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JAIT 2024 Vol.15(6): 784-797
doi: 10.12720/jait.15.6.784-797

Maximizing Learning Outcomes through Fuzzy Inference System and Graph Theory Based on Learning Analytics

J. Chandra Sekhar 1, Balajee J. 2, Sanjiv R. Godla 3, Vuda Sreenivasa Rao 4, Yousef A. B. El-Ebiary 5, and Chamandeep Kaur 6,*
1. Department of Computer Science and Engineering, NRI Institute of Technology, Guntur, India
2. Department of Computer Science and Engineering, Mother Theresa Institute of Engineering and Technology,
Andhra Pradesh, India
3. Department of CSE (Artificial intelligence and Machine Learning), Aditya College of Engineering and Technology Surampalem, Andhra Pradesh, India
4. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation,
Green Fileds, Vaddeswaram, India
5. Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin University, Malaysia
6. Department of Computer Science, Jazan University, Jazan, Saudi Arabia
Email: jcsekhar9@nriit.ac.in (J.C.S.); Balajeej04@gmail.com (B.J.); sanjiv_gsr@yahoo.com (S.R.G.); vsreenivasarao@kluniversity.in (V.S.R.); yousefelebiary@unisza.edu.my (Y.A.B.E-E);
kaur.chaman83@gmail.com (C.K.)
*Corresponding author

Manuscript received November 24, 2023; revised December 7, 2023; accepted January 18, 2024; published June 26, 2024.

Abstract—Teachers are urged to explore innovative instructional methods, including technology integration and personality-oriented approaches, to enhance learning outcomes and foster better upbringing. The unique tactic proposed in this study involves incorporating learning analytics and feedback data into pedagogy improvement efforts. Teachers get access to visual classroom data about the active learning facilitation strategies they use in their classes using the automated feedback platform TEACHActive. In addition to discussing the system’s information flow from an autonomous observation model to the feedback data, including the technological architecture, the study also examines the core necessity of the TEACHActive system improving teaching practises through reflection. To gather these data, a fuzzy inference method and graph theory are used. By combining graph theory and fuzzy logic, the conventional approach is innovatively modified in order to enhance instruction. By utilising these strategies, teachers can enhance their pedagogical practises and individualise learning experiences. The integration of the TEACHActive automated feedback platform, which utilizes learning analytics and feedback information, to improve teaching practices and personalize learning experiences through the fusion of graph theory and fuzzy logic, resulting in enhanced education outcomes. This research fills the gap in conventional instructional techniques by introducing TEACHActive, a system that integrates learning analytics and feedback data through fuzzy inference and graph theory. By providing insightful information on active learning strategies, the study uniquely improves teaching practices, enhancing student learning and improving academic results. The study’s unique approach offers teachers valuable insights into active learning techniques, leading to better pedagogical procedures for improved learning and upbringing results. The method is feasible to run fuzzy inference systems and statistical analysis using Matlab software. The results show that four variables have the most impact on how well pedagogical processes work.
 
Keywords—pedagogy, learning activities, feedback data, fuzzy inference system, graph theory

Cite: J. Chandra Sekhar, Balajee J., Sanjiv R. Godla, Vuda Sreenivasa Rao, Yousef A. B. El-Ebiary, and Chamandeep Kaur, "Maximizing Learning Outcomes through Fuzzy Inference System and Graph Theory Based on Learning Analytics," Journal of Advances in Information Technology, Vol. 15, No. 6, pp. 784-797, 2024.

Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.