images
Intelligent Automation & Soft Computing
images

DOI: 10.32604/iasc.2024.059591

CORRECTION

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

Jing Geng1,*, Huali Yang2 and Shengze Hu3

1National Engineering Research Center of Educational Big Data, Central China Normal University, Wuhan, 430079, China
2Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan, 430079, China
3School of Computer Science and Artificial Intelligence, Wuhan Textile University, Wuhan, 430079, China
*Corresponding Author: Jing Geng. Email: gengjing55@163.com

Published: 31 October 2024

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.

images
Copyright © 2024 The Authors. Published by Tech Science Press.
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.