Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
  • Wu L, Chen X, Liu F, Xie J, Xia C, Tan Z, Tian M, Li J, Zhang K, Lian D, Hong R and Wang M. (2025). EduStudio: towards a unified library for student cognitive modeling. Frontiers of Computer Science: Selected Publications from Chinese Universities. 19:8. Online publication date: 1-Aug-2025.

    https://doi.org/10.1007/s11704-024-40372-3

  • Sun X, Liu Q, Zhang K, Shen S, Zhuang Y and Guo Y. (2025). LGS-KT: Integrating logical and grammatical skills for effective programming knowledge tracing. Neural Networks. 10.1016/j.neunet.2025.107164. 185. (107164). Online publication date: 1-May-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0893608025000437

  • Bai Y, Li X, Liu Z, Huang Y, Guo T, Hou M, Xia F and Luo W. (2025). csKT: Addressing cold-start problem in knowledge tracing via kernel bias and cone attention. Expert Systems with Applications. 10.1016/j.eswa.2024.125988. 266. (125988). Online publication date: 1-Mar-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417424028550

  • Qian F, Hu Y, Li G, Chen J, Wang S and Zhao S. Enhanced Knowledge Tracing With Learnable Filter. IEEE Transactions on Computational Social Systems. 10.1109/TCSS.2024.3452130. 12:1. (198-209).

    https://ieeexplore.ieee.org/document/10701610/

  • Li Q, Yuan X, Yue J, Shen X, Liang R, Liu S and Yan Z. (2025). Dual-view multi-scale cognitive representation for deep knowledge tracing. Knowledge-Based Systems. 10.1016/j.knosys.2025.113010. 310. (113010). Online publication date: 1-Feb-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705125000589

  • Yang H, Hu J, Chen J, Hu S, Geng J, Zhu Q and Huang T. (2025). MAHKT: Knowledge tracing with multi-association heterogeneous graph embedding based on knowledge transfer. Knowledge-Based Systems. 10.1016/j.knosys.2025.112958. 310. (112958). Online publication date: 1-Feb-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705125000061

  • Sun J, Du S, Zhou J, Yuan X, Shen X and Liang R. (2024). Question Embedding on Weighted Heterogeneous Information Network for Knowledge Tracing. ACM Transactions on Knowledge Discovery from Data. 19:1. (1-28). Online publication date: 31-Jan-2025.

    https://doi.org/10.1145/3703158

  • Zhou H, Rong W, Zhang J, Sun Q, Ouyang Y and Xiong Z. (2025). AAKT: Enhancing Knowledge Tracing With Alternate Autoregressive Modeling. IEEE Transactions on Learning Technologies. 18. (25-38). Online publication date: 1-Jan-2025.

    https://doi.org/10.1109/TLT.2024.3521898

  • Wang J, Ma H, Zhang M, Zhang L and Chang L. (2025). Multi-Granularity Ensemble Interaction Graph Modeling for Knowledge Tracing. Knowledge-Based Systems. 10.1016/j.knosys.2024.112834. 309. (112834). Online publication date: 1-Jan-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705124014680

  • Huang C, Jiang W, Li K, Wu J and Zhang J. (2025). Enhancing learning process modeling for session-aware knowledge tracing. Knowledge-Based Systems. 10.1016/j.knosys.2024.112740. 309. (112740). Online publication date: 1-Jan-2025.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705124013741

  • Huang D, Yu J, Mao S, Li J and Jiang Y. (2025). Dual-Mode Contrastive Learning-Enhanced Knowledge Tracing. PRICAI 2024: Trends in Artificial Intelligence. 10.1007/978-981-96-0116-5_7. (81-92).

    https://link.springer.com/10.1007/978-981-96-0116-5_7

  • Zheng Q, Mao S, Chen K and Jiang Y. (2024). EGANKT: Enhancing Graph-Attention Networks for Knowledge Tracing by Predicting Concepts and Abilities 2024 IEEE International Conference on Big Data (BigData). 10.1109/BigData62323.2024.10825562. 979-8-3503-6248-0. (1902-1908).

    https://ieeexplore.ieee.org/document/10825562/

  • Zhang J, Xia R, Miao Q and Wang Q. (2024). Explore Bayesian analysis in Cognitive-aware Key–Value Memory Networks for knowledge tracing in online learning. Expert Systems with Applications. 10.1016/j.eswa.2024.124933. 257. (124933). Online publication date: 1-Dec-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417424018001

  • Zhang K, Ji T and Zhang H. (2024). Knowledge tracing via multiple-state diffusion representation. Expert Systems with Applications. 10.1016/j.eswa.2024.124797. 255. (124797). Online publication date: 1-Dec-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417424016646

