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Research Article Open access CC BY 4.0

From Data to Decisions: A Scoping Review of Actionable Learning Analytics for Teaching and Assessment

Ademola Busayo Ajayi, Maureen Ifeyinwa Emenike, Benjamin Osaze Enobakhare, Onyebuchi Arthur Chukwuka, Eugene Rwandashi, Lilian Chinweotito Awah

Asian Journal of Education and Social Studies · pp. 673–685 · Published 13 Nov 2025

10.9734/ajess/2025/v51i112643

Abstract

This study presents a systematic review of analytics-informed teaching practices, exploring how educators across K–12 and higher education contexts use learning analytics to enhance pedagogy and student outcomes. A comprehensive search across four major databases identified empirical studies grounded in established frameworks, including the Learning Analytics Cycle. The findings reveal consistent benefits, such as increased student engagement and more adaptive instruction, alongside enduring challenges related to limited data literacy, ethical concerns, and infrastructural constraints. The review highlights the need for longitudinal and context-sensitive research to better understand how analytics influence teaching and learning across diverse educational systems. It concludes that the actionability of learning analytics is fundamentally a socio-technical process—one that depends on educators’ data literacy and robust ethical governance to ensure responsible and sustainable impact.

Actionable learning analytics teaching and assessment data-informed pedagogy student engagement educational data mining inclusive education

Cited by 1

Data-Driven Adaptive Learning Management: A Decision-Making Model

S. M. Levin · International Journal For Multidisciplinary Research · 2026

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