Adaptive Wireless Network Model with Reinforcement Learning for Language Proficiency Development

This study gives a new way to learn English, showing its importance in today's globalized world. The study recognizes how difficult it is to learn a language. It offers a new way to use wireless networks to create a flexible and adaptable learning environment by combining the latest developments in Reinforcement Learning (RL) algorithms with ideas from the field of education. This method produces a personalized learning path by thoroughly testing students' reading, listening, and observation skills. An application using the suggested method was carefully built by fifty people, who used RL techniques to check students' progress and identify their strengths. The model's fantastic success is shown by the fact that it passes 96% of tests and is accurate 95% of the time.479 Cross-linguistic skills include analytical thinking, good communication, and standard language skills that the system aims to improve. Students worldwide can benefit from this method, which combines cutting-edge technology with traditional teaching methods to create a personalized and adaptable learning environment that helps students succeed in today's changing educational environment.

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