  • Jain A and Mago N. (2024). A Narrative Review of Developments in Knowledge Tracing in Last Decade 2024 3rd Edition of IEEE Delhi Section Flagship Conference (DELCON). 10.1109/DELCON64804.2024.10866076. 979-8-3315-1859-2. (1-7).

    https://ieeexplore.ieee.org/document/10866076/

  • Han Y, Tang H, Zhang W, Du L, Zhao J and Shao M. (2024). Dynamic heterogeneous graph contrastive networks for knowledge tracing. Applied Soft Computing. 10.1016/j.asoc.2024.112194. 166. (112194). Online publication date: 1-Nov-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S1568494624009682

  • Zhang H, Wang L, Qu Y, Li W and Jiang Q. (2024). Enhanced Dynamic Key-Value Memory Networks for Personalized Student Modeling and Learning Ability Classification. Cognitive Computation. 10.1007/s12559-024-10341-w. 16:6. (2878-2901). Online publication date: 1-Nov-2024.

    https://link.springer.com/10.1007/s12559-024-10341-w

  • Shen X, Yu F, Liu Y, Liang R, Wan Q, Yang K and Sun J. Revisiting Knowledge Tracing: A Simple and Powerful Model. Proceedings of the 32nd ACM International Conference on Multimedia. (263-272).

    https://doi.org/10.1145/3664647.3681205

  • Huang T, Ou X, Yang H, Hu S, Geng J, Hu J and Xu Z. Remembering is Not Applying: Interpretable Knowledge Tracing for Problem-solving Processes. Proceedings of the 32nd ACM International Conference on Multimedia. (3151-3159).

    https://doi.org/10.1145/3664647.3681049

  • Luo H, Zhang Z, Cui L, Zhang Z and Liang Y. (2024). An efficient state-aware Coarse-Fine-Grained model for Knowledge Tracing. Knowledge-Based Systems. 302:C. Online publication date: 25-Oct-2024.

    https://doi.org/10.1016/j.knosys.2024.112375

  • Fu L, Guan H, Du K, Lin J, Xia W, Zhang W, Tang R, Wang Y and Yu Y. SINKT: A Structure-Aware Inductive Knowledge Tracing Model with Large Language Model. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management. (632-642).

    https://doi.org/10.1145/3627673.3679760

  • Sun X, Zhang K, Shen S, Wang F, Guo Y and Liu Q. (2024). Target hierarchy-guided knowledge tracing : Fine-grained knowledge state modeling. Expert Systems with Applications. 10.1016/j.eswa.2024.123898. 251. (123898). Online publication date: 1-Oct-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417424007644

  • Zhang S, Pu J, Cui J, Shen S, Chen W, Hu K and Chen E. (2024). MLC-DKT: A multi-layer context-aware deep knowledge tracing model. Knowledge-Based Systems. 10.1016/j.knosys.2024.112384. (112384). Online publication date: 1-Aug-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705124010189

  • Mao A, Chen J and Liu Y. Improving Knowledge Tracing via Considering Conceptual Structure and Individual Differences. Proceedings of the ACM Turing Award Celebration Conference - China 2024. (59-65).

    https://doi.org/10.1145/3674399.3674427

  • Huang C, Wei H, Huang Q, Jiang F, Han Z and Huang X. (2024). Learning consistent representations with temporal and causal enhancement for knowledge tracing. Expert Systems with Applications. 10.1016/j.eswa.2023.123128. 245. (123128). Online publication date: 1-Jul-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417423036321

  • Lu G, Niu K, Peng X, Zhou Y, Zhang K and Tai W. (2024). Self-KT: Self-attentive Knowledge Tracing with Feature Fusion Pre-training in Online Education 2024 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN60899.2024.10651418. 979-8-3503-5931-2. (1-8).

    https://ieeexplore.ieee.org/document/10651418/

  • Lv T and Xu L. (2024). Deep Attention Knowledge Tracking Incorporating Multiple Features and TCN-Transformer 2024 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN60899.2024.10650848. 979-8-3503-5931-2. (1-8).

    https://ieeexplore.ieee.org/document/10650848/

  • Long Y, Yu W, Huang J, Zhang T and Lai N. (2024). MGKT: A Multi-Relation Enhanced Graph-Based Model for Knowledge Tracing 2024 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN60899.2024.10649935. 979-8-3503-5931-2. (1-8).

    https://ieeexplore.ieee.org/document/10649935/

  • Li J, Deng Y, Mao S, Qin Y and Jiang Y. Knowledge-Associated Embedding for Memory-Aware Knowledge Tracing. IEEE Transactions on Computational Social Systems. 10.1109/TCSS.2023.3306909. 11:3. (4016-4028).

