GrouProfile: um modelo de gerenciamento de perfis de grupos de aprendizes

Abstract

The Modality of E-Learning and Distance Education (LDE) obtained an exponential growth regarding the number of new courses and students enrolled recently. In order to attend this demand adequately, the distance learning tools should be improved constantly. These tools are known as Virtual Learning Environments (VLE) and generally presenting interaction channels and pedagogical discussions that promote the development of educational methodologies.The development of methodologies such as AVA is helpful to prepare, edit and manage classes, becoming a tool to support discussions, presentations, and other activities virtual form. The AVA also can be used to provide classroom support, to delivery and distribute activities and also as content storage. Although, if initially VLE creates an easy way to the realization of course in the LDE modality, on another hand, can lead to creating gaps among teacher and their student group. It happens because generally the VLE courses are made at a distance, without physical contact between the professor, students or groups of them, such as characters, preference, problems, feelings. This impacts directly in the classes production, because of the correct identification of students group profile, allows teachers to prepare lessons and materials more efficient, attractive and aligned with the learning objectives of each group. In addition, searching for a solution to help the creation of groups of learners profiles in AVA, this work proposes a model called GrouProfile, which allows management of student groups profiles based on historical contexts. Moreover, this work proposes a software agent that will work like a monitor of groups, allowing to the teachers a way to management where the notifications, movements of a particular group are presented for the creation of groups dynamically, based on pre-determined teacher’s rules such as proactivity, reactivity and interest of a group of students with better or worst performance. Also, the model establishes a general overview of the whole class, providing to the teacher a tool to attend to specific situations and a way to improve the learning method to attend the expectations of the majority of the students. This profile obtained is stored following the history of the evolution and changes of each class. We started this study by performing a literature review using the Snowballing strategy. Subsequently, a survey was conducted through questionnaires applied to the teachers, seeking its vision about proactive, reactive and interest, students characteristic as well, which are the students with better and worst performance. Finally, to validate the results, a case study was carried out and a new questionnaire was applied only to the teachers of the classes that participated before. After completing it, we could see that GrouProfile can establish a general overview of the class and the individual profile of each student in a very similar view that the classroom teacher has.