Decision Making by Rule-Based Fuzzy Cognitive Maps: An Approach to Implement Student-Centered Education
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 vers
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Decision Making by Rule-Based Fuzzy Cognitive Maps: An Approach to Implement Student-Centered Education A. Peña-Ayala and J. H. Sossa-Azuela
Abstract 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.
1 Introduction Our DMA is a cognitive computing approach that is inspired by the mental capabilities [12]. The DMA represents a decision-making framework to deal with uncertain and unreliable knowledge as a sample of cognitive reasoning [1].
A. Peña-Ayala (B) WOLNM, ESIME-Z, Instituto Politécnico Nacional, U. Prof. Adolfo López Mateos, s/n, GAM, Mexico, DF, México e-mail: [email protected] J. H. Sossa-Azuela CIC IPN, U. Prof. Adolfo López Mateos, s/n, Gustavo A. Madero, 07738 Mexico, DF, Mexico e-mail: [email protected] E. I. Papageorgiou (ed.), Fuzzy Cognitive Maps for Applied Sciences and Engineering, Intelligent Systems Reference Library 54, DOI: 10.1007/978-3-642-39739-4_6, © Springer-Verlag Berlin Heidelberg 2014
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A. Peña-Ayala and J. H. Sossa-Azuela
Causality, our awareness of what produces a specific consequence in the world and why it matters, is the conceptual baseline to predict and explain some effects given particular conditions [14]. Both, cause and effect, represent instances of common sense (i.e. it concerns the knowledge that every person assumes her/his neighbors also posses, and the kind of reasoning that people daily perform to induce causal results) [6]. In our approach, both knowledge and reasoning are qualitatively characterized and deployed for decision making (i.e., they are stated by natural language terms and sentences to acquire, depict and reveal the meaning that individuals provide in their world and their every day experiences) [7]. According to the prior context, our DMA is designed and built as an approach for decision-making applicable cross-domains, such as education. Its description is organized as follows: A profile of the application context is shaped in Sect. 2 and its framework is sketched in Sect. 3. The processes to model the user and the lectures are set in Sect. 4; whereas, the knowledge base
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