    https://ieeexplore.ieee.org/document/10239269/

  • Linhao Z, Shenghua Z and Zhijiao X. Discovering Multi-Relational Integration for Knowledge Tracing with Retentive Networks. Proceedings of the 2024 International Conference on Multimedia Retrieval. (960-968).

    https://doi.org/10.1145/3652583.3658030

  • Liu G, Zhan H and Kim J. Question Difficulty Consistent Knowledge Tracing. Proceedings of the ACM Web Conference 2024. (4239-4248).

    https://doi.org/10.1145/3589334.3645582

  • Sun J, Yu F, Wan Q, Li Q, Liu S and Shen X. Interpretable Knowledge Tracing with Multiscale State Representation. Proceedings of the ACM Web Conference 2024. (3265-3276).

    https://doi.org/10.1145/3589334.3645373

  • Sun Y, Wang J, Cheng P, Zheng L, Chen L and Yin J. (2024). Cross-Domain-Aware Worker Selection with Training for Crowdsourced Annotation 2024 IEEE 40th International Conference on Data Engineering (ICDE). 10.1109/ICDE60146.2024.00026. 979-8-3503-1715-2. (249-262).

    https://ieeexplore.ieee.org/document/10598166/

  • Msayer M, Aoula E and Bouihi B. (2024). Artificial intelligence in computerized adaptive testing to assess the cognitive performance of students: A Systematic Review 2024 International Conference on Intelligent Systems and Computer Vision (ISCV). 10.1109/ISCV60512.2024.10620092. 979-8-3503-5018-0. (1-8).

    https://ieeexplore.ieee.org/document/10620092/

  • Zhao L, Li S, He X and Liu H. Research on Expression Image Recognition and Classification Based on Multi stimulus Perception Deep Learning in Intelligent Learning Environment. Proceedings of the 5th International Conference on Computer Information and Big Data Applications. (665-670).

    https://doi.org/10.1145/3671151.3671269

  • Xu J and Hu W. (2024). An Enhanced Deep Knowledge Tracing Model via Multiband Attention and Quantized Question Embedding. Applied Sciences. 10.3390/app14083425. 14:8. (3425).

    https://www.mdpi.com/2076-3417/14/8/3425

  • Xu A, Monroe W and Bicknell K. Large language model augmented exercise retrieval for personalized language learning. Proceedings of the 14th Learning Analytics and Knowledge Conference. (284-294).

    https://doi.org/10.1145/3636555.3636883

  • Qin C, Hu W, Du F and Wang S. (2024). Graph Attention-Enhanced Knowledge Tracing: Unveiling Exercise Variability and Long-Term Dependencies 2024 12th International Conference on Information and Education Technology (ICIET). 10.1109/ICIET60671.2024.10542821. 979-8-3503-7177-2. (482-488).

    https://ieeexplore.ieee.org/document/10542821/

  • Yang H, Hu S, Geng J, Huang T, Hu J, Zhang H and Zhu Q. (2024). Heterogeneous graph-based knowledge tracing with spatiotemporal evolution. Expert Systems with Applications: An International Journal. 238:PF. Online publication date: 15-Mar-2024.

    https://doi.org/10.1016/j.eswa.2023.122249

  • Xiong Z, Li H, Liu Z, Chen Z, Zhou H, Rong W and Ouyang Y. (2024). A Review of Data Mining in Personalized Education: Current Trends and Future Prospects. Frontiers of Digital Education. 10.1007/s44366-024-0019-6. 1:1. (26-50). Online publication date: 1-Mar-2024.

    https://link.springer.com/10.1007/s44366-024-0019-6

  • Lu Y, Wang D, Chen P and Zhang Z. (2024). Design and Evaluation of Trustworthy Knowledge Tracing Model for Intelligent Tutoring System. IEEE Transactions on Learning Technologies. 17. (1701-1716). Online publication date: 1-Jan-2024.

    https://doi.org/10.1109/TLT.2024.3403135

  • Shen S, Liu Q, Huang Z, Zheng Y, Yin M, Wang M and Chen E. (2024). A Survey of Knowledge Tracing: Models, Variants, and Applications. IEEE Transactions on Learning Technologies. 17. (1898-1919). Online publication date: 1-Jan-2024.

    https://doi.org/10.1109/TLT.2024.3383325

  • Zhang W, Gong Z, Luo P and Li Z. DKVMN-KAPS: Dynamic Key-Value Memory Networks Knowledge Tracing With Students’ Knowledge-Absorption Ability and Problem-Solving Ability. IEEE Access. 10.1109/ACCESS.2024.3388718. 12. (55146-55156).

