The Global Landscape of Learning Analytics Research in Higher Education: A Bibliometric Analysis

Reni Kurnia; Ambiyar Ambiyar; Fahmi  Rizal

doi:10.56806/jh.v7i3.455

Authors

Reni Kurnia Universitas Negeri Padang
Ambiyar Ambiyar Universitas Negeri Padang
Fahmi Rizal Universitas Negeri Padang

DOI:

https://doi.org/10.56806/jh.v7i3.455

Keywords:

Learning analytics, Bibliometrics analysis , educational data mining , Self-regulated learning

Abstract

The growing adoption of digital learning environments has intensified interest in learning analytics as a means of understanding student behavior and improving educational decision-making in higher education. Despite the increasing volume of studies in this field, a clear picture of its global research development remains limited. This study examines the research landscape of learning analytics in higher education through a bibliometric analysis of publications indexed in the Scopus database from 2015 to 2025. Following a multi-stage screening process based on publication year, document type, language, and accessibility, 479 open-access journal articles were selected for analysis. Bibliometric mapping was conducted using Scopus metadata and VOSviewer to identify publication trends, influential contributors, collaboration networks, and thematic patterns. The results indicate a consistent rise in publication output over the past decade, reflecting expanding scholarly attention to data-driven learning practices. Research activity is largely concentrated in several productive countries and leading academic journals, with collaboration networks centered around a few dominant institutions. Keyword analysis reveals a shift from basic descriptive analytics toward predictive modeling, artificial intelligence, student engagement, and ethical issues related to data use. These findings offer a clearer understanding of the field’s intellectual structure and may serve as a reference for future research and policy development in learning analytics.

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