Artificial Intelligence-Based English Self-Learning Effect Evaluation and Adaptive Influencing Factors Analysis
Xing Shu, Chengjun Xu
Abstract
Under the background of continuous development in our country, traditional English education can no longer meet the needs of modern times. Through the evaluation of English autonomous learning effect of artificial intelligence and the analysis of the influencing factors of adaptability, the teaching effect of English class is improved and the students’ awareness of autonomous learning is cultivated. In the pilot study, students now have an overall level of adaptation (3 < M < 4) supported by English proficiency. That is, the standard deviation is 1. The overall level of self-study in English is higher than that of boys (M = 3.40 for females, M = 3.32 for males, and M = 3.32 for males). Compared with non-English majors, English majors are more suitable for self-study of artificial intelligence in English (M = 3.59 for English majors), (M = 3.36 for non-English majors), and students can improve their adaptive ability to learn AI by creating models. Transfer learning is the key to improving learners’ English proficiency, and adaptive learning is the key to achieving this goal. Self-adaptive learning ensures the quality of students’ autonomous English homework. Improper English learning not only affects students’ learning outcomes but also affects their ability to learn English.