Contributions of the report-type plugin for dropout risk identification in Moodle VLE based on data visualization
DOI:
https://doi.org/10.5753/rbie.2020.28.0.01Keywords:
Dropout, Moodle, Learning Analytics, Data Visualization, IndicatorsAbstract
This work belongs to the field of educational research known as Learning Analytics and aims to analyze the contribution of social, cognitive and behavioral indicators of student learning, based on Ava Moodle data, to help tutors and managers of online courses in identification of students at risk of circumvention. AVAs generate reports and logs on student activities, however, they are often difficult to understand for tutors, teachers and educational managers. Thus, they do not allow the identification of evasion problems more objectively. Therefore, it is believed that the use of a solution that collects data of indicators related to the accesses, interactions and notes of the students in an AVA and presents them through infographic, can help teachers, tutors and managers to identify students who can to leave a course at a distance. Therefore, a report plugin for the AVA Moodle was designed and implemented, containing filtering features, sending notifications and interactive graphics generated by the Google Charts tool. To evaluate this plugin, qualitative analyzes were carried out through a focus group with teachers, tutors and managers of distance learning courses. It was concluded, then, that the plugin provides an improvement in the perception of these professionals on students who are at risk of avoidance, in comparison to the native logs and reports of Moodle.
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Copyright (c) 2020 Maria Tatiane de Souza Brito, Francisco Petrônio Alencar de Medeiros, Ed Porto Bezerra, Alex Sandro Rodrigues Barbosa
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