نوع مقاله : علمی پژوهشی(عادی)
نویسندگان
گروه زبان و ادبیات انگلیسی، دانشکده زبانها و ادبیات خارجی، دانشگاه تهران، تهران ، ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In response to the rapid evolution of Artificial Intelligence (AI) technologies in language education, this study aimed to develop an AI literacy model and elucidate its instructional implications among Iranian EFL learners. An exploratory mixed-methods design was employed; in the qualitative phase, data were extracted through semi-structured interviews and Grounded Theory analysis, while in the quantitative phase, the resulting model was tested on 200 language learners using factor analysis, Structural Equation Modeling (SEM), and fit indices via SPSS and Smart PLS software. Qualitative findings revealed one central category and six primary components: ‘Literacy and Awareness Levels,’ ‘The Role of Education and Media,’ ‘AI Functions,’ ‘Challenges and Constraints,’ ‘Benefits and Applications,’ and ‘Policy-making and Ethics,’ which were organized into 27 conceptual codes. Quantitative results indicated that these components accounted for 47.85% of the total variance of the construct. Furthermore, the structural model predicted 71.4% (R2 = 0.714) of the variance in AI literacy, which, coupled with a Goodness of Fit (GOF) index of 0.641, signifies a robust and satisfactory model fit. The findings suggest that while AI offers opportunities such as immediate feedback, personalized learning, and enhanced motivation, it also presents challenges including diminished human interaction, lack of cultural context comprehension, content inaccuracies, and cognitive dependency. Consequently, the implementation of formal AI literacy courses, ethics-based instruction, and the development of indigenous tools are essential for the safe and effective utilization of this technology. The proposed model provides a practical framework for policymakers and language educators.
کلیدواژهها [English]
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