Generating Intelligent Teaching-Learning Systems using Concept Maps and Case-Based Reasoning.

The use of pedagogical methods with the technologies of the information and communications produce a new quality that favors the task of generating, transmitting and sharing knowledge. Such is the case of the pedagogical effect that produces the use of the Concept Maps, which constitute a tool for the management of knowledge, 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 beexamined and shared. However, it does not address how relevant Concept Maps can be retr ieved or adapted to new problems. Case-Based Reasoning is playing an increasing role in knowledge retrieval and reuse for corporate memories, and its capabilities are appealing to augment the concept mapping process. 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 applied in the teaching-learning process by laymen in the Computer Science field.