Work

Comparing AI-Assisted and Traditional Teaching in College English: Pedagogical Benefits and Learning Behaviors

Year: 2025

Type: article

Abstract: In the era of artificial intelligence, higher education is embracing new opportunities for pedagogical innovation. This study investigates the impact of integrating AI into college English teaching, focusing on its role in enhancing students’ critical thinking and academic engagement. A controlled experiment compared AI-assisted instruction with traditional teaching, revealing that AI-supported learning improved overall English proficiency, especially in writing skills and among lower- and intermediate-level learners. Behavioral analysis showed that the quality of AI interaction—such as meaningful feedback adoption and autonomous revision—was more influential than mere usage frequency. Student feedback further suggested that AI-enhanced teaching stimulated motivation and self-efficacy while also raising concerns about potential overreliance and shallow engagement. These findings highlight both the promise and the limitations of AI in language education, underscoring the importance of teacher facilitation and thoughtful design of human–AI interaction to support deep and sustainable learning.

Source: Information

DOI: 10.3390/info16100895

Authors: Changyi Li, Jiang Long

Institutions: Harbin University of Science and Technology, Jilin University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $1,930