TY - JOUR
T1 - Decision making by rule-based fuzzy cognitive maps
T2 - An approach to implement student-centered education
AU - Peña-Ayala, A.
AU - Sossa-Azuela, J. H.
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2014.
PY - 2014
Y1 - 2014
N2 - In this chapter we outline a decisions-making approach (DMA) that is based on the representation and simulation of causal phenomena. It applies an extension of the traditional Fuzzy Cognitive Maps called Rules-based Fuzzy Cognitive Maps (RBFCM). This version depicts the qualitative flavor of the object to be modeled and is grounded on the well-sounded fuzzy logic. As a result of a case study in the educational field, we found empirical evidence of the RBFCM usefulness. Our DMA offers decision-making services to the sequencing module of an intelligent and adaptive web-based educational system (IAWBES). According to the studentcentered education paradigm, an IAWBES elicits learners’ traits to adapt lectures to enhance their apprenticeship. This RBFCM based DMA models the teachinglearning scenery, simulates the bias exerted by authored lectures on the student’s learning, and picks the lecture option that offers the highest achievement. The results reveal that the experimental group reached higher learning than the control group.
AB - In this chapter we outline a decisions-making approach (DMA) that is based on the representation and simulation of causal phenomena. It applies an extension of the traditional Fuzzy Cognitive Maps called Rules-based Fuzzy Cognitive Maps (RBFCM). This version depicts the qualitative flavor of the object to be modeled and is grounded on the well-sounded fuzzy logic. As a result of a case study in the educational field, we found empirical evidence of the RBFCM usefulness. Our DMA offers decision-making services to the sequencing module of an intelligent and adaptive web-based educational system (IAWBES). According to the studentcentered education paradigm, an IAWBES elicits learners’ traits to adapt lectures to enhance their apprenticeship. This RBFCM based DMA models the teachinglearning scenery, simulates the bias exerted by authored lectures on the student’s learning, and picks the lecture option that offers the highest achievement. The results reveal that the experimental group reached higher learning than the control group.
UR - http://www.scopus.com/inward/record.url?scp=84927551169&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-39739-4_6
DO - 10.1007/978-3-642-39739-4_6
M3 - Artículo
AN - SCOPUS:84927551169
SN - 1868-4394
VL - 54
SP - 107
EP - 120
JO - Intelligent Systems Reference Library
JF - Intelligent Systems Reference Library
ER -