Computational Intelligence Using Fuzzy Logic in Educational Data Analysis A Study of Methodologies and Applications

Résumé fourni par la source

In this exploratory research, the use of computational intelligence, more especially fuzzy sense, in the analysis of educational data is investigated. The paper also investigates colorful approaches and the practical applications of these methodologies. To improve tutoring and literacy challenges, educational institutions are increasingly resorting to data-driven techniques. This trend is expected to continue. The use of fuzzy sense, which is well-known for its capacity to manage queries and complexity, provides potentially useful tools for evaluating educational data. The purpose of this project is to investigate how fuzzy sense models can be utilized to reuse and interpret various educational data sets. These data sets include educational criteria for student achievement as well as learning gesture patterns. In the process of establishing meaningful perceptivity from educational data, comparative evaluations of various fuzzy sense approaches highlight both the benefits and limits of these methodologies. To demonstrate the efficacy of fuzzy sense in the process of developing educational decision-making procedures, case studies illustrate realistic executions across a variety of educational environments. The findings highlight the potential for computational intelligence, and more specifically fuzzy sense, to change the way educational data analysis is done by providing preceptors and stakeholders with additional nuanced and practical perceptivity.

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