstrations, please refer to cafalab.com/
Ph.D., University of Maryland
M.A., University of Maryland
B.A., Department of Business Administration, Sogang University
B.A., Department of Philosophy, Sogang University
Tian, C., & Choi, J. (2023). The Impact of Item Model Parameter Variations on Person Parameter Estimation in Computerized Adaptive Testing With Automatically Generated Items. Applied Psychological Measurement, 0(0). https://doi.org/10.1177/01466216231165313
Choi, J. (2020). Educational Reform in the Digital Age: Backgrounds of Big Data based Intelligent Learning Analytics Platform, Educational Development, 220, 44-50.
Choi, J. (2019). Assessment Engineering for Learning Analytics, Educational Development, 214, 42-45.
Choi, J., Yoon, K., & Kim, S. (2019). Computerized Item Modeling Practice with CAFA Automatic Item Generation. Clarksville, MD: CAFA Lab, Inc.
Choi, J. (2019). Automatic Item Generation with Machine Learning Techniques: A Pathway to Intelligent Assessments. In Jiao, H. & Lissitz, R. W. (Eds.). Applications of artificial intelligence to assessment. Charlotte, NC: Information Age Publisher.
Choi, J., Chen, J., & Harring, J. R. (2019). Logistic growth modeling with Markov chain Monte Carlo estimation. Journal of Modern Applied Statistical Methods, 18(1), eP2997. doi: 10.22237/jmasm/1556669820
Choi, J., & Zhang, X. (2019). Computerized Item Modeling Practices using Computer Adaptive Formative Assessment Automatic Item Generation System: A Tutorial, The Quantitative Methods for Psychology, 15(3), 214-225. doi: 10.20982/tqmp.15.3.p214
Tekleselassie, A. A., & Choi, J. (2019). Understanding School Principal Attrition and Mobility Through Hierarchical Generalized Linear Modeling. Educational Policy. https://doi.org/10.1177/0895904819857825
Choi, J. (2018). Estimating Structural Equation Models within a Bayesian Framework: A Concrete Example of a Markov chain Monte Carlo Method. Biometrics and Biostatistics International Journal, 7(2): 00191. DOI: 10.15406/bbij.2018.07.00191
Choi, J., Kim, H., & Pak, S. (2018). Evaluation of Automatic Item Generation Utilities in Formative Assessment Application for Korean High School Students. Journal of Educational Issues, 4(1), 68-89. doi:10.5296/jei.v4i1.
Young, D. & Choi, J. (2018). Information and Computer Technologies for Improving International Assessment. In S. Swayze & V. Ford (Eds.), Innovative Applications of Knowledge Discovery and Information Resources Management. PA: IGI Global. doi:10.4018/978-1-5225-5829-3
Choi, J. (2018). Roles and Impacts of Automatic Item Generation on Assessment Research, Practice, and Policy. In S. Swayze & V. Ford (Eds.), Innovative Applications of Knowledge Discovery and Information Resources Management. PA: IGI Global. doi:10.4018/978-1-5225-5829-3
Choi, J., Kim, S., & Yoon, K. (2017). CAFA AIG Manual: Computer Adaptive Formative Assessment Automatic Item Generation User’s Guide [System Manual], 2nd edition. Clarksville, MD: CAFA Lab, Inc.
Choi, J. (2017). Next Generation Item and Test Development: A Practical Introduction to Automatic Item Generation. Washington, D.C.: Assessment, Testing and Measurement Technical Report Series, The George Washington University.
Beveridge, S., Appleyard, J., Choi, J., & DiNardo, J. (2017). Application of the Knowledge Validation Inventory - Revised to Examine Individual and Regional Variation Training Needs of Rehabilitation Counselors, Education and Training Issues in Forensic Vocational Analysis, 16(2).
Zeglin, R. J., Hergenrather, K. C., Poppen, P. J., Choi, J., Zea, M.C., & Reisen, C. (2017). Latino Sexual Beliefs Scale: An Exploratory Factor Analysis of Latino MSM, Archives of Sexual Behavior, doi:10.1007/s10508-017-0988-3.
Choi, J., & Levy, R. (2017). Markov chain Monte Carlo Estimation Methods for Structural Equation Modeling: A Comparison of Subject-level Data and Moment-level Data Approaches. Biometrics and Biostatistics International Journal, 6(5): 00182. DOI: 10.15406/bbij.2017.06.00182
Choi, J., Kim, S., & Yoon, K. (2017). K-Math Workbook Grade 7. Clarksville, MD: CAFA Lab, Inc.
