TY - GEN
T1 - Teaching-learning by means of a fuzzy-causal user model
AU - Peña Ayala, Alejandro
PY - 2009
Y1 - 2009
N2 - In this research the teaching-learning phenomenon that occurs during an E-learning experience is tackled from a fuzzy-causal perspective. The approach is suitable for dealing with intangible objects of a domain, such as personality, that are stated as linguistic variables. In addition, the bias that teaching content exerts on the user's mind is sketched through causal relationships. Moreover, by means of fuzzy-causal inference, the user's apprenticeship is estimated prior to delivering a lecture. This supposition is taken into account to adapt the behavior of a Web-based education system (WBES). As a result of an experimental trial, volunteers that took options of lectures chosen by this user model (UM) achieved higher learning than participants who received lectures' options that were randomly selected. Such empirical evidence contributes to encourage researchers of the added value that a UM offers to adapt a WBES.
AB - In this research the teaching-learning phenomenon that occurs during an E-learning experience is tackled from a fuzzy-causal perspective. The approach is suitable for dealing with intangible objects of a domain, such as personality, that are stated as linguistic variables. In addition, the bias that teaching content exerts on the user's mind is sketched through causal relationships. Moreover, by means of fuzzy-causal inference, the user's apprenticeship is estimated prior to delivering a lecture. This supposition is taken into account to adapt the behavior of a Web-based education system (WBES). As a result of an experimental trial, volunteers that took options of lectures chosen by this user model (UM) achieved higher learning than participants who received lectures' options that were randomly selected. Such empirical evidence contributes to encourage researchers of the added value that a UM offers to adapt a WBES.
UR - http://www.scopus.com/inward/record.url?scp=70549108082&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-05258-3_46
DO - 10.1007/978-3-642-05258-3_46
M3 - Contribución a la conferencia
SN - 3642052576
SN - 9783642052576
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 521
EP - 532
BT - MICAI 2009
T2 - 8th Mexican International Conference on Artificial Intelligence, MICAI 2009
Y2 - 9 November 2009 through 13 November 2009
ER -