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Knowledge tracing (KT), wherein students' problem-solving histories are used to estimate their current levels of knowledge, has attracted significant interest from researchers.
Corbett, A.T., Anderson, J.R.: Knowledge tracing: Modeling the acquisition of procedural knowledge. User modeling and user-adapted interaction 4
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Pavlik Jr, P.I., Cen, H., Koedinger, K.R.: Performance factors analysis–a new alternative to knowledge tracing. Online Submission (2009)
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Stamper, J., Niculescu-Mizil, A., Ritter, S., Gordon, G.J., Koedinger, K.R.: Algebra | 2005-2006. development data set from kdd cup 2010 educational data mining challenge (2010), find it at http://pslcdatashop.web.cmu.edu/KDDCup/downloads.jsp
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Piech, C., Bassen, J., Huang, J., Ganguli, S., Sahami, M., Guibas, L.J., Sohl-Dickstein, J.: Deep knowledge tracing. Advances in neural information processing systems 28
2015
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Zhang, J., Shi, X., King, I., Yeung, D.Y.: Dynamic key-value memory networks for knowledge tracing. In: Proceedings of the 26th international conference on World Wide Web. pp. 765–774 (2017)
2017
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Chen, P., Lu, Y., Zheng, V.W., Pian, Y.: Prerequisite-driven deep knowledge tracing. In: 2018 IEEE international conference on data mining (ICDM). pp. 39–48. IEEE (2018)
2018
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Su, Y., Liu, Q., Liu, Q., Huang, Z., Yin, Y., Chen, E., Ding, C., Wei, S., Hu, G.: Exercise-enhanced sequential modeling for student performance prediction. In: Proceedings of the AAAI conference on artificial intelligence. vol. 32 (2018)
2018
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Yeung, C.K., Yeung, D.Y.: Addressing two problems in deep knowledge tracing via prediction-consistent regularization. In: Proceedings of the fifth annual ACM conference on learning at scale. pp. 1–10 (2018)
2018
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Abdelrahman, G., Wang, Q.: Knowledge tracing with sequential key-value memory networks. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval. pp. 175–184 (2019)
2019
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Ai, F., Chen, Y., Guo, Y., Zhao, Y., Wang, Z., Fu, G., Wang, G.: Concept-aware deep knowledge tracing and exercise recommendation in an online learning system. International Educational Data Mining Society (2019)
2019
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Liu, Q., Huang, Z., Yin, Y., Chen, E., Xiong, H., Su, Y., Hu, G.: Ekt: Exercise-aware knowledge tracing for student performance prediction. IEEE Transactions on Knowledge and Data Engineering 33
2019
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2019
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Nakagawa, H., Iwasawa, Y., Matsuo, Y.: Graph-based knowledge tracing: modeling student proficiency using graph neural network. In: IEEE/WIC/ACM International Conference on Web Intelligence. pp. 156–163 (2019)
2019
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2019
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Vie, J.J., Kashima, H.: Knowledge tracing machines: Factorization machines for knowledge tracing. In: Proceedings of the AAAI conference on artificial intelligence. vol. 33, pp. 750–757 (2019)
2019
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Zhao, S., Fu, H., Gong, M., Tao, D.: Geometry-aware symmetric domain adaptation for monocular depth estimation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. pp. 9788–9798 (2019)
2019
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Gervet, T., Koedinger, K., Schneider, J., Mitchell, T., et al.: When is deep learning the best approach to knowledge tracing? Journal of Educational Data Mining 12
2020
Cited alongside, same era.
Ghosh, A., Heffernan, N., Lan, A.S.: Context-aware attentive knowledge tracing. In: Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining. pp. 2330–2339 (2020)
2020
Cited alongside, same era.
2020
Cited alongside, same era.
Pandey, S., Srivastava, J.: Rkt: relation-aware self-attention for knowledge tracing. In: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. pp. 1205–1214 (2020)
2020
Cited alongside, same era.
