Year: 2025
Type: article
Abstract: : Learning Platforms generate huge data and play a vital role in the field of education as a nation's future is dependent upon the progress of the students. These platforms generate lots of data and, offer valuable opportunities to predict and categorize student performance. Machine Learning (ML) has become a prominent method for analyzing this data, providing meaningful insights into academic outcomes. This research proposes a deep learning-based approach for processing and classifying student performance using ML algorithms. ML classifiers like Support Vector Machines (SVM), Multi-Layer Perceptron (MLP), and Naïve Bayes are applied to preprocessed data. The models' effectiveness is measured using parameters like accuracy, precision, recall, F-score, and the time taken to train each model.
Authors: Ms.Gazala Begum, Ms.Bhavana, Dr.Jabeen Sultana, Mohammed Ehtesham Ul Baqui, Nouman Ajmal Khan
Institution: Imam Mohammad ibn Saud Islamic University
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4410923291