    https://ieeexplore.ieee.org/document/10499257/

  • Ke F, Wang W, Tan W, Du L, Jin Y, Huang Y and Yin H. (2024). HiTSKT: A hierarchical transformer model for session-aware knowledge tracing. Knowledge-Based Systems. 10.1016/j.knosys.2023.111300. 284. (111300). Online publication date: 1-Jan-2024.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705123010481

  • Zhao H and Sun J. (2024). Data Augmentation for Knowledge Tracing Based on Variational AutoEncoder and Efficient Network Reusing. Web and Big Data. 10.1007/978-981-97-7244-5_18. (271-285).

    https://link.springer.com/10.1007/978-981-97-7244-5_18

  • Xu L, Guo L, Wu X, Wang X and Guo L. (2024). Knowledge Tracing with Contrastive Learning and Attention-Based Long Short-Term Memory Network. Advanced Intelligent Computing Technology and Applications. 10.1007/978-981-97-5591-2_3. (25-36).

    https://link.springer.com/10.1007/978-981-97-5591-2_3

  • Bouarour N, Benouaret I and Amer-Yahia S. (2024). Multi-objective Test Recommendation for Adaptive Learning. Transactions on Large-Scale Data- and Knowledge-Centered Systems LVI. 10.1007/978-3-662-69603-3_1. (1-36).

    https://link.springer.com/10.1007/978-3-662-69603-3_1

  • Cui S, Wang M and Xu S. (2024). A Temporal-Enhanced Model for Knowledge Tracing. Artificial Neural Networks and Machine Learning – ICANN 2024. 10.1007/978-3-031-72356-8_27. (407-421).

    https://link.springer.com/10.1007/978-3-031-72356-8_27

  • Sinha P, Khushi and Dagur A. (2024). Improved Framework Model to Train and Evaluate Difficulty of Interview Question Using Generative AI. Artificial Intelligence and Its Practical Applications in the Digital Economy. 10.1007/978-3-031-71429-0_14. (175-188).

    https://link.springer.com/10.1007/978-3-031-71429-0_14

  • Pinto J and Paquette L. (2024). Deep Learning for Educational Data Science. Trust and Inclusion in AI-Mediated Education. 10.1007/978-3-031-64487-0_6. (111-139).

    https://link.springer.com/10.1007/978-3-031-64487-0_6

  • Zhang J, Xia R and Wang Q. (2023). Design of Data-Driven Learning Path Based on Knowledge Graph and Tracing Model 2023 IEEE International Conference on High Performance Computing & Communications, Data Science & Systems, Smart City & Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys). 10.1109/HPCC-DSS-SmartCity-DependSys60770.2023.00118. 979-8-3503-3001-4. (813-820).

    https://ieeexplore.ieee.org/document/10467016/

  • Sun W, Gao B, Chen J, Huang S and Luo W. (2023). An Interactive Framework of Balancing Evaluation Cost and Prediction Accuracy for Knowledge Tracing 2023 IEEE International Conference on Big Data (BigData). 10.1109/BigData59044.2023.10386686. 979-8-3503-2445-7. (1-8).

    https://ieeexplore.ieee.org/document/10386686/

  • Liu Z, Liu Q, Guo T, Chen J, Huang S, Zhao X, Tang J, Luo W and Weng J. XES3G5M. Proceedings of the 37th International Conference on Neural Information Processing Systems. (32958-32970).

    /doi/10.5555/3666122.3667551

  • Yang S, Yu X, Tian Y, Yan X, Ma H and Zhang X. Evolutionary neural architecture search for transformer in knowledge tracing. Proceedings of the 37th International Conference on Neural Information Processing Systems. (19520-19539).

    /doi/10.5555/3666122.3666979

  • Shi J, Su W, Liu L, Xu S, Huang T, Liu J, Yue W and Li S. (2023). A Deep Memory-Aware Attentive Model for Knowledge Tracing 2023 IEEE International Conference on Data Mining Workshops (ICDMW). 10.1109/ICDMW60847.2023.00201. 979-8-3503-8164-1. (1581-1590).

    https://ieeexplore.ieee.org/document/10411550/

  • Zhao Y, Ma M, Wang J, He X and Chang L. (2023). Question-response representation with dual-level contrastive learning for improving knowledge tracing. Information Sciences. 10.1016/j.ins.2023.120032. (120032). Online publication date: 1-Dec-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0020025523016183

  • Ilić M, Mikić V, Kopanja L and Vesin B. (2023). Intelligent techniques in e-learning: a literature review. Artificial Intelligence Review. 10.1007/s10462-023-10508-1. 56:12. (14907-14953). Online publication date: 1-Dec-2023.

