Publication: Application of artificial neural networks for prediction of learning performances
Issued Date
2016-10-19
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2-s2.0-84997770175
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Mahidol University
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SCOPUS
Bibliographic Citation
2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016. (2016), 745-751
Suggested Citation
Permphan Dharmasaroja, Nicha Kingkaew Application of artificial neural networks for prediction of learning performances. 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2016. (2016), 745-751. doi:10.1109/FSKD.2016.7603268 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/43424
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Title
Application of artificial neural networks for prediction of learning performances
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Abstract
© 2016 IEEE. Artificial neural networks (ANNs) have rarely been used in the field of medical education, especially in the prediction of learning performances. This study aims to evaluate the potential application of ANN models for predicting learning performances, in comparison with multivariate logistic regression models. The predictor variables included demographics, high-school backgrounds, first-year grade-point averages, and composite scores of examinations during the course. Medical student learning performances were represented by their normalized T-scores of the total examination score. Three ANN models, including a support vector machine, were used to predict performance. A comparison between the models, based upon areas under the receiver operating characteristic curve values, showed no significant differences between the ANNs and logistic regression models (p > 0.05 for all pairs in the comparison). This work thus reveals the promising potential for the application of ANNs in the prediction of learning performances, in the field of medical education.
