Abordagem avaliativa multidimensional para previsão da evasão do discente em cursos on-line.

Abstract

The student’s dropout in online courses was pointed out as one of the biggest issue in the area according to the educational organizations. The main result was the high dropout rates in these courses compared to face-to-face courses in 2015 in Brazil (between 25% and 50%). Moreover, this challenge belongs to the virtual learning worldwide. In this sense, the literature review showed that several approaches are adopted to minimize the student’s dropout rates. However, they limited their focus on a learning unique resource (forum, chat, upload, download, submissions). Regarding these approaches, the current research detected an insufficiency of studies about the educational interactions of the dropout student and uncertainties in the assessment. Many methodologies are used by teachers to manage a subjectivity and uncertainty associated to the evaluation process, such as: fuzzy logic, Bayesian networks, Markov chains, etc. This thesis emphasized the fuzzy logic, because this technique solves the ambiguity found in the learning evaluation by the expert. We present an assessment framework (FuzzySD) to track the virtual classroom and to support the teacher to make a prediction of students’ dropout in online courses. In this sense, we analyzed the information related to the students’ actions during the teaching-learning process in online courses. It can be denominated as multidimensional analysis because we assessed multiple variables related to the student’s behavior. Such behavioral variables were fundamental in the definition of three main metrics to the understanding of student avoidance, they are: Self-regulation, Interaction and Motivation. It is important to consider a presence of fuzzy logic to deal with the input metrics of the FuzzySD framework. The evaluation of FuzzySD was performed by means of precision analysis on sample cut-outs based on dataset from courses of “IFPB Virtual”. The accuracy of the approach is analyzed as results of its own indicators between 65% and 95% of hits. Finally, the results discussed about the challenges of applying a multidimensional evaluative module to the context of Brazilian online courses.