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Correction: Noise-Filtering Enhanced Deep Cognitive Diagnosis Model for Latent Skill Discovering

Jing Geng1,*, Huali Yang2, Shengze Hu3

1 National Engineering Research Center of Educational Big Data, Central China Normal University, Wuhan, 430079, China
2 Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, 430079, China
3 School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan, 430079, China

* Corresponding Author: Jing Geng. Email: email

Intelligent Automation & Soft Computing 2024, 39(5), 985-986. https://doi.org/10.32604/iasc.2024.059591

This article is a correction of:

Noise-Filtering Enhanced Deep Cognitive Diagnosis Model for Latent Skill Discovering
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Abstract

This article has no abstract.

In the article “Noise-Filtering Enhanced Deep Cognitive Diagnosis Model for Latent Skill Discovering” by Jing Geng, Huali Yang and Shengze Hu (Intelligent Automation & Soft Computing, 2023, Vol. 37, No. 2, pp. 1311–1324. doi: 10.32604/iasc.2023.038481), the References [1–2], [4–12], and [23–29] were not appropriately aligned with the context of the main text.

The authors sincerely apologize for any inconvenience caused by the inclusion of References [1–2], [4–12], and [23–29]. The authors have addressed this issue by replacing these references with more relevant literature to support the content in the respective sections.

Please find below the corrected information:

Reference [1] has been replaced with: L. Tetzlaff, F. Schmiedek and G. Brod, “Developing personalized education: A dynamic framework,” Educational Psychology Review, vol. 33, pp. 863–882, 2021.

Reference [2] has been replaced with: A. Sun and X. Chen, “Online education and its effective practice: A research review,” Journal of Information Technology Education: Research, vol. 15, pp. 157–190, 2016.

Reference [4] has been replaced with: A. Peña-Ayala, “Educational data mining: A survey and a data mining-based analysis of recent works,” Expert Systems with Applications, vol. 41, no. 4, pp. 1432–1462, 2014.

Reference [5] has been replaced with: Y. Zhang, Y. Yun, R. An, J. Cui, H. Dai and X. Shang, “Educational data mining techniques for student performance prediction: method review and comparison analysis,” Frontiers in Psychology, vol. 12, pp. 698490, 2021.

Reference [6] has been replaced with: C. Liu and Y. Cheng, “An application of the support vector machine for attribute-by-attribute classification in cognitive diagnosis,” Applied Psychological Measurement, vol. 42, no. 1, pp. 58–72, 2018.

Reference [7] has been replaced with: R. S. Baker, T. Martin and L. M. Rossi, “Educational data mining and learning analytics,” in The Wiley Handbook of Cognition and Assessment: Frameworks, Methodologies, and Applications, pp. 379–396, 2016.

Reference [8] has been replaced with: C. F. Lin, Y. C. Yeh, Y. H. Hung and R. I. Chang, “Data mining for providing a personalized learning path in creativity: An application of decision trees,” Computers & Education, vol. 68, pp. 199–210, 2013.

Reference [9] has been replaced with: N. A. Samah, N. Yahaya and M. B. Ali, “Individual differences in online personalized learning environment,” Educational Research and Reviews, vol. 6, no. 7, pp. 516–521, 2011.

Reference [10] has been replaced with: K. S. McCarthy, M. Watanabe, J. Dai and D. S. McNamara, “Personalized learning in iSTART: Past modifications and future design,” Journal of Research on Technology in Education, vol. 52, no. 3, pp. 301–321, 2020.

Reference [11] has been replaced with: S. Y. Chen, P.-R. Huang, Y.-C. Shih and L.-P. Chang, “Investigation of multiple human factors in personalized learning,” Interactive Learning Environments, vol. 24, no. 1, pp. 119–141, 2016.

Reference [12] has been replaced with: A. B. F. Mansur, N. Yusof and A. H. Basori, “Personalized learning model based on deep learning algorithm for student behaviour analytic,” Procedia Computer Science, vol. 163, pp. 125–133, 2019.

Reference [23] has been replaced with: Y. Q. Zhou, Q. Liu, J. Z. Wu, F. Wang, Z. Y. Huang et al., “Modeling context-aware features for cognitive diagnosis in student learning,” in Proc. of the 27th ACMSIGKDD Conf. on Knowledge Discovery and Data Mining, pp. 2420–2428, 2021.

Reference [24] has been replaced with: J. T. Li, F. Wang, Q. Liu, M. X. Zhu, W. Huang et al., “HierCDF: A bayesian network-based hierarchical cognitive diagnosis framework,” in Proc. of the 28th ACMSIGKDD Conf. on Knowledge Discovery and Data Mining, pp. 904–913, 2022.

Reference [25] has been replaced with: S. Cheng, Q. Liu, E. H. Chen, Z. Huang, Z. Y. Huang et al., “DIRT: Deep learning enhanced item response theory for cognitive diagnosis,” in Proc. of the 28th ACM Int. Conf. on Information and Knowledge Management, pp. 2397–2400, 2019.

Reference [26] has been replaced with: F. Wang, Q. Liu, E. H. Chen, Z. Y. Huang, Y. Y. Chen et al., “Neural cognitive diagnosis for intelligent education systems,” in Proc. of the AAAI Conf. on Artificial Intelligence, vol. 34, no. 4, pp. 6153–6161, 2020.

Reference [27] has been replaced with: L. Gao, Z. Y. Zhao, C. Li, J. L. Zhao and Q. T. Zeng, “Deep cognitive diagnosis model for predicting students' performance,” Future Generation Computer Systems, vol. 126, pp. 252–262, 2022.

Reference [28] has been replaced with: H. W. Yang, T. L. Qi, J. Li, L. J. Guo, M. R. Ren et al., “A novel quantitative relationship neural network for explainable cognitive diagnosis model,” Knowledge-Based Systems, vol. 250, pp. 109156.

Reference [29] has been replaced with: C. Y. Chiu, J. A. Douglas and X. Li, “Cluster analysis for cognitive diagnosis: Theory and applications,” Psychometrika, vol. 74, no. 4, pp. 633–665.

The authors state that the scientific conclusions are unaffected. This correction was approved by the Intelligent Automation & Soft Computing Editorial Office. The corrected version of the article has been updated accordingly.


Cite This Article

APA Style
Geng, J., Yang, H., Hu, S. (2024). Correction: noise-filtering enhanced deep cognitive diagnosis model for latent skill discovering. Intelligent Automation & Soft Computing, 39(5), 985-986. https://doi.org/10.32604/iasc.2024.059591
Vancouver Style
Geng J, Yang H, Hu S. Correction: noise-filtering enhanced deep cognitive diagnosis model for latent skill discovering. Intell Automat Soft Comput . 2024;39(5):985-986 https://doi.org/10.32604/iasc.2024.059591
IEEE Style
J. Geng, H. Yang, and S. Hu, “Correction: Noise-Filtering Enhanced Deep Cognitive Diagnosis Model for Latent Skill Discovering,” Intell. Automat. Soft Comput. , vol. 39, no. 5, pp. 985-986, 2024. https://doi.org/10.32604/iasc.2024.059591


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This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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