D 2026

Fifteen Years of Learning Analytics Research: Topics, Trends, and Challenges

ŠVÁBENSKÝ, Valdemar; Conrad BORCHERS; Elvin FORTUNA; Elizabeth B. CLOUDE; Dragan GAŠEVIĆ et al.

Basic information

Original name

Fifteen Years of Learning Analytics Research: Topics, Trends, and Challenges

Authors

ŠVÁBENSKÝ, Valdemar; Conrad BORCHERS; Elvin FORTUNA; Elizabeth B. CLOUDE and Dragan GAŠEVIĆ

Edition

New York, NY, USA, Proceedings of the 16th Learning Analytics and Knowledge Conference (LAK '26), 12 pp. 2026

Publisher

ACM

Other information

Language

English

Type of outcome

Proceedings paper

Country of publisher

United States of America

Confidentiality degree

is not subject to a state or trade secret

Publication form

electronic version available online

References:

Marked to be transferred to RIV

No

Organization

Fakulta informatiky – Repository – Repository

Keywords in English

LAK community; survey; recent development; current landscape; global perspective

Links

GN25-15839I, research and development project.
Changed: 16/1/2026 00:51, RNDr. Daniel Jakubík

Abstract

In the original language

The learning analytics (LA) community has recently reached two important milestones: celebrating the 15th LAK conference and updating the 2011 definition of LA to reflect the 15 years of changes in the discipline. However, despite LA's growth, little is known about how research topics, funding, and collaboration, as well as the relationships among them, have developed within the community over time. This study addressed this gap by analyzing all 936 full and short papers published at LAK over a 15-year period using unsupervised machine learning, natural language processing, and network analytics. The analysis revealed a stable core of prolific authors alongside high turnover of newcomers, systematic links between funding sources and research directions, and six enduring topical centers that remain globally shared but vary in prominence across countries. These six topical centers, which encompass LA research, are: self-regulated learning, dashboards and theory, social learning, automated feedback, multimodal analytics, and outcome prediction. Our findings highlight key challenges for the future: widening participation, reducing dependency on a narrow set of funders, and ensuring that emerging research trajectories remain responsive to educational practice and societal needs.

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