@inproceedings{e0653aa5377d4323b5e7c21b22921a0c,
title = "DiKT: Dichotomous Knowledge Tracing",
abstract = "Knowledge tracing models the cognitive process of skill acquisition of a student to predict the current knowledge state. Based on cognitive processing theory, we regard student knowledge state in dichotomous view in alignment with Performance Factor Analysis (PFA). Assuming that a student{\textquoteright}s correct and incorrect responses are fundamentally different for modeling a student{\textquoteright}s knowledge state, we propose a Dichotomous Knowledge Tracing (DiKT), a novel knowledge tracing network with a dichotomous perspective on a student{\textquoteright}s knowledge state. We modify the network{\textquoteright}s value memory by dividing it into two memories, each encoding recallable and unrecallable knowledge to precisely capture the student knowledge state. With the proposed architecture, our model generates a knowledge trajectory that instantly and accurately portrays a student{\textquoteright}s knowledge level based on learning history. Empirical evaluations demonstrate that our proposed model achieves comparable performance on benchmark educational datasets.",
keywords = "Deep learning, Dynamic Key-Value Memory Network, Knowledge tracing, Learning analytics, Performance Factor Analysis, Student modeling",
author = "Seounghun Kim and Woojin Kim and Heeseok Jung and Hyeoncheol Kim",
note = "Funding Information: Acknowledgements. This work was supported by Institute for Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2020-0-00368, A Neural-Symbolic Model for Knowledge Acquisition and Inference Techniques). Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 17th International Conference on Intelligent Tutoring Systems, ITS 2021 ; Conference date: 07-06-2021 Through 11-06-2021",
year = "2021",
doi = "10.1007/978-3-030-80421-3_5",
language = "English",
isbn = "9783030804206",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "41--51",
editor = "Cristea, {Alexandra I.} and Christos Troussas",
booktitle = "Intelligent Tutoring Systems - 17th International Conference, ITS 2021, Proceedings",
address = "Germany",
}