Supporting Early Academic Intervention Using Learning Analytics Through a Power BI-Based Dashboard

Authors

Nuraisyah Fitrie Abdullah

Faculty of Accountancy, UiTM Cawangan Sarawak (Malaysia)

Azmira Abdullah

Faculty of Accountancy, UiTM Cawangan Sarawak (Malaysia)

Siti Maliza Salleh

Faculty of Accountancy, UiTM Cawangan Sarawak (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2026.102100137

Subject Category: Education

Volume/Issue: 10/21 | Page No: 1644-1648

Publication Timeline

Submitted: 2026-09-19

Accepted: 2026-09-24

Published: 2026-10-02

Abstract

ABSTRACT
Early identification of students requiring academic support necessitates that lecturers review continuous assessment results while intervention remains possible. However, maintaining quiz, test, and assignment marks in separate records can obscure recurring weaknesses. This paper introduces a proposed Power BI dashboard that consolidates these results, displays both class and individual student performance, and highlights repeated low scores for lecturer review. The proposed workflow connects identified assessment concerns to appropriate responses, such as consultations, targeted feedback, or focused revision sessions, and documents subsequent progress. Risk flags are designed to prompt professional judgement rather than serve as automatic indicators of student outcomes. A future comparison of cohorts before and after implementation will assess whether dashboard-supported monitoring correlates with earlier intervention and improved academic performance. This approach provides a practical framework for leveraging existing assessment records to inform academic support, contingent upon data quality, privacy considerations, and careful interpretation.

Keywords

Learning Analytics, Power BI, Student Performance, Continuous Assessment, Early Academic Intervention.

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References

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