Obtaining a Learning Analytics model with information from an LMS
Leonardo Nevárez Chávez- Marisela Ivette Caldera Franco
- Gregorio Ronquillo Máynez
Published 2021-12-10
Keywords
- Data analysis,
- academic performance,
- Moodle platform,
- analysis models,
- educational intervention
- Análisis de datos,
- rendimiento académico,
- plataforma Moodle,
- modelos de análisis,
- intervención educativa
How to Cite
Copyright (c) 2021
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Abstract
As a result of the teaching and learning process, data in higher education institutions is generated and obtained in different computational systems, such as internal systems, the LMS (Learning Management System), social media, among others. The information obtained from these systems is rarely used for its analysis, feedback, and processes improvement. Considering only one LMS, these produce important information, as students’ logins, sections or seen elements, delivery of homework and its compliance in time limits, as well as the participation in forums and other activities. This research has the purpose of describing the use of the information contained in the logs, which is generated by the Moodle LMS, with the objective of establishing a Learning Analytics model, leading to the prediction of the students’ performance. The model is incorporated in an informatic application through a friendly interface, and it serves to make known the model results to tutors, professors or authorized staff. The application identifies students in academic danger, and it is suggested to be used as a support to decide a possible academic intervention on behalf of students. Simple regression, multiple regression, grouping, and main components analysis techniques are used to obtain different prediction models. The CRISP-DM methodology is applied as a guidance in the development process.
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