Integration of neuro-fuzzy modeling in learning management systems to predict academic achievement of graduates

A. Zulkhazhav (), M. Milosz (), A. Nazyrova (), A. Barlybayev () and G. Bekmanova ()

International Journal of Innovative Research and Scientific Studies, 2025, vol. 8, issue 3, 4900-4914

Abstract: This study explores the application of intelligent modeling to support academic decision-making by integrating a predictive system into a university’s learning management environment. Utilizing 25,706 records from 16,158 students over an eight-year period (2015–2022), the dataset includes exam results and final grades across 353 subjects within bachelor's, master's, and PhD programs. After transforming categorical variables - such as education level, course year, and subject name - into numerical format and applying normalization, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was developed to model student performance. This system was chosen for its capacity to capture complex, nonlinear relationships while providing interpretable outputs through fuzzy rules. Comparative evaluation using RMSE, MAE, MSE, and R² metrics demonstrated that ANFIS consistently outperformed alternative models, achieving the lowest RMSE value of 12.80. These findings highlight the model’s reliability and its effectiveness in analyzing academic outcomes across diverse student cohorts. By enabling the early identification of academic risk and delivering interpretable predictions, the system offers practical value to educational institutions aiming to personalize learning pathways and implement data-informed strategies to enhance student success in digital learning environments.

Keywords: Computing programs; fuzzy systems; neuro-fuzzy models; prediction; student performance. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijirss.com/index.php/ijirss/article/view/7637/1656 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:aac:ijirss:v:8:y:2025:i:3:p:4900-4914:id:7637

Access Statistics for this article

International Journal of Innovative Research and Scientific Studies is currently edited by Natalie Jean

More articles in International Journal of Innovative Research and Scientific Studies from Innovative Research Publishing
Bibliographic data for series maintained by Natalie Jean ().