Abdelrahman, G., Wang, Q., Nunes, B.: Knowledge tracing: A survey. ACM Computing Surveys 55
2023
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Emerson, A., Min, W., Azevedo, R., Lester, J.: Early prediction of student knowledge in game-based learning with distributed representations of assessment questions. British Journal of Educational Technology 54
2023
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2023
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2023
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2020
Cited alongside, same era.
2020
Cited alongside, same era.
Zhao, J., Bhatt, S., Thille, C., Gattani, N., Zimmaro, D.: Cold start knowledge tracing with attentive neural turing machine. In: Proceedings of the Seventh ACM Conference on Learning@ Scale. pp. 333–336 (2020)
2020
Cited alongside, same era.
2021
Cited alongside, same era.
Kim, S., Kim, W., Jung, H., Kim, H.: Dikt: Dichotomous knowledge tracing. In: Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings 17. pp. 41–51. Springer (2021)
2021
Cited alongside, same era.
Shen, S., Liu, Q., Chen, E., Huang, Z., Huang, W., Yin, Y., Su, Y., Wang, S.: Learning process-consistent knowledge tracing. In: Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining. pp. 1452–1460 (2021)
2021
Cited alongside, same era.
Wang, C., Ma, W., Zhang, M., Lv, C., Wan, F., Lin, H., Tang, T., Liu, Y., Ma, S.: Temporal cross-effects in knowledge tracing. In: Proceedings of the 14th ACM International Conference on Web Search and Data Mining. pp. 517–525 (2021)
2021
Cited alongside, same era.
2021
Cited alongside, same era.
Jung, H., Yoo, J., Yoon, Y., Jang, Y.: Language proficiency enhanced knowledge tracing. In: International Conference on Intelligent Tutoring Systems. pp. 3–15. Springer (2023)
2023
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2023
Later among the works it cites.
Ni, Q., Wei, T., Zhao, J., He, L., Zheng, C.: Hhskt: A learner–question interactions based heterogeneous graph neural network model for knowledge tracing. Expert Systems with Applications 215
2023
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Olney, A.M.: Generating multiple choice questions from a textbook: Llms match human performance on most metrics. In: AIED Workshops (2023)
2023
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2023
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2023
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Wang, Q., Mousavi, A.: Which log variables significantly predict academic achievement? a systematic review and meta-analysis. British Journal of Educational Technology 54
2023
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Wu, T., Ling, Q.: Fusing hybrid attentive network with self-supervised dual-channel heterogeneous graph for knowledge tracing. Expert Systems with Applications 225
2023
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Xu, J., Huang, X., Xiao, T., Lv, P.: Improving knowledge tracing via a heterogeneous information network enhanced by student interactions. Expert Systems with Applications 232
2023
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Yin, Y., Dai, L., Huang, Z., Shen, S., Wang, F., Liu, Q., Chen, E., Li, X.: Tracing knowledge instead of patterns: Stable knowledge tracing with diagnostic transformer. In: Proceedings of the ACM Web Conference 2023. pp. 855–864 (2023)
2023
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2023
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2023
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Colpo, M.P., Primo, T.T., de Aguiar, M.S.: Lessons learned from the student dropout patterns on covid-19 pandemic: An analysis supported by machine learning. British Journal of Educational Technology 55
2024
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2024
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Shen, S., Liu, Q., Huang, Z., Zheng, Y., Yin, M., Wang, M., Chen, E.: A survey of knowledge tracing: Models, variants, and applications. IEEE Transactions on Learning Technologies (2024)
2024
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Sun, J., Wei, M., Feng, J., Yu, F., Li, Q., Zou, R.: Progressive knowledge tracing: Modeling learning process from abstract to concrete. Expert Systems with Applications 238
2024
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Yang, H., Hu, S., Geng, J., Huang, T., Hu, J., Zhang, H., Zhu, Q.: Heterogeneous graph-based knowledge tracing with spatiotemporal evolution. Expert Systems with Applications 238
2024
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