    https://link.springer.com/10.1007/s10462-023-10508-1

  • Abdelrahman G, Wang Q and Nunes B. (2023). Knowledge Tracing: A Survey. ACM Computing Surveys. 55:11. (1-37). Online publication date: 30-Nov-2023.

    https://doi.org/10.1145/3569576

  • Li W, Zhang H and Huang W. (2023). Context Matters: Advancing Knowledge Tracing in Online Learning with Enhanced Attention Mechanisms 2023 13th International Conference on Information Technology in Medicine and Education (ITME). 10.1109/ITME60234.2023.00134. 979-8-3503-1915-6. (644-648).

    https://ieeexplore.ieee.org/document/10505603/

  • Wang X, Zhao S, Guo L, Zhu L, Cui C and Xu L. GraphCA: Learning from Graph Counterfactual Augmentation for Knowledge Tracing. IEEE/CAA Journal of Automatica Sinica. 10.1109/JAS.2023.123678. 10:11. (2108-2123).

    https://ieeexplore.ieee.org/document/10266657/

  • Sun J, Yu F, Liu S, Luo Y, Liang R and Shen X. Adversarial Bootstrapped Question Representation Learning for Knowledge Tracing. Proceedings of the 31st ACM International Conference on Multimedia. (8016-8025).

    https://doi.org/10.1145/3581783.3612044

  • Zhang M, Zhu X, Zhang C, Pan F, Qian W and Zhao H. No Length Left Behind: Enhancing Knowledge Tracing for Modeling Sequences of Excessive or Insufficient Lengths. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. (3226-3235).

    https://doi.org/10.1145/3583780.3614988

  • Guan Q, Xiao F, Cheng X, Fang L, Chen Z, Chen G and Luo W. KG4Ex: An Explainable Knowledge Graph-Based Approach for Exercise Recommendation. Proceedings of the 32nd ACM International Conference on Information and Knowledge Management. (597-607).

    https://doi.org/10.1145/3583780.3614943

  • Lu Y, Wang D, Chen P, Meng Q and Yu S. (2022). Interpreting Deep Learning Models for Knowledge Tracing. International Journal of Artificial Intelligence in Education. 10.1007/s40593-022-00297-z. 33:3. (519-542). Online publication date: 1-Sep-2023.

    https://link.springer.com/10.1007/s40593-022-00297-z

  • Zhao Y, Ma H, Wang W, Gao W, Yang F and He X. (2023). Exploiting multiple question factors for knowledge tracing. Expert Systems with Applications: An International Journal. 223:C. Online publication date: 1-Aug-2023.

    https://doi.org/10.1016/j.eswa.2023.119786

  • Huang S, Liu Z, Zhao X, Luo W and Weng J. Towards Robust Knowledge Tracing Models via k-Sparse Attention. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. (2441-2445).

    https://doi.org/10.1145/3539618.3592073

  • Yu J, Lu M, Zhong Q, Yao Z, Tu S, Liao Z, Li X, Li M, Hou L, Zheng H, Li J and Tang J. MoocRadar: A Fine-grained and Multi-aspect Knowledge Repository for Improving Cognitive Student Modeling in MOOCs. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval. (2924-2934).

    https://doi.org/10.1145/3539618.3591898

  • Guo J, Ding Y, Li Y, Zheng L, Ma X and Xiao L. (2023). Deep Knowledge Tracking Based on Double Attention Mechanism and Cognitive Difficulty 2023 IEEE Symposium on Computers and Communications (ISCC). 10.1109/ISCC58397.2023.10217838. 979-8-3503-0048-2. (1423-1428).

    https://ieeexplore.ieee.org/document/10217838/

  • Labra C and Santos O. Exploring cognitive models to augment explainability in Deep Knowledge Tracing. Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. (220-223).

    https://doi.org/10.1145/3563359.3597384

  • Zhao Y, Ma H, Wang W, Gao W, Wang J and He X. (2023). Improving Knowledge Tracing with Diverse Question Factors 2023 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN54540.2023.10191002. 978-1-6654-8867-9. (1-7).

    https://ieeexplore.ieee.org/document/10191002/

  • Mao S, Zhan J, Wang Y and Jiang Y. (2023). Improving Knowledge Tracing via Considering Two Types of Actual Differences From Exercises and Prior Knowledge. IEEE Transactions on Learning Technologies. 16:3_Part_1. (324-338). Online publication date: 1-Jun-2023.

    https://doi.org/10.1109/TLT.2023.3259013

  • Abdelrahman G and Wang Q. (2023). Learning data teaching strategies via knowledge tracing. Knowledge-Based Systems. 10.1016/j.knosys.2023.110511. 269. (110511). Online publication date: 1-Jun-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705123002617

