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The significant challenge with traditional learning diagnosis methods is the inability to balance diagnostic accuracy and interpretability. Although the existing psychometric\u2010based learning diagnosis methods provide some domain interpretation through cognitive parameters, they have insufficient modeling capability with a shallow structure for large\u2010scale learning data. While the deep learning\u2010based learning diagnosis methods have improved the accuracy of learning performance prediction, their inherent black\u2010box properties lead to a lack of interpretability, making their results untrustworthy for educational applications. To settle the abovementioned problem, the proposed unified interpretable intelligent learning diagnosis framework, which benefits from the powerful representation learning ability of deep learning and the interpretability of psychometrics, achieves a better performance of learning prediction and provides interpretability from three aspects: cognitive parameters, learner\u2010resource response network, and weights of self\u2010attention mechanism. Within the proposed framework, this paper presents a two\u2010channel learning diagnosis mechanism LDM\u2010ID as well as a three\u2010channel learning diagnosis mechanism LDM\u2010HMI. Experiments on two real\u2010world datasets and a simulation dataset show that our method has higher accuracy in predicting learners\u2019 performances compared with the state\u2010of\u2010the\u2010art models and can provide valuable educational interpretability for applications such as precise learning resource recommendation and personalized learning tutoring in intelligent tutoring systems.<\/jats:p>","DOI":"10.1155\/2023\/4468025","type":"journal-article","created":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T02:50:08Z","timestamp":1676947808000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["A Unified Interpretable Intelligent Learning Diagnosis Framework for Learning Performance Prediction in Intelligent Tutoring Systems"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6960-509X","authenticated-orcid":false,"given":"Zhifeng","family":"Wang","sequence":"first","affiliation":[]},{"given":"Wenxing","family":"Yan","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5799-6692","authenticated-orcid":false,"given":"Chunyan","family":"Zeng","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Tian","sequence":"additional","affiliation":[]},{"given":"Shi","family":"Dong","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2023,2,20]]},"reference":[{"key":"e_1_2_13_1_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40561-018-0052-3"},{"key":"e_1_2_13_2_2","doi-asserted-by":"publisher","DOI":"10.1186\/s40561-016-0026-2"},{"key":"e_1_2_13_3_2","doi-asserted-by":"publisher","DOI":"10.1002\/int.22763"},{"key":"e_1_2_13_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10639-020-10116-4"},{"key":"e_1_2_13_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2006.04.025"},{"key":"e_1_2_13_6_2","doi-asserted-by":"publisher","DOI":"10.1080\/14703290903525846"},{"key":"e_1_2_13_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2017.03.005"},{"key":"e_1_2_13_8_2","doi-asserted-by":"publisher","DOI":"10.1111\/j.1745-3984.2007.00041.x"},{"key":"e_1_2_13_9_2","doi-asserted-by":"publisher","DOI":"10.2307\/2533698"},{"key":"e_1_2_13_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/bf02293610"},{"key":"e_1_2_13_11_2","doi-asserted-by":"publisher","DOI":"10.1177\/0146621608326423"},{"key":"e_1_2_13_12_2","doi-asserted-by":"publisher","DOI":"10.3102\/1076998607309474"},{"key":"e_1_2_13_13_2","doi-asserted-by":"publisher","DOI":"10.1037\/1082-989x.11.3.287"},{"key":"e_1_2_13_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/bf02294535"},{"key":"e_1_2_13_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/bf02295640"},{"key":"e_1_2_13_16_2","unstructured":"PiechC. 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