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MOTIVATION TO TEACH AND AI ANXIETY AMONG TESOL STUDENT-TEACHERS WITH DEGREE-YEAR AND GENDER DIFFERENCES
(1) Alanya Alaaddin Keykubat University, Turkey
(*) Corresponding Author
Abstract
Integrating Artificial Intelligence (AI) in language teaching may induce anxiety among educators. This quantitative study investigates the relationship between AI anxiety and teaching motivation among TESOL student-teachers, an area that remains under-researched. The participants were 146 student-teachers in a TESOL program with different degree-years and genders. Two questionnaires examined the relationship between two dependent variables, AI anxiety and motivation to teach, and two independent variables, degree-year and gender differences. The investigation of AI anxiety encompassed four factors: anxiety due to learning, job replacement, AI configuration, and sociotechnical blindness, while the motivation to teach two factors: intrinsic and extrinsic motivation. The analysis was conducted using Kruskal-Wallis, Mann-Whitney U, and correlational analysis, and the findings revealed moderate levels of AI anxiety and motivation to teach. A significant difference in “job replacement anxiety” and the degree-year indicated that student-teachers could have different levels of job replacement anxiety in different years. Female student-teachers had higher AI anxiety and motivation to teach than male candidates. The minor positive correlations (%7-8) between AI anxiety, particularly the sociotechnical blindness factor, and intrinsic motivation show that intrinsic motivation could determine the anxiety level; therefore, teacher educators could give particular attention to reducing the sociotechnical blindness.
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DOI: https://doi.org/10.24071/llt.v28i1.9166
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