TY - GEN
T1 - Predictive causal approach for student modeling
AU - Peña, Alejandro
AU - Sossa, Humberto
AU - Gutierréz, Agustín
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=34547684286&partnerID=8YFLogxK
U2 - 10.1109/MICAI.2006.39
DO - 10.1109/MICAI.2006.39
M3 - Contribución a la conferencia
AN - SCOPUS:34547684286
SN - 0769527221
SN - 9780769527222
T3 - Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006
SP - 398
EP - 407
BT - Proceedings - Fifth Mexican International Conference on Artificial Intelligence, MICAI 2006
T2 - 5th Mexican International Conference on Artificial Intelligence, MICAI 2006
Y2 - 13 November 2006 through 17 November 2006
ER -