Topic outline

  • Introduction

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    • The method requires participants to engage actively in the process of constructing, analyzing, and interpreting the Fuzzy Cognitive Map (FCM). This may involve tasks such as identifying the key components of the system under study, defining the relationships between these components, and assigning fuzzy values to represent the strength or direction of these relationships. Participants may also be expected to use the FCM to make predictions or test scenarios related to the system being modeled, and to interpret the results of these exercises.


  • Method

    • Fuzzy logic is a mathematical framework that allows for the representation of uncertain or imprecise information, and it has been used to model and control complex systems in various fields. It was introduced by Zadeh L.  in the 1960s and 1970s. Later in 1993, Kosko B., in its book entitled  "Fuzzy Thinking: The New Science of Fuzzy Logic" has popularized the concept of "fuzzy thinking" as a way of dealing with uncertainty and imprecision in decision-making and problem-solving. Therefore, through the FCM method, instructors can select a relevant topic, guide students to identify key components and causal relationships, assign fuzzy values to represent strength of the relationships, and analyze the FCM to make predictions or test scenarios related to the system being modeled. On the one hand, FCMs are a conceptual modeling tool that helps students to organize and synthesize their knowledge of a particular topic or system. By constructing an FCM, students are forced to think systematically about the key components and relationships in the system, and to identify the underlying causal mechanisms. In addition, the FCM approach incorporates fuzzy logic, which allows for uncertainty and imprecision in the representation of relationships between components of a system. This enables students to represent complex, real-world systems that are often characterized by non-linear and uncertain dynamics. On the other hand, the FCM approach emphasizes collaboration and teamwork, as students work together to identify the key components of the system, determine the relationships between them, and assign fuzzy values to the edges of the FCM. This encourages students to learn from each other, to share ideas and perspectives, and to develop their communication and teamwork skills. Additionally, the FCM approach is an active learning approach that engages students in a hands-on, experiential learning process, because by using FCMs to model and analyze real-world problems or scenarios, students can apply their knowledge in a meaningful way, and develop their critical thinking and problem-solving skills.


  • Experiences

    • Instructors may adopt the FCM in a classroom setting as follows:


       


      1)       Choose a topic: Select a topic that is relevant to the course content and can be modeled using an FCM. This could be a real-world problem or a hypothetical scenario that is related to the course objectives.


       


      2)       Define the components: Work with students to identify the key components of the system being modelled, and help them to define the attributes and characteristics of each component. This step may involve some brainstorming and group discussion.


       


      3)       Determine the causal relationships: Guide students to determine the causal relationships between the different components and represent them as directed edges in the FCM. Encourage students to think systematically and consider multiple perspectives.


       


      4)       Assign fuzzy values: Help students to assign fuzzy values to the edges of the FCM to represent the strength or direction of the causal relationships. This step may involve some research, data analysis, or expert opinions.


       


      5)       Analyze the FCM: Have students use the FCM to make predictions or test scenarios related to the system being modelled, and to interpret the results of these exercises. This step may involve some simulation, visualization, or data analysis tools.


       


      6)       Reflect on the learning outcomes: Assess the effectiveness of the FCM exercise in achieving the learning objectives and provide feedback to students on their performance and understanding of the topic. Encourage students to reflect on their learning process and to identify areas for improvement.


       


  • Additional resources

    • ●        Kosko B., Fuzzy thinking. Hyperion Press: New York; 1993.

      ●        Kosko B., Fuzzy cognitive maps. Int J Man-Mach Stud 1986;24:65]75

      ●        Gardner H., The unschooled mind: How children learn and how schools should teach. New York: Harper Collins; 1991.

      ●        Zadeh L., Fuzzy sets, Inf Contr 1965;8:338]353.

       

      ●        Fuzzy cognitive maps to conceptualize complex problems:

       

       


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