@article{ART003130958},
author={Bokyung Kim and Yeonseop Lee and Jang-hoon Shin and Yusung Jang and Wansuk Choi},
title={Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2024},
volume={29},
number={10},
pages={113-120}
TY - JOUR
AU - Bokyung Kim
AU - Yeonseop Lee
AU - Jang-hoon Shin
AU - Yusung Jang
AU - Wansuk Choi
TI - Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach
JO - Journal of The Korea Society of Computer and Information
PY - 2024
VL - 29
IS - 10
PB - The Korean Society Of Computer And Information
SP - 113
EP - 120
SN - 1598-849X
AB - This study aims to assess the effectiveness of machine learning models in predicting the pass rates of physical therapy students in national exams. Traditional grade prediction methods primarily rely on past academic performance or demographic data. However, this study employed machine learning and deep learning techniques to analyze mock test scores with the goal of improving prediction accuracy. Data from 1,242 students across five Korean universities were collected and preprocessed, followed by analysis using various models. Models, including those generated and fine-tuned with the assistance of ChatGPT-4, were applied to the dataset. The results showed that H2OAutoML (GBM2) performed the best with an accuracy of 98.4%, while TabNet, LightGBM, and RandomForest also demonstrated high performance. This study demonstrates the exceptional effectiveness of H2OAutoML (GBM2) in predicting national exam pass rates and suggests that these AI-assisted models can significantly contribute to medical education and policy.
KW - Machine Learning;Predictive Analysis;H2OAutoML(GBM2);Deep Learning;Educational Policy;ChatGPT
DO -
UR -
ER -
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang and Wansuk Choi. (2024). Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach. Journal of The Korea Society of Computer and Information, 29(10), 113-120.
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang and Wansuk Choi. 2024, "Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach", Journal of The Korea Society of Computer and Information, vol.29, no.10 pp.113-120.
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang, Wansuk Choi "Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach" Journal of The Korea Society of Computer and Information 29.10 pp.113-120 (2024) : 113.
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang, Wansuk Choi. Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach. 2024; 29(10), 113-120.
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang and Wansuk Choi. "Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 113-120.
Bokyung Kim; Yeonseop Lee; Jang-hoon Shin; Yusung Jang; Wansuk Choi. Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach. Journal of The Korea Society of Computer and Information, 29(10), 113-120.
Bokyung Kim; Yeonseop Lee; Jang-hoon Shin; Yusung Jang; Wansuk Choi. Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach. Journal of The Korea Society of Computer and Information. 2024; 29(10) 113-120.
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang, Wansuk Choi. Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach. 2024; 29(10), 113-120.
Bokyung Kim, Yeonseop Lee, Jang-hoon Shin, Yusung Jang and Wansuk Choi. "Exploring Predictive Models for Student Success in National Physical Therapy Examination: Machine Learning Approach" Journal of The Korea Society of Computer and Information 29, no.10 (2024) : 113-120.