  • Mallik S and Gangopadhyay A. (2023). Proactive and reactive engagement of artificial intelligence methods for education: a review. Frontiers in Artificial Intelligence. 10.3389/frai.2023.1151391. 6.

    https://www.frontiersin.org/articles/10.3389/frai.2023.1151391/full

  • Liu Z, Liu Q, Chen J, Huang S, Gao B, Luo W and Weng J. Enhancing Deep Knowledge Tracing with Auxiliary Tasks. Proceedings of the ACM Web Conference 2023. (4178-4187).

    https://doi.org/10.1145/3543507.3583866

  • Su H, Liu X, Yang S and Lu X. (2023). Deep knowledge tracing with learning curves. Frontiers in Psychology. 10.3389/fpsyg.2023.1150329. 14.

    https://www.frontiersin.org/articles/10.3389/fpsyg.2023.1150329/full

  • Ma B, Hettiarachchi G, Fukui S and Ando Y. Each Encounter Counts: Modeling Language Learning and Forgetting. LAK23: 13th International Learning Analytics and Knowledge Conference. (79-88).

    https://doi.org/10.1145/3576050.3576062

  • Chen M, Bian K, He Y, Li Z and Zheng H. (2023). Enhanced Learning and Forgetting Behavior for Contextual Knowledge Tracing. Information. 10.3390/info14030168. 14:3. (168).

    https://www.mdpi.com/2078-2489/14/3/168

  • Su W, Jiang F, Shi C, Wu D, Liu L, Li S, Yuan Y and Shi J. (2023). An XGBoost-Based Knowledge Tracing Model. International Journal of Computational Intelligence Systems. 10.1007/s44196-023-00192-y. 16:1.

    https://link.springer.com/10.1007/s44196-023-00192-y

  • Xiao Y, Xiao R, Huang N, Hu Y, Li H and Sun B. (2022). Knowledge tracing based on multi-feature fusion. Neural Computing and Applications. 10.1007/s00521-022-07834-w. 35:2. (1819-1833). Online publication date: 1-Jan-2023.

    https://link.springer.com/10.1007/s00521-022-07834-w

  • Ma R, Zhang H, Mei B, Lv G and Zhao L. (2023). SATCN: An Improved Temporal Convolutional Neural Network with Self Attention Mechanism for Knowledge Tracing. Computer Science and Education. 10.1007/978-981-99-2443-1_1. (3-17).

    https://link.springer.com/10.1007/978-981-99-2443-1_1

  • Habijan M and Galić I. (2023). Evaluating LightGBM Classifier for Knowledge Tracing on EdNet Dataset. Digital Transformation in Education and Artificial Intelligence Application. 10.1007/978-3-031-36833-2_3. (33-44).

    https://link.springer.com/10.1007/978-3-031-36833-2_3

  • Jung H, Yoo J, Yoon Y and Jang Y. (2023). Language Proficiency Enhanced Knowledge Tracing. Augmented Intelligence and Intelligent Tutoring Systems. 10.1007/978-3-031-32883-1_1. (3-15).

    https://link.springer.com/10.1007/978-3-031-32883-1_1

  • Zhang Y, Yu M, Sun J, Zhang T and Yu G. (2023). MG-CR: Factor Memory Network and Graph Neural Network Based Personalized Course Recommendation. Database Systems for Advanced Applications. 10.1007/978-3-031-30672-3_37. (547-562).

    https://link.springer.com/10.1007/978-3-031-30672-3_37

  • Chen J, Shen J, Long T, Shen L, Zhang W and Yu Y. (2023). Heterogeneous Graph Representation for Knowledge Tracing. Neural Information Processing. 10.1007/978-3-031-30105-6_19. (224-235).

    https://link.springer.com/10.1007/978-3-031-30105-6_19

  • Naranjo J, Stoffova V and Zhu C. (2022). Knowledge tracing: A brief overview of the advances done since 2021 using deep learning techniques. Journal of Technology and Information. 10.5507/jtie.2022.013. 14:2. (160-173). Online publication date: 31-Dec-2022.

    http://jtie.upol.cz/doi/10.5507/jtie.2022.013.html

  • Shi H, Yang Y, Chen Z and Fu P. Dynamic Multi-skill Knowledge Tracing for Intelligent Educational System. Proceedings of the 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence. (1-6).

    https://doi.org/10.1145/3579654.3579740

  • Song X, Li J, Cai T, Yang S, Yang T and Liu C. (2022). A survey on deep learning based knowledge tracing. Knowledge-Based Systems. 10.1016/j.knosys.2022.110036. 258. (110036). Online publication date: 1-Dec-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705122011297

