반응시간에 기반한 수행 오류 예측 = Performance Error Prediction Based on Reaction Times

다국어 초록 (Multilingual Abstract)

Error prediction is important in regard to prevention of danger caused by the human errors. Previous studies have considered only the neurobiological traits or a single factor to predict errors. The present study considered not only the various factors related to errors but also reaction times preceding errors as behavioral traits. In Study 1, the error-preceding trends were extracted from the reaction times preceding errors and these were assigned to clusters. Also, on the basis of the extracted clusters, the error-prediction function was extracted and validated. In Study 2, the error-prediction function was applied in an online manner in order to test whether errors can be predicted in real-time. The results showed that a variety of clusters were extracted from the error-preceding trends, which reflects the diverse factors related to performance errors. Moreover, the error-prediction function predicted the errors and corrects higher than 70% in Study 1, and 68% and 58%, respectively, in Study 2. These findings suggest that human errors are caused by diverse factors and these can be predicted on the basis of behavior traits.

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