2024
Marticorena-Sánchez, Raúl; López-Nozal, Carlos; Serrano-Mamolar, Ana; Olivares-Gil, Alicia
UBUMonitor: Desktop application for visual e-learning student clustering with Moodle Journal Article
In: SoftwareX, vol. 26, pp. 101727, 2024, ISSN: 2352-7110.
Abstract | Links | BibTeX | Tags: e-learning analytic, Educational data clustering process, Educational software, Learning management systems, Unsupervised machine learning
@article{MARTICORENASANCHEZ2024101727,
title = {UBUMonitor: Desktop application for visual e-learning student clustering with Moodle},
author = {Raúl Marticorena-Sánchez and Carlos López-Nozal and Ana Serrano-Mamolar and Alicia Olivares-Gil},
url = {https://www.sciencedirect.com/science/article/pii/S2352711024000980},
doi = {https://doi.org/10.1016/j.softx.2024.101727},
issn = {2352-7110},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {SoftwareX},
volume = {26},
pages = {101727},
abstract = {UBUMonitor is an open-source Java desktop tool designed to analyse student interactions and grades within courses in the Moodle learning management system. Its primary goal is to assist educational researchers in making informed decisions. The application offers flexible configuration of educational datasets, enabling educational researchers to customize features of their analyses based on filters such as time, participants, e-resources, e-forums and teaching e-activities. With a modular architecture developed iteratively in Github with 35 releases, UBUMonitor has demonstrated its usability in teaching through several published use cases. This paper focuses specifically on the student clustering module, which allows customization of course activity access and grading, supports multiple clustering algorithms, and incorporates techniques for validating both the optimal number of clusters and the quality of cluster result.},
keywords = {e-learning analytic, Educational data clustering process, Educational software, Learning management systems, Unsupervised machine learning},
pubstate = {published},
tppubtype = {article}
}
UBUMonitor is an open-source Java desktop tool designed to analyse student interactions and grades within courses in the Moodle learning management system. Its primary goal is to assist educational researchers in making informed decisions. The application offers flexible configuration of educational datasets, enabling educational researchers to customize features of their analyses based on filters such as time, participants, e-resources, e-forums and teaching e-activities. With a modular architecture developed iteratively in Github with 35 releases, UBUMonitor has demonstrated its usability in teaching through several published use cases. This paper focuses specifically on the student clustering module, which allows customization of course activity access and grading, supports multiple clustering algorithms, and incorporates techniques for validating both the optimal number of clusters and the quality of cluster result.