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Analysis of the Factors Influencing the Adaptability of College English Learning Based on Artificial Intelligence Teaching Assistance

Author

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  • Lingmei Cao
  • Shuxian Zhu
  • Lianhui Li

Abstract

Good learning adaptability is the key to ensure students’ learning quality. Learning maladjustment not only affects students’ learning effect but also affects the effectiveness of AI-enabled English learning. Although some studies have found that there is a certain degree of poor learning adaptability in the practice of artificial intelligence (AI) supporting English teaching, most studies only describe the phenomenon and do not further explore the causes of poor learning adaptability. Therefore, the research intends to understand the current situation of college students’ English learning adaptability under the support of AI through the investigation and analysis of college students’ English learning adaptability under the support of AI and clarifies the impact of various influencing factors on learning adaptability as well as the relationship between learning adaptability and various factors, and put forward strategies to improve students’ learning adaptability. This research is a new exploration of learning adaptability in the field of AI English learning. At the same time, it is also an extension of the research environment of learning adaptability in information-based learning and a supplement to the research results. This paper combs the composition structure of college students’ English learning adaptability under the support of AI and constructs the influencing factor model of college students’ English learning adaptability under the support of AI. The research has certain theoretical significance and practical value.

Suggested Citation

  • Lingmei Cao & Shuxian Zhu & Lianhui Li, 2022. "Analysis of the Factors Influencing the Adaptability of College English Learning Based on Artificial Intelligence Teaching Assistance," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-9, September.
  • Handle: RePEc:hin:jnlmpe:8543492
    DOI: 10.1155/2022/8543492
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