Design of online intelligent English teaching platform based on artificial intelligence techniques

TLDR

Artificial intelligence education (AIEd) uses AI in teaching, and many AIEd‑driven applications are already deployed in schools and universities. The study aims to develop a deep‑learning‑assisted online English teaching platform that combines AI modules and knowledge recommendation to enhance students’ language learning efficiency. The platform employs decision‑tree algorithms and neural networks to build an assessment model, investigates links between evaluation outcomes and factors, and integrates AI modules with knowledge recommendation. The system generates valuable data, improves teachers’ instructional quality and students’ English scores, demonstrates higher learning efficiency and relevance, and offers a reference model for similar methods.

Abstract

Abstract Artificial intelligence education (AIEd) is defined in the field of education as the utilization of artificial intelligence. There are currently many AIEd‐driven applications in schools and universities. This paper applies an artificial intelligence module combined with the knowledge recommendation to the system and develops an online English teaching system in comparison with the common teaching auxiliary system. The method of English teaching is useful in investigating the potential internal connections between evaluation outcomes and various factors. This article develops deep learning‐assisted online intelligent English teaching system that utilizes to create a modern tool platform to help students improve their English language teaching efficiency in line with their mastery of knowledge and personality. The decision tree algorithm and neural networks have been used and to generate an English teaching assessment implementation model based on decision tree technologies. It provides valuable data from extensive information, summarizes rules and data, and helps teachers to improve their education and the English scores of students. This system reflects the thinking of the artificial intelligence expert system. Test application demonstrates that the system can help students improve their learning efficiency and will make learning content more relevant. Besides, the system provides an example model with similar methods and has a referential definition.