Title :
Predictive Causal Approach for Student Modeling
Author :
Pena, Alejandro ; Sossa, Humberto ; Gutierréz, Agustín
Abstract :
This work proposes a Student Model (SM) oriented to predict causal effects that teaching and learning experiences produce on a student before their delivery. Our student modeling approach elicits concepts from domains that depict the educative program and the individual profile of the student, as content description and cognitive skills. The Cognitive Map sketches causal-effect relationships among the concepts involved by means of Fuzzy Rule Bases. Concepts and relations are fully described in an ontology. Based on the ontology, it is outcome a Cognitive Map for each option of teaching-learning experience. The analysis of the model depicted by the Cognitive Map is done through its activation. This process is a kind of simulation, which traces fuzzy causal inferences in order to estimate behaviors and final states for the concepts. The prediction of the causal results is achieved according to the interpretation of the evolution and final values of the concepts. So in Web-based Education Systems (WBES) that own several options for content, sequencing, and evaluation material, our student modeling offers a predictive support for student-centered education.
Keywords :
Artificial intelligence; Education; Engines; Fuzzy cognitive maps; Intelligent structures; Knowledge acquisition; Ontologies; Predictive models; Samarium; State estimation;
Conference_Titel :
Artificial Intelligence, 2006. MICAI '06. Fifth Mexican International Conference on
Conference_Location :
Mexico City, Mexico
Print_ISBN :
0-7695-2722-1
DOI :
10.1109/MICAI.2006.39