Learning Analytics in Islamic Religious Education: Predicting Students’ Learning Achievement through Educational Data Mining
Husna Husna; Khalid Abdullah Al Muzaini; Maryam Rashid Saleh Al Tamimi; Muneera Mohammed Al Dossary · 2026 · Ar-Rayyan Journal of Islamic Education
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
The increasing availability of educational data has opened new opportunities for improving instructional decision-making through learning analytics. However, its application in Islamic Religious Education (IRE) remains limited, particularly in predicting students’ academic achievement and learning behavior. This study aims to develop a learning analytics model capable of identifying learning patterns and predicting students’ performance in IRE. A quantitative research design employing Educational Data Mining (EDM) techniques was conducted using learning management system (LMS) data from 512 se
Abstract by Husna Husna; Khalid Abdullah Al Muzaini; Maryam Rashid Saleh Al Tamimi; Muneera Mohammed Al Dossary, Ar-Rayyan Journal of Islamic Education (2026) — licensed CC BY-SA 4.0.
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Metadata source: OpenAlex · DOI 10.67899/ar.v3i1.225