  • Xiahou J, Fan F, Lin F and Feng S. (2022). Multi-Scaled Attentive Knowledge Tracing 2022 4th International Workshop on Artificial Intelligence and Education (WAIE). 10.1109/WAIE57417.2022.00027. 978-1-6654-6351-5. (99-104).

    https://ieeexplore.ieee.org/document/10035191/

  • Yang S, Liu X, Su H, Zhu M and Lu X. (2022). Deep Knowledge Tracing with Learning Curves 2022 IEEE International Conference on Data Mining Workshops (ICDMW). 10.1109/ICDMW58026.2022.00046. 979-8-3503-4609-1. (282-291).

    https://ieeexplore.ieee.org/document/10031094/

  • Sun J, Zou R, Liang R, Gao L, Liu S, Li Q, Zhang K and Jiang L. (2022). Ensemble Knowledge Tracing: Modeling interactions in learning process. Expert Systems with Applications. 10.1016/j.eswa.2022.117680. 207. (117680). Online publication date: 1-Nov-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417422009769

  • Chen M, Guan Q, He Y, He Z, Fang L and Luo W. Knowledge Tracing Model with Learning and Forgetting Behavior. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. (3863-3867).

    https://doi.org/10.1145/3511808.3557622

  • Zheng X, Ban Q, Wu W, Chen J, Xiao J, Wang L, Zheng W and He L. (2022). Learner Profile based Knowledge Tracing 2022 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN55064.2022.9892574. 978-1-7281-8671-9. (01-08).

    https://ieeexplore.ieee.org/document/9892574/

  • Xu L, Wang G, Guo L and Wang X. (2022). Long- and Short-term Attention Network for Knowledge Tracing 2022 International Joint Conference on Neural Networks (IJCNN). 10.1109/IJCNN55064.2022.9891896. 978-1-7281-8671-9. (1-9).

    https://ieeexplore.ieee.org/document/9891896/

  • Lyu L, Wang Z, Yun H, Yang Z and Li Y. (2022). Deep Knowledge Tracing Based on Spatial and Temporal Representation Learning for Learning Performance Prediction. Applied Sciences. 10.3390/app12147188. 12:14. (7188).

    https://www.mdpi.com/2076-3417/12/14/7188

  • Li R, Yin Y, Dai L, Shen S, Lin X, Su Y and Chen E. PST. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. (2601-2606).

    https://doi.org/10.1145/3477495.3531903

  • Gu H, Dong X and Zhou D. (2022). Dynamic Key-Value Memory Networks based on Concept Structure for Knowledge Tracing 2022 4th International Conference on Computer Science and Technologies in Education (CSTE). 10.1109/CSTE55932.2022.00060. 978-1-6654-8188-5. (290-294).

    https://ieeexplore.ieee.org/document/9973108/

  • He Z, Li W and Yan Y. (2021). Modeling knowledge proficiency using multi-hierarchical capsule graph neural network. Applied Intelligence. 10.1007/s10489-021-02765-w. 52:7. (7230-7247). Online publication date: 1-May-2022.

    https://link.springer.com/10.1007/s10489-021-02765-w

  • Song X, Li J, Lei Q, Zhao W, Chen Y and Mian A. (2022). Bi-CLKT: Bi-Graph Contrastive Learning based Knowledge Tracing. Knowledge-Based Systems. 10.1016/j.knosys.2022.108274. 241. (108274). Online publication date: 1-Apr-2022.

    https://linkinghub.elsevier.com/retrieve/pii/S0950705122000880

  • Cheng S, Liu Q, Chen E, Zhang K, Huang Z, Yin Y, Huang X and Su Y. AdaptKT: A Domain Adaptable Method for Knowledge Tracing. Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining. (123-131).

    https://doi.org/10.1145/3488560.3498379

  • Long T, Qin J, Shen J, Zhang W, Xia W, Tang R, He X and Yu Y. Improving Knowledge Tracing with Collaborative Information. Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining. (599-607).

    https://doi.org/10.1145/3488560.3498374

  • Abdelrahman G and Wang Q. Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2022.3206447. (1-13).

    https://ieeexplore.ieee.org/document/9891841/

  • Murtaza M, Ahmed Y, Shamsi J, Sherwani F and Usman M. AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions. IEEE Access. 10.1109/ACCESS.2022.3193938. 10. (81323-81342).

    https://ieeexplore.ieee.org/document/9840390/

  • Chen M, Ma W, Mao S and Jiang Y. (2022). GMEKT: A Novel Graph Attention-Based Memory-Enhanced Knowledge Tracing. PRICAI 2022: Trends in Artificial Intelligence. 10.1007/978-3-031-20862-1_30. (408-421).

