International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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Intelligent Learning Analytics for Monitoring Student Progress in Further Education Mathematics

Author(s) Samira Binteh Hussain
Country United Kingdom
Abstract Intelligent Learning Analytics (ILA) is increasingly transforming contemporary education by enabling real-time monitoring of learner progress and supporting personalised learning pathways. By utilising artificial intelligence, ILA systems diagnose learner misconceptions, identify strengths and weaknesses, and provide targeted interventions. This study investigates the impact of Intelligent Learning Analytics on learner progress in a Further Education (FE) mathematics context using progress check assessments. A descriptive quantitative research design was employed. Progress Check 1 (PC1) and Progress Check 2 (PC2) grades from 40 learners were analysed, with 35 valid paired datasets included. Descriptive statistics and a paired-samples t-test were used to examine performance changes. Findings revealed an increase in mean grades from PC1 to PC2, with nearly half of learners demonstrating improvement. Low-ability learners showed the most substantial gains. Although statistical significance was not achieved at the 0.05 level, results indicate a positive learning trend. The study also highlights limitations of current ILA systems, including excessive micro-tasks and limited teacher control over diagnostic assessments. Overall, ILA demonstrates strong potential to enhance learner outcomes, particularly when integrated with blended learning models such as station rotation.
Keywords Intelligent Learning Analytics, Blended Learning, Station Rotation Model, Mathematics Education, STEM, Scaffolding, CENTURY.
Field Mathematics
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-30
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.64995

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