Exploring AI Literacy and Perception: Insights from Iranian EFL Researchers

The rapid integration of Artificial Intelligence (AI) into education has transformed teaching and research practices, particularly in the context of English as a Foreign Language (EFL). However, the effective adoption of AI in EFL research requires a deep understanding of AI literacy and stakeholder perceptions. This mixed-methods study investigates Iranian EFL researchers' AI literacy, perceptions of AI applications, and their implications for research and pedagogy. Quantitative data were collected through a validated AI Literacy Questionnaire administered to 112 participants, measuring nine dimensions of AI literacy, including technical skills, ethical considerations, and emotional regulation. Results revealed low AI literacy levels across all dimensions, with significant gaps in advanced skills like AI creation and ethical analysis. Cluster analysis identified three proficiency groups: high, moderate, and low, with the majority falling into the low proficiency category. Qualitative data from semi-structured interviews with 16 participants highlighted both positive and negative perceptions of AI in research. While participants acknowledged AI's potential for enhancing data analysis, time efficiency, and writing accuracy, concerns included ethical risks, data privacy issues, and overreliance on AI, which could stifle creativity and critical thinking. These findings underline the pressing need for targeted training programs and policy interventions to enhance AI literacy among Iranian EFL researchers, fostering responsible and effective AI integration in research and education.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2025-10-01
DOI
https://doi.org/10.30479/jmrels.2025.21412.2465
Primary Topic
Bacillus and Francisella bacterial research
Type
article
Field-Weighted Citation Impact
0.00
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article

Exploring AI Literacy and Perception: Insights from Iranian EFL Researchers

SHILAP Revista de lepidopterología
Bacillus and Francisella bacterial research
article

Exploring AI Literacy and Perception: Insights from Iranian EFL Researchers

article en

Abstract

The rapid integration of Artificial Intelligence (AI) into education has transformed teaching and research practices, particularly in the context of English as a Foreign Language (EFL). However, the effective adoption of AI in EFL research requires a deep understanding of AI literacy and stakeholder perceptions. This mixed-methods study investigates Iranian EFL researchers' AI literacy, perceptions of AI applications, and their implications for research and pedagogy. Quantitative data were collected through a validated AI Literacy Questionnaire administered to 112 participants, measuring nine dimensions of AI literacy, including technical skills, ethical considerations, and emotional regulation. Results revealed low AI literacy levels across all dimensions, with significant gaps in advanced skills like AI creation and ethical analysis. Cluster analysis identified three proficiency groups: high, moderate, and low, with the majority falling into the low proficiency category. Qualitative data from semi-structured interviews with 16 participants highlighted both positive and negative perceptions of AI in research. While participants acknowledged AI's potential for enhancing data analysis, time efficiency, and writing accuracy, concerns included ethical risks, data privacy issues, and overreliance on AI, which could stifle creativity and critical thinking. These findings underline the pressing need for targeted training programs and policy interventions to enhance AI literacy among Iranian EFL researchers, fostering responsible and effective AI integration in research and education.

SHILAP Revista de lepidopterología
Hakim Sabzevari University (IR)
Quality Education
Openalex Percentile: Top 59%
Bacillus and Francisella bacterial research
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Exploring AI Literacy and Perception: Insights from Iranian EFL Researchers · SHILAP Revista de lepidopterología (2025) | TGRS Research Map | TGRS