Feedback based on the combination of self-con dence and correctness of an answer canhelp learners identify misconceptions. In this study, we propose a self-con dence estimation methodto aid the development of a system for vocabulary learning. The proposed method is based onthe examination of eye movement and handwriting behaviors. To evaluate the performance of theproposed method, we examined the eye movement of 7 participants and the handwriting behaviorof 8 participants while completing English spelling tests. The results revealed that our methodwas able to classify self-con dence into two classes with 87% accuracy in the typing dataset and79% in the handwriting dataset.
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