predictive model of student academic performance
Year: 2025
Type: article
Abstract: —Students represent the foundation of the future,and supporting their academic growth is essential for building a skilled and knowledgeable society. Predicting student perfor-mance is highly valuable for both learners and institutions, as it reflects the effectiveness of teaching methods, academic programs,and overall educational quality. With the rapid increase inacademic, demographic, and behavioral data, advanced methodssuch as data mining, machine learning (ML), and deep learning(DL) have been widely adopted to forecast performance andassist in identifying at-risk learners at an early stage. These approaches not only provide meaningful insights but also en-able proactive decision-making, helping teachers and institutions design evidence-based strategies to improve learning outcomes,enhance retention, and ensure long-term student success.
Author: Patil, Suchita
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7105747751
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