Supporting Adaptive English Learning With Fuzzy Logic-Based Personalized Learning

Serious play for learning has gained popularity in recent years. The research belongs to the opportunity to engage pupils in innovative ways to attract and hold their attention. The purpose of this research is to offer a novel interdisciplinary strategy to identify English language possibilities using complex games that integrates psychological analytic theory, fuzzy reasoning, and neural networks. The study began with a Delphi approach to collect comments from students based on a matrix of the usage of complex games to speak English. A fuzzy logic-based personalized English learning (FLPEL) system is suggested in this article. It creates a fuzzy linguistic identification method that includes four basic input variables (strong points, weak points, possibilities, and risks) recognized through the matrix. It indicates the outcome (studying potentials of the second language) by considering some dynamic input characteristics. The outcomes of the implementation were acquired using the Matlab tool and revealed trustworthy insights and discoveries.