A Neural Network-Based Student Performance Evaluation Method for Smart Learning Systems-Reference-Cited by-同舟云学术

A Neural Network-Based Student Performance Evaluation Method for Smart Learning Systems

Published:2023 Issue: Volume: Page:127-137
ISSN:2194-5357
Container-title:Soft Computing Applications
language:
Short-container-title:

Author:

Soomro Saima Siraj^ORCID,Jalbani Akhtar Hussain^ORCID,Channa Muhammad Ibrahim^ORCID,Lakho Shamshad,Memon Imran Ali^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-23636-5_10

Reference17 articles.

1. Karaci, A.: Intelligent tutoring system model based on fuzzy logic and constraint-based student model. Neural Comput. Appl. 31(8), 3619–3628 (2018). https://doi.org/10.1007/s00521-017-3311-2

2. Corbett, A.T., Koedinger, K.R., Anderson, J.R.: Intelligent tutoring systems. In: North-Holland Handbook of Human-Computer Interaction, pp. 849–874 (1997)

3. Roventa, E., Naaji, A., Dascal, I.: Using fuzzy techniques for students’ evaluation. In: the 14th WSEAS International Conference on Computers: Part of the 14th WSEAS CSCC Multiconference-Volume I World Scientific and Engineering Academy and Society (WSEAS), pp. 375–378 (2010)

4. Rao, D.H., Mangalwede, S.R., Deshmukh, V.B.: Student performance evaluation model based on scoring rubric tool for network analysis subject using fuzzy logic. In: IEEE International Conference on Electrical, Electronics, Communication, Computer, and Optimization Techniques (ICEECCOT) (2017)

5. Deshmukh, V.B., Mangalwede, S.R., Rao, D.H.: Student performance evaluation model based on Bloom’s Taxonomy using fuzzy logic. In: International Conference on Electrical, Electronics, Communication, Computer, Mechanical and Computing (EECCMC). IEEE (2018)