Innovative research on english teaching model based on artificial intelligence and wireless communication

• Main Authors: Wang, Yuan, Na, Kew Si
• Format: Article
• Published: World Scientific 2022
• Subjects: P Philology. Linguistics
• Online Access: http://eprints.utm.my/id/eprint/101399/; http://dx.doi.org/10.1142/S0218539322400071

It is a network system for teaching English through a wireless communication (WC) premised distance teaching system. This is a process of education that is capable of encouraging students' concerns to acquire knowledge voluntarily. The paper is designed to develop and implement an online intelligent English training system using artificial intelligence (AI) that helps students improve their English learning efficiency in line with knowledge and personality. The system's numerous sensor nodes may create a variety of topologies. The gathered information is transmitted over the global system for mobile communication (GSM) network to the user interface. The operator can manage the remote sensor node via the GSM network. Nevertheless, there are certain derivative aspects such as the absence of verbal judgment, the actual evaluation and signaling system, the interactive educational platform teachers and learners need. The paper is based on the above issues. It contains a whole talk-based system where teachers, students, and English teaching can be revised together - AIWC (ET-AIWC) systems are designed to improve and advance the genetic algorithm based on an encoding technique for dynamic parameter adjustment of the iterative process based on these problems. In combination with an AI expert system, suitable learning techniques were created to enable students to double the learning effect by half the amount of work. An online teaching assistant system was designed to monitor, regulate, and engage with students throughout the learning process and a modified scoring system that provides real-time evaluation of student speakers to improve students' oral competence in English better and more efficiently, achieving 95.2%.