Introduction: One of the main concerns and issues for educators, particularly for engineering students, has been the caliber of mathematics instruction and learning. There are many different concepts and skills that make up mathematics. The improvement of problem-solving skills is one of mathematics' key functions. Numerous colleges struggle with the issue of students quitting because of mathematics because it is frequently thought of as a topic that students find difficult to master. Objectives: The study's goal is to examine the reasons why engineering students struggle with math. In this research, using fuzzy cognitive map techniques (FCM), we analyze the challenges engineering students encounter when trying to earn grades in math-related courses. FCM is a blend of some fuzzy logic and neural network ideas. FCM is made up of collections of concepts and all the different causal relationships that connect them. Methods: We created a model of the issues and causal relationships that engineering students faced when trying to succeed in mathematics classes. Both statically and dynamically, utilizing concepts from graph theory and simulations, the model is examined. Also we applied DEMATEL one of the Multi Criteria Decision Making method. Results: The analysis reveals that the main issue is not just the students' lack of mathematical background knowledge, but also their attitude toward learning, psychological response to the first failure, and lack of effort to complete additional tasks or attend tutorials. Conclusions: Using the FCM method, a model was created for the case of problems faced by engineering college students in scoring marks in mathematical related subjects based on the opinion of a domain expert. The model was first examined statically. The model was then simulated in a dynamic and it was predicted that there should be an attitude change in teachers and as well as students. Through the above static and dynamic studies of the FCM model was identified as important and useful decision support system, since it capable to provide support to decision makers, by making predictions on various scenarios that are imposed on the FCM model.
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