Recomendação de estratégias pedagógicas através de emoções, perfis de personalidade e inteligências múltiplas utilizando raciocínio baseado em casos

Abstract

This paper presents a system for recommending pedagogical strategies in virtual learning environments. For this, individual characteristics of the student were considered, such as personality profile and basic emotions detected during the cognitive process. In addition, a Case-Based Reasoning system was developed to develop new cases through the information stored in the student model, as well as the relation of these characteristics to the Multiple Intelligences of each student. Thus, through the initial set of pedagogical strategies stored in the student model, we have as results a database composed of 91 new cases retained from 9 initial cases.

Using Project-based Learning in a Hybrid e-Learning System Model

“…In the state of the art, this approach has been approached mainly through two techniques of Artificial Intelligence: Expert Systems and CBR, the latter being the technique that will be used in this work. For example, in [49], CBR is used for the selection and recommendation of pedagogical strategies, from an initial set of strategies stored in the student's model, considering the particular characteristics of each individual, such as personality profiles, multiple emotions and intelligences, and cognitive processes of the students, within virtual learning systems [49]; while in [50], the assumption is considered that "learners struggle to identify and retrieve the optimal case to solve a new problem", and proposes a CBR-based recommendation system to "support the decision-making process about which case is most relevant to solve new problems".…”