Proceedings of The 5th International Conference on Innovation in Science and Technology
Year: 2018
DOI: https://www.doi.org/10.33422/5ist.2018.12.108
A REPORT-TYPE PLUGIN TO INDICATE DROP-OUT RISK IN VIRTUAL LEARNING ENVIRONMENT MOODLE
Maria Tatiane Brito, Francisco Petrônio Alencar de Medeiros and Alex Sandro Barbosa
ABSTRACT:
The growth of distance education over the last two decades has also been accompanied by high drop-out rates. The native reports of the virtual learning environments (VLE) used in online courses usually appear in a format that does not facilitate the interpretation of the information of the students by those involved in the pedagogical process, making it difficult to identify students who are at risk of abandoning the courses. A current trend of VLEs is the incorporation of tools based on Learning Analytics to collect large amounts of data and present to teachers, tutors, and managers to support them in the learning process. Therefore, this work proposes a computational tool for Moodle VLE, which uses data visualization techniques to present cognitive, social and behavioral aspects of the students in order to improve the students’ activity awareness and mediation, aiming to decrease drop-out rates. The computational tool, that is an integrated plugin to Moodle, allows the selection of filters and also the notification of identified students through the sending of messages by the VLE, facilitating the identification of possible students at drop-out risk. The next step of this project will be the evaluation of the tool in terms of user experience and acceptance tests using the qualitative method focus group. The plugin evaluation is planned to be conducted in iterations under IFPB Distance Learning Department and complemented by an analysis of the collected focus group data.
Keywords: distance learning, drop-out rate, learning analytics, Moodle and visualization.