Utilizing Machine Learning and a Multi-Modal Teaching Approach for Reforming University English Education

Machine learning encompasses perception, understanding, and application of knowledge. Traditional English teaching struggles to meet modern demands, prompting universities to innovate. This research explored the multimodal concept and proposed a new approach for university-level English instruction, an ensemble multimodal adaptive boosting-based teaching model. Through simulation studies, the ensemble multimodal adaptive boosting-based teaching model was developed and tested in two classrooms via a grammar proficiency post-test. Results showed that the study group significantly outperformed the control group, demonstrating enhanced English grammar abilities. This innovative teaching method not only boosted students' performance but also improved interaction between students and educators, highlighting its effectiveness in enhancing English education.