Shin, Jinnie

Assistant Professor
Research and Evaluation Methodology Program
School of Human Development and Organizational Studies in Education

College of Education
University of Florida
1602 Norman Hall
PO Box 117049
Gainesville, FL 32611
Phone: 352-273-4332
Fax: 352-846-2697
jinnie.shin@coe.ufl.edu

Research Biography

Jinnie Shin, Ph.D., is an Assistant Professor of Research and Evaluation Methodology in the School of Human Development and Organizational Studies in Education within the College of Education at the University of Florida. She has expertise in application of theory-based natural language processing and learning analytics in education research. In her work, she has focused on investigating how to bridge the gap between psychometric analysis and artificial intelligence in education research. Dr. Shin has experience with various international industry projects with the Medical Council of Canada, American College Testing, and the New Zealand Qualifications Authority, which focus on providing effective solutions to complex education problems using deep learning and natural language processing research.

Degrees

Ph.D. in Educational Psychology (Measurement, Evaluation, and Data Science), 2021
University of Alberta

M.Ed. in Educational Psychology (Measurement, Evaluation, and Cognition), 2018
University of Alberta

B.Ed. in Elementary Education (English Education), 2016
Gyeongin National University of Education

Key Professional Appointments

Assistant Professor, School of Human Development and Organizational Studies in Education, College of Education, University of Florida, 2021 – Present

Selected Publications

Book Chapters

Shin, J., Guo, Q., & Gierl, M. J. (2020). Automated essay scoring using deep learning. In M. Khosrow-Pour (Ed.), Handbook of research on modern educational technologies, applications, and management (Vol. 2). IGI-Global. doi: 10.4018/978-1-7998-3476-2

Journal Articles

Shin, J., Chen, F., Chang, L., & Bulut, O. (in press). Analyzing students’ performance in computerized formative assessments to optimize teacher’s test administration decisions using deep learning frameworks. Journal of Computers in Education.

Shin, J., & Bulut, O. (2021). Building an intelligent recommendation system for personalized test scheduling in computerized assessments: A reinforcement learning approach. Behavior Research Methods. https://doi.org/10.3758/s13428-021-01602-9

Bulut, O., Cormier, D. C., & Shin, J. (2020). An intelligent recommender system for personalized test administration scheduling with computerized formative assessments. Frontiers in Education, 5, 1-11. https://doi.org/10.3389/feduc.2020.572612

Shin, J., & Gierl, M. J. (2020). More efficient processes for creating automated essay scoring frameworks: A demonstration of two algorithms. Language Testing, 38(2), 247-272. https://doi.org/10.1177/0265532220937830

Shin, J., Bulut, O., & Gierl, M. J. (2020). Development practices of trusted AI systems among Canadian data scientists. International Review of Information Ethics, 28. https://doi.org/10.29173/irie377

Shin, J., Bulut, O., & Gierl, M. J. (2019). The effect of the most-attractive-distractor location on multiple-choice item difficulty. Journal of Experimental Education, 88(4), 643-659. https://doi.org/10.1080/00220973.2019.1629577

Shin, J., Guo, Q., & Gierl, M. J. (2019). Multiple-choice item distractor development using topic modeling approaches. Frontiers in Psychology, 10, 825. https://doi.org/10.3389/fpsyg.2019.00825

Selected Links

Personal website: https://jinnieshin.netlify.app/