CMKT: Concept Map Driven Knowledge Tracing-Reference-Cited by-同舟云学术

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CMKT: Concept Map Driven Knowledge Tracing

Published:2022-08-01 Issue:4 Volume:15 Page:467-480
ISSN:1939-1382
Container-title:IEEE Transactions on Learning Technologies
language:
Short-container-title:IEEE Trans. Learning Technol.

Author:

Lu Yu¹^ORCID,Chen Penghe¹^ORCID,Pian Yang²^ORCID,Zheng Vincent W.³^ORCID

Affiliation:

1. Advanced Innovation Center for Future Education, School of Educational Technology, Faculty of Education, Beijing Normal University, Beijing, China

2. School of Educational Technology, Faculty of Education, Beijing Normal University, Beijing, China

3. Advanced Digital Sciences Center, Singapore

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,General Engineering,Education

Link

http://xplorestaging.ieee.org/ielx7/4620076/9892984/09850398.pdf?arnumber=9850398

Reference84 articles.

1. A Survey on Network Embedding

2. Injecting Logical Background Knowledge into Embeddings for Relation Extraction

3. Harnessing Deep Neural Networks with Logic Rules

4. Knowledge Graph Embedding With Iterative Guidance From Soft Rules

5. metapath2vec

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1. MLC-DKT: A multi-layer context-aware deep knowledge tracing model;Knowledge-Based Systems;2024-11

2. Enhancing knowledge tracing with concept map and response disentanglement;Knowledge-Based Systems;2024-10

3. Enhanced Dynamic Key-Value Memory Networks for Personalized Student Modeling and Learning Ability Classification;Cognitive Computation;2024-08-27

4. Using AI-empowered assessments and personalized recommendations to promote online collaborative learning performance;Journal of Research on Technology in Education;2024-01-22

5. Design and Evaluation of Trustworthy Knowledge Tracing Model for Intelligent Tutoring System;IEEE Transactions on Learning Technologies;2024

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