Learning analytics tools to analyze progress and results with Moodle LMS Data

Abstract

© 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksTeachers can benefit from the information provided by learning analytics data for multiple purposes. Visual learning analytics dashboards provide near real-time information while more complex offline tools are commonly used to synthesize and transform the data gathered into interpretable information for teachers. The extended use of Learning Management Systems in universities, such as Moodle or Canvas, provides a rich environment to capture learning analytics data from students' interactions while they are progressing in their courses. In this paper, we present two different learning analytics tools aimed at teachers to obtain information about students' progress and results using data from the Moodle LMS at different stages of their learning process: (1) a progress visualization plugin for Moodle, which provides teachers with real-time information about the progress achieved by students in their courses, and the different goals set for their plans; and (2) an analytics Jupyter Notebook tool with a pre-defined set of analysis and visualizations to apply to data gathered from default activities in Moodle. The plugin is in an initial validation stage, while the analysis tool has been tested in a case study in a university course. Combined, both contributions can enrich the information that teachers have during and after the academic year, adapting their classes to better fit students' progress and needs, as well as providing overall results and comparison between groups after the course has finishedThis work received partial support from the Project Indigo! (Ministry of Science and Innovation with reference number PID2019-105951RB-I00 / AEI / 10.13039 / 501100011033) and the Project TEA360 (Ministry of Science, Innovation and Universities with reference number PID2023-150488OB-I00 (SPID202300X150488IV0)