Computer-Assisted Recommendation for Monographs Advisory: Based on Informational Profile and Teachers’ Advisory Capacity

Abstract

Social Combination Systems are recommendation systems able to suggest people, instead of recommending products or services. These systems are applied in various contexts, including Distance Learning (DL), modality of education that needs to have a set of computational tools in order to facilitate the teaching-learning process. The identification of potential advisors and work overload are some of the difficulties in this process. Researches in this area invest in the idea of working interests of students, teachers and education managers. Therefore, this study used a qualitative and quantitative approach, so that the data were collected in a Virtual Learning Environment (VLE) and through the application of a structured questionnaire to potential advisors. Thus, this paper aims to describe the application of two recommendation techniques, implemented through a Informational Model of Social Combination that assists the Educational Manager in the process of monographs advisors allocation. Three systems developed through genetic algorithms will be presented, which were applied in the Bachelor’s course of Information Systems, offered jointly by the Federal University of Alagoas and the Open University of Brazil. These results indicate that the proposed filtering methods can be used to help educational managers in order to reduce cases of incompatibility of profiles of students and advisors as well as reducing the workload of teachers.