Structural Study of Post-COVID-19 Use Based on LMS Log Data Analysis from the University of Extremadura: A Case Study of Learning Analytics

The widespread adoption of Learning Management Systems (LMSs) in higher education has not necessarily led to profound pedagogical transformations, raising questions about how digital technologies are actually integrated into teaching practices. This study aims to describe and map the techno-pedagogical configurations used by instructors at the University of Extremadura (Spain) to identify teaching patterns and characterize course design within a virtual campus. Using log data from 12,361 Moodle courses during the 2021–2022 academic year, a K-means clustering analysis was applied to classify courses based on their use of digital tools and resources. The analysis identified five distinct clusters ranging from traditional models with minimal LMS use (67.37%) to advanced innovation configurations (3.98%), including audiovisual-based innovation, participative traditional models, and repository-focused approaches. The results indicate that the implementation of techno-pedagogical strategies is highly heterogeneous and that courses classified as more innovative do not consistently produce better academic outcomes. These findings suggest that for most faculty, the LMS functions as digital support for traditional face-to-face teaching rather than as a driver of pedagogical transformation, highlighting the need for teacher-centered analytics capable of capturing instructional design patterns beyond mere behavioral metrics.

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Journal
Education Sciences
Published
2026-02-16
DOI
https://doi.org/10.3390/educsci16020319
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Structural Study of Post-COVID-19 Use Based on LMS Log Data Analysis from the University of Extremadura: A Case Study of Learning Analytics

Francisco-Ignacio Revuelta-Domínguez, Alicia González-Pérez, Jorge Guerra-Antequera, Rubén Arriazu-Muñoz
Education Sciences
Online Learning and Analytics
article

Structural Study of Post-COVID-19 Use Based on LMS Log Data Analysis from the University of Extremadura: A Case Study of Learning Analytics

Francisco-Ignacio Revuelta-Domínguez, Alicia González-Pérez, Jorge Guerra-Antequera, Rubén Arriazu-Muñoz
article en

Abstract

The widespread adoption of Learning Management Systems (LMSs) in higher education has not necessarily led to profound pedagogical transformations, raising questions about how digital technologies are actually integrated into teaching practices. This study aims to describe and map the techno-pedagogical configurations used by instructors at the University of Extremadura (Spain) to identify teaching patterns and characterize course design within a virtual campus. Using log data from 12,361 Moodle courses during the 2021–2022 academic year, a K-means clustering analysis was applied to classify courses based on their use of digital tools and resources. The analysis identified five distinct clusters ranging from traditional models with minimal LMS use (67.37%) to advanced innovation configurations (3.98%), including audiovisual-based innovation, participative traditional models, and repository-focused approaches. The results indicate that the implementation of techno-pedagogical strategies is highly heterogeneous and that courses classified as more innovative do not consistently produce better academic outcomes. These findings suggest that for most faculty, the LMS functions as digital support for traditional face-to-face teaching rather than as a driver of pedagogical transformation, highlighting the need for teacher-centered analytics capable of capturing instructional design patterns beyond mere behavioral metrics.

Education SciencesVol. 16(2)
Universidad de Extremadura (ES)
Universidad de Extremadura
Industry, innovation and infrastructure
Openalex Percentile: Top 61%
Online Learning and Analytics
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Structural Study of Post-COVID-19 Use Based on LMS Log Data Analysis from the University of Extremadura: A Case Study of Learning Analytics — Francisco-Ignacio Revuelta-Domínguez, Alicia González-Pérez, et al. · Education Sciences (2026) | TGRS Research Map | TGRS