Choi, J. (2017, January). The Rise of Assessment Engineering in 4th Industrial Revolution. Invited article of the 2017 newsletter of the Korean Society for Educational Evaluation, Seoul, Korea.
Choi, J., Kim, S., & Yoon, K. (2016). K-Math Workbook Grade 6. Clarksville, MD: CAFA Lab, Inc.
Choi, J. (2016). Introduction to Assessment Engineering. Assessment, Testing, and Measurement Technical Report Series. The George Washington University, Washington DC.
Choi, J., & Lee, J. (2016). Book review on the next generation of testing: common core standards, smarter-balanced, PARCC, and the nationwide testing movement. Teachers College Record, Date Published: November 14, 2016. http://www.tcrecord.org ID Number: 21738.
Dardick, W., & Choi, J. (2016). Teacher Empowered Assessment System: Assessment for the 21st Century. Journal of Applied Educational and Policy Research, 2(2).
Marotta, S., Shaine, M., & Choi, J. (2015). Posttraumatic growth among combat veterans: A proposed developmental pathway. Psychological Trauma: Theory, Research, Practice, and Policy.
Choi, J., Kang, M., Kim, N., Dardick, W., & Zhang, X. (2015). A smart way of coping with Common Core challenges - Introduction to CAFA SmartWorkbook. Journal of Educational Issues, 1(2), 70-89.
Chen, J., Choi, J., Stapleton, L. & Weiss, B. (2014). An empirical evaluation of mediation effect analysis with manifest and latent variables using Markov chain Monte Carlo and alternative estimation methods. Structural Equation Modeling: A Multidisciplinary Journal, 21(2).
Choi, J., Kim, S., & Yoon, K. (2014). CAFA Automatic Item Generation (v 1.0 Beta) System: Computer Adaptive Formative Assessment Client Application for Automatic Item Generation [Computer System]. eMathTest, Inc.
Choi, J., Kim, S., & Yoon, K. (2014). CAFA Smart Workbook (v 1.0 Beta) System: Computer Adaptive Formative Assessment Client Application for Common Core Math Workbook [Computer System]. eMathTest, Inc.
Chen, J., Zhang, D., & Choi, J. (2014). Estimation of the latent mediated effect with ordinal data using the limited-information and Bayesian full-information approaches. Behavioral Research Methods.
Marmarosh, C., Bieri, K., Schutt, J., Barone, C., & Choi, J. (2014). The insecure psychotherapy base: Using client and therapist attachment styles to understand the early alliance. Psychotherapy.
Stewart, J. F., Mallery, C., & Choi, J. (2013). College student persistence: A multilevel analysis of distance learning course completion at the crossroads of disability. Journal of College Student Retention: Research, Theory & Practice, 15(3), 367-385.
Levy, R. & Choi, J. (2013). An introduction to Bayesian structural equation modeling. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd ed.). Greenwood, CT: Information Age Publishing, Inc.
Choi, J. & Kim, S. (2013). Reliability. In Kim, S. (Eds.), Educational measurement (4th ed. Trans. in Korean). New York: American Council on Education and Macmillan.
Tekleselassie, A., Mallery, C., & Choi, J. (2013). Applying the multivariate model to unpack the gender gap in college access among African Americans and Caucasians. Journal of Negro Education, 82(2), 139-156.
Choi, J., Kim, S., & Yoon, K. (2013). CAFA Smart Assignment (v 1.0 Beta) System: Computer Adaptive Formative Assessment Client Application for School Assignments [Computer System]. eMathTest, Inc.
Marmarosh, C., Nikityn, M., Moehringer, J., Ferraioli, L., Kahn, S., Cerkevich, A., Choi, J., & Reisch, E. (2013). Adult attachment, attachment to the supervisor, and the supervisory alliance: How they relate to novice therapists’ perceived counseling self-efficacy. Psychotherapy, 50(2), 178-88.
Choi, J., Kim, S., & Yoon, K. (2012). CAFA (v 1.0 Beta) System: Computer Adaptive Formative Assessment System for Educational Services [Computer System]. eMathTest, Inc.
