Concept maps and case-based reasoning: a perspective for the intelligent teaching/learning systems

Abstract

The use of present pedagogical methods and Information and Communication Technologies produce a new quality that favors the task of generating, transmitting and sharing knowledge. That is the case of the pedagogical effect that produces the use of the Concept Maps, which are considered a learning technique as a way to increase meaningful learning in the sciences. It is also used for the knowledge management as an aid to personalize the learning process, to exchange knowledge, and to learn how to learn. Concept Mapping provides a framework for making this internal knowledge explicit in a visual form that can easily be examined and shared. Concept Maps are relevant since they can be retrieved or adapted to new problems. In the other hand, Case-Based Reasoning as a technique in Artificial Intelligence plays an important role in knowledge retrieval and reuse of memories. In this paper the authors present a new approach to elaborate Intelligent Teaching/Learning Systems, where the techniques of Concept Maps and Artificial Intelligence are combined, using the Case-Based Reasoning as theoretical framework for the Student Model. The proposed model has been implemented in the computational system HESEI, which has been successfully used in the teaching/learning process by laymen in the Computer Science field.