Quality Meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing-Reference-Cited by-同舟云学术

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Quality Meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing

Published:2020-11 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE International Conference on Data Mining (ICDM)
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Author:

Bi Haoyang,Ma Haiping,Huang Zhenya,Yin Yu,Liu Qi,Chen Enhong,Su Yu,Wang Shijin

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9338245/9338248/09338437.pdf?arnumber=9338437

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2. Dual-channel feature enhancement cognitive diagnosis framework for student performance prediction;Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024);2024-07-11

3. RDGT: Enhancing Group Cognitive Diagnosis With Relation-Guided Dual-Side Graph Transformer;IEEE Transactions on Knowledge and Data Engineering;2024-07

4. Model-Agnostic Adaptive Testing for Intelligent Education Systems via Meta-learned Gradient Embeddings;ACM Transactions on Intelligent Systems and Technology;2024-05-23

5. Unified Uncertainty Estimation for Cognitive Diagnosis Models;Proceedings of the ACM Web Conference 2024;2024-05-13

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