Choi, J., Kim, S., Chen, J., & Dannels, A. S. (2011). A comparison of maximum likelihood and Bayesian Estimation for Polychoric Correlation using Monte Carlo simulation. Journal of Educational and Behavioral Statistics, 36(4), 523-549.
Choi, J., Dunlop, M., Chen, J., & S. Kim. (2011). A comparison of different approaches for coefficient alpha for ordinal data. Journal of Educational Evaluation, 24(2), 485-506.
Tekleselassie, A., Mallery, C., & Choi, J. (2011). Applying the multivariate model to unpack the gender gap in college access among African Americans and Caucasians. Graduate School of Education and Human Development Working Paper Series. The George Washington University.
Choi, J. (2010). ezIA User’s Guide Korean Version [Software Manual], 1st edition.
Kroopnick, H. M., Chen, J., Dayton, C. M., & Choi, J. (2010). Assessing classification bias in latent class analysis: Comparing resubstitution and leave-one-out methods. Journal of Modern Applied Statistical Methods, 9(1), 52-63.
Choi, J., Peters, M., & Mueller, R. (2010). Correlational analysis of ordinal data: From Pearson's r to Bayesian Polychoric Correlation. Asia Pacific Education Review, 11, 459-466.
Stewart, J. F., Mallery, C., & Choi, J. (2010). A multilevel analysis of distance learning achievement: Are college students with disabilities making the grade? Journal of Rehabilitation, 76(2), 27-39.
Choi, J., Fan, W., & Hancock, G. R. (2009). A note on confidence intervals for two-group latent mean effect size measures. Multivariate Behavioral Research, 44(3), 396-406.
Choi, J., Harring, J. R., & Hancock, G. R. (2009). Latent growth modeling for logistic response functions. Multivariate Behavioral Research, 44(5), 620-645.
Marmarosh, C., Gelso, C., Markin, R., Majors, R., Mallery, C., & Choi, J. (2009). The real relationship in psychotherapy: Relationships to adult attachments, working alliance, transference, and therapy outcome. Journal of Counseling Psychology, 56(3), 337-350.
Chen, J., & Choi, J. (2009). A comparison of maximum likelihood and expected a posteriori estimation for polychoric correlation using Monte Carlo simulation. Journal of Modern Applied Statistical Methods, 8, 337-354.
Choi, J., Chen, J., & Kim, S. (2009). BayesPCC (v 3.0.0): A stand-alone Microsoft Windows software program for estimating Polychoric correlation matrices using Bayesian estimation methods [Computer software].
Chen, J., Choi, J., & Kim, S. (2009). BayesPCC for Windows User’s Guide [Software Manual], 2nd edition.
Choi, J., Kim, S., & Yoon, K. (2009). ezIA (v 1.0.0): A Microsoft Excel Add-In for Test Item Analysis [Computer Software]. Delta Sigma Soft, Inc.
Choi, J., Kim, S., & Yoon, K. (2009). ezIA (v 1.0.0): A Microsoft Excel Add-In for test item analysis [Computer software].
Choi, J., & Chen, J. (2009). ezIA User’s Guide [Software Manual], 2nd edition.
Choi, J., Chen, J., & Kim, S. (2007). EAPPCC: A Matlab subroutine for estimating polychoric correlation matrices using an Expected A Posteriori estimation method. [Matlab Subroutine].
Choi, J., Chen, J., & Kim, S. (2007). EAPPCC for Windows User’s Guide [Software Manual], 1st edition.
Choi, J., Chen, J., & Kim, S. (2007). EAPPCC: Matlab Subroutine User’s Guide [Software Manual].
Hancock, G. R., & Choi, J. (2006). A vernacular for linear latent growth models. Structural Equation Modeling: A Multidisciplinary Journal, 13, 352-377.
- Quantitative Methods
- Assessment Knowledge Engineering
- Computer Adaptive Formative Assessment
- November 2023 - Dr. Jaehwa Choi gave two presentations at the 2023 Beyond Multiple Choice Conference: 1) Paper Presentation: "Prompt Engineering for Adaptive and Responsible Learning (PEARL): An Introduction" and 2) Panel Discussion: "AI and inclusivity: Bridging the equity gap."
- October 2023 - Dr. Jaehwa Choi presented, "Integrating Generative AI in Assessment Engineering: Hands on Training with ChatGPT," at the 2023 Northeastern Educational Research Association Conference.