Um modelo computacional de combinação social aplicado ao processo de planejamento de orientadores em ambientes virtuais de aprendizagem

Abstract

Distance Education (DE) is a teaching modality capable of providing professional formation for people with limited access to university education. For this end, a set of computational tools is required in assisting the teaching and learning process (PEREIRA et al., 2006a). Moreover, some common obstacles for DE are the issues of identifying possible advisors for those students in the process of writing monographs and work overload. This has become an important issue for researches, placing their emphasis on the idea of working the interests of students, teachers and education managers. For such, this work used a quali-quantitative approach, in a way that data were collected in a Distance Learning Environment (DLE) and also by the application of a structured questionnaire to potential advisors. As such, this work has the objective of proposing a Computational Model of Social Combination that helps the DE Manager in the process of advisors planning for monograph works. This paper presents three computational tools developed by using genetic algorithms. These tools were applied according to the context of the DE undergraduate course of Information Systems offered by the Federal University of Alagoas and the Open University of Brazil. The results show that the proposed computational model can be used to help DE Managers to reduce the cases of students’ and advisors’ profiles incompatibility, as well as to reduce docent work overload.