[2T4-OS-5a] OS-5

[2T4-OS-5a-04] Deep-IRT for predicting addressing times

〇Wakaba Kishida¹, Emiko Tsutsumi², Maomi Ueno¹ (1. The University of Electro-Communications, 2. The University of Tokyo)

Keywords:Deep Learning, AI, Educational Technology

With the spread of computer-based testings and learning systems, it becomes possible to collect examinees' response data and addressing times that cannot be obtained from paper tests. The previous research pointed out that predicting the examinees' addressing times is important for adaptive learning. This study proposed Deep-IRT to predict the examinees' addressing times based on the Deep-IRT method which provides high accuracy of examinees' response prediction and the parameter interpretability. The proposed method predicts examinees' addressing times by two independent networks: an examinees' speed network and an item network. Empirical experiments demonstrate the effectiveness of the proposed method.