Fuzzy Cognitive Model for Student as Support in Learning
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Garcia Gorrostieta, J.M. & Rose Gómez, C.E. (2008). Fuzzy Cognitive Model for Student as Support in Learning. In K. McFerrin et al. (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference 2008 (pp. 1084-1089). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/27327.
Society for Information Technology & Teacher Education International Conference (SITE) 2008
Las Vegas, Nevada, USA
March 3, 2008
Karen McFerrin, Roberta Weber, Roger Carlsen & Dee Anna Willis
More Information on SITE
Table of Contents
In a virtual environment the student's evaluation becomes more complicated, how to determine the learning level of the student in a certain subject is the central topic of the present work. Intelligent tutoring systems divide the course in objectives, they have concepts, exercises and questionnaires that register the degree of understanding of the student in the student model and based on it personalizes the necessary feedback. However, due to its great adaptability to the student, the intelligent tutoring systems are bounded to their lack of adaptability to some learning management systems. Our proposal is a cognitive model of the student using the representation of neurofuzzy knowledge, for which a multiagents system is used, that carries out the storage of the measurements of the acquisition of student's knowledge in MOODLE. This system provides an updated diagnosis to the teacher and provides a customized feedback to the student before and after presenting his evaluation.
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- Usage Analysis in Learning Systems
- e-Learning platforms for Semantic Web
- Learning Objects in Context
- Introducing a framework-oriented approach to develop an intelligent tutoring system
- Computational Intelligence in Web-Based Education: A Tutorial
- Getting Ready For Mobile Learning—Adaptation Perspective
- A Framework for Developing Adaptive Personalized eLearning
- Artificial Agents in Distance Learning
- Modalities of Using Learning Objects for Intelligent Agents
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