    https://link.springer.com/10.1007/978-3-031-20862-1_30

  • Umutlu D and Gursoy M. (2022). Leveraging Artificial Intelligence Techniques for Effective Scaffolding of Personalized Learning in Workplaces. Artificial Intelligence Education in the Context of Work. 10.1007/978-3-031-14489-9_4. (59-76).

    https://link.springer.com/10.1007/978-3-031-14489-9_4

  • Long T, Liu Y, Shen J, Zhang W and Yu Y. Tracing Knowledge State with Individual Cognition and Acquisition Estimation. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. (173-182).

    https://doi.org/10.1145/3404835.3462827

  • Gao S, Chen X, Ren Z, Zhao D and Yan R. (2021). Meaningful Answer Generation of E-Commerce Question-Answering. ACM Transactions on Information Systems. 39:2. (1-26). Online publication date: 30-Apr-2021.

    https://doi.org/10.1145/3432689

  • Wu J, Huang Z, Liu Q, Lian D, Wang H, Chen E, Ma H and Wang S. Federated Deep Knowledge Tracing. Proceedings of the 14th ACM International Conference on Web Search and Data Mining. (662-670).

    https://doi.org/10.1145/3437963.3441747

  • Huang T, Yang H, Li Z, Xie H, Geng J and Zhang H. A Dynamic Knowledge Diagnosis Approach Integrating Cognitive Features. IEEE Access. 10.1109/ACCESS.2021.3105830. 9. (116814-116829).

    https://ieeexplore.ieee.org/document/9515946/

  • Liu C and Li X. (2021). Memory Attentive Cognitive Diagnosis for Student Performance Prediction. Web and Big Data. APWeb-WAIM 2021 International Workshops. 10.1007/978-981-16-8143-1_8. (79-90).

    https://link.springer.com/10.1007/978-981-16-8143-1_8

  • Zhang X, Zhang J, Lin N and Yang X. (2021). Sequential Self-Attentive Model for Knowledge Tracing. Artificial Neural Networks and Machine Learning – ICANN 2021. 10.1007/978-3-030-86362-3_26. (318-330).

    https://link.springer.com/10.1007/978-3-030-86362-3_26

  • Xie Q, Wang L, Song P and Lin X. (2021). SQKT: A Student Attention-Based and Question-Aware Model for Knowledge Tracing. Web and Big Data. 10.1007/978-3-030-85899-5_17. (221-236).

    https://link.springer.com/10.1007/978-3-030-85899-5_17

  • Zhang X and Li L. (2021). Attentional Neural Factorization Machines for Knowledge Tracing. Knowledge Science, Engineering and Management. 10.1007/978-3-030-82136-4_26. (319-330).

    https://link.springer.com/10.1007/978-3-030-82136-4_26

  • Ouyang Y, Zhou Y, Zhang H, Rong W and Xiong Z. (2021). PAKT: A Position-Aware Self-attentive Approach for Knowledge Tracing. Artificial Intelligence in Education. 10.1007/978-3-030-78270-2_51. (285-289).

    https://link.springer.com/10.1007/978-3-030-78270-2_51

  • Yang Y, Shen J, Qu Y, Liu Y, Wang K, Zhu Y, Zhang W and Yu Y. (2021). GIKT: A Graph-Based Interaction Model for Knowledge Tracing. Machine Learning and Knowledge Discovery in Databases. 10.1007/978-3-030-67658-2_18. (299-315).

    http://link.springer.com/10.1007/978-3-030-67658-2_18

  • Gan W, Sun Y and Sun Y. (2020). Knowledge Interaction Enhanced Knowledge Tracing for Learner Performance Prediction 2020 7th International Conference on Behavioural and Social Computing (BESC). 10.1109/BESC51023.2020.9348285. 978-1-7281-8605-4. (1-6).

    https://ieeexplore.ieee.org/document/9348285/

  • Gan W, Sun Y, Peng X and Sun Y. (2020). Modeling learner’s dynamic knowledge construction procedure and cognitive item difficulty for knowledge tracing. Applied Intelligence. 10.1007/s10489-020-01756-7.

    http://link.springer.com/10.1007/s10489-020-01756-7

  • Liouane Z, Lemlouma T, Roose P, Weis F and Messaoud H. (2020). An intelligent knowledge system for designing, modeling, and recognizing the behavior of elderly people in smart space. Journal of Ambient Intelligence and Humanized Computing. 10.1007/s12652-020-01876-5.

    http://link.springer.com/10.1007/s12652-020-01876-5

  • Benedetto L, Cappelli A, Turrin R and Cremonesi P. (2020). Introducing a Framework to Assess Newly Created Questions with Natural Language Processing. Artificial Intelligence in Education. 10.1007/978-3-030-52237-7_4. (43-54).

    http://link.springer.com/10.1007/978-3-030-52237-7_4