Predictive causal approach for student modeling

Alejandro Peña, Humberto Sossa, Agustín Gutierréz

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaProceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006
Páginas398-407
Número de páginas10
DOI
EstadoPublicada - 2006
Evento5th Mexican International Conference on Artificial Intelligence, MICAI 2006 - Apizaco, México
Duración: 13 nov. 200617 nov. 2006

Serie de la publicación

NombreProceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006

Conferencia

Conferencia5th Mexican International Conference on Artificial Intelligence, MICAI 2006
País/TerritorioMéxico
CiudadApizaco
Período13/11/0617/11/06

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