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Interpretable Cognitive State Prediction via Temporal Fuzzy Cognitive Map | IEEE Journals & Magazine | IEEE Xplore

Interpretable Cognitive State Prediction via Temporal Fuzzy Cognitive Map


Abstract:

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved predi...Show More

Abstract:

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying and understanding these factors remain a challenge. Thus, this article proposes the temporal fuzzy cognitive map (tFCM) model, which combines the prediction power of DNNs with the interpretability of fuzzy cognitive maps. In the proposed tFCM model, cognitive states are modeled as fuzzy, multidimensional, and interrelated vectors, which are input to a long short-term memory network for prediction. This integration allows the proposed model to combine the exceptional ability of DNNs to uncover latent factors with the distinct benefits of fuzzy cognitive maps' ability to reveal potential correlations. A comparative experiment was designed and conducted on a large-scale dataset to assess the predictive performance and interpretability of the proposed tFCM model. The results demonstrate tFCM's superior performance and interpretability compared to existing models. The findings of this study contribute to the development of a multidimensional quantitative model to represent cognitive states and an interpretable model architecture for state prediction.
Published in: IEEE Transactions on Learning Technologies ( Volume: 17)
Page(s): 514 - 526
Date of Publication: 22 August 2023

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Author image of Yuang Wei
Shanghai Institute of AI for Education, East China Normal University, Shanghai, China
Yuang Wei received the master's degree in control science and engineering from the North China University of Technology, Beijing, China, in 2022. He is currently working toward the Ph.D. in computer science and technology (specializing in intelligent education) with the East China Normal University, Shanghai, China.
His research largely focuses on knowledge tracing and his current research interest includes the constructio...Show More
Yuang Wei received the master's degree in control science and engineering from the North China University of Technology, Beijing, China, in 2022. He is currently working toward the Ph.D. in computer science and technology (specializing in intelligent education) with the East China Normal University, Shanghai, China.
His research largely focuses on knowledge tracing and his current research interest includes the constructio...View more
Author image of Bo Jiang
Department of Educational Information Technology, East China Normal University, Shanghai, China
Bo Jiang received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2014.
He was an Associate Professor with the Department of Educational Information Technology, Zhejiang University of Technology. He is currently an Associate Professor with the Department of Educational Information Technology, East China Normal University, Shanghai, China. His research interests include lear...Show More
Bo Jiang received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2014.
He was an Associate Professor with the Department of Educational Information Technology, Zhejiang University of Technology. He is currently an Associate Professor with the Department of Educational Information Technology, East China Normal University, Shanghai, China. His research interests include lear...View more

Author image of Yuang Wei
Shanghai Institute of AI for Education, East China Normal University, Shanghai, China
Yuang Wei received the master's degree in control science and engineering from the North China University of Technology, Beijing, China, in 2022. He is currently working toward the Ph.D. in computer science and technology (specializing in intelligent education) with the East China Normal University, Shanghai, China.
His research largely focuses on knowledge tracing and his current research interest includes the construction of knowledge maps and natural language processing models in education.
Yuang Wei received the master's degree in control science and engineering from the North China University of Technology, Beijing, China, in 2022. He is currently working toward the Ph.D. in computer science and technology (specializing in intelligent education) with the East China Normal University, Shanghai, China.
His research largely focuses on knowledge tracing and his current research interest includes the construction of knowledge maps and natural language processing models in education.View more
Author image of Bo Jiang
Department of Educational Information Technology, East China Normal University, Shanghai, China
Bo Jiang received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2014.
He was an Associate Professor with the Department of Educational Information Technology, Zhejiang University of Technology. He is currently an Associate Professor with the Department of Educational Information Technology, East China Normal University, Shanghai, China. His research interests include learner modeling, learning analytics, and computer science education.
Dr. Jiang was the recipient of the 2021 Asia-Pacific Society on Computers in Education Early Career Research Award. He is currently serves on the Editorial Board member of IEEE Transactions on Learning Technologies and Research & Practice in Technology Enhanced Learning. He also serves as the Executive Committee member of the Asia-Pacific Society on Computers in Education.
Bo Jiang received the Ph.D. degree in control science and engineering from Zhejiang University, Hangzhou, China, in 2014.
He was an Associate Professor with the Department of Educational Information Technology, Zhejiang University of Technology. He is currently an Associate Professor with the Department of Educational Information Technology, East China Normal University, Shanghai, China. His research interests include learner modeling, learning analytics, and computer science education.
Dr. Jiang was the recipient of the 2021 Asia-Pacific Society on Computers in Education Early Career Research Award. He is currently serves on the Editorial Board member of IEEE Transactions on Learning Technologies and Research & Practice in Technology Enhanced Learning. He also serves as the Executive Committee member of the Asia-Pacific Society on Computers in Education.View more
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