the profile of english education students’ ai literacy: A case study at english education Department at State Islamic University in West Java

Mardhiyah, Shofia (2025) the profile of english education students’ ai literacy: A case study at english education Department at State Islamic University in West Java. Sarjana thesis, UIN Sunan Gunung Djati Bandung.

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Abstract

The rapid advancement of artificial intelligence (AI) has transformed learning practices in higher education, including English Language Teaching (ELT). As AI tools become increasingly embedded in academic tasks, students’ ability to understand, evaluate, and use these technologies ethically and responsibly has become essential. This study aims (1) to assess the current level of AI literacy among English Education students in ELT classrooms and (2) to identify the challenges they encounter in understanding and ethically utilizing AI tools. The study was conducted at an Islamic State University in Java, where an AI-focused course has been integrated into the curriculum. This research employed a qualitative research design with a case study approach, beginning with a questionnaire adapted from the Meta AI Literacy Scale (MAILS) by Carolus et al. (2023), which measures four dimensions: AI Literacy, Create AI, AI Self-Efficacy, and AI Self-Competency. The questionnaire was administered to 68 English Education students who had prior exposure to AI through the AI for Education course. Based on mean-score patterns, three participants representing the highest, middle, and lowest of the score that students get were selected for semi-structured interviews. The interview data were analyzed thematically to examine students’ ethical and practical challenges in using AI tools. The findings indicate that English Education students demonstrate an overall High level of AI literacy, driven primarily by strong operational competence in using widely accessible generative AI tools for academic tasks. However, this proficiency is uneven across literacy dimensions. While students perform well in using and applying AI, they exhibit limited conceptual understanding of how AI systems function, difficulty in detecting AI-generated content and embedded automation, and weak capacity to critically evaluate the reliability, bias, and limitations of AI outputs. Although ethical awareness and AI self-efficacy are generally present, they remain largely procedural and context-dependent, with minimal engagement in deeper ethical reasoning related to transparency, data ownership, and the risks of overreliance on AI tools. Interview data further revealed persistent challenges in formulating effective prompts, verifying output accuracy beyond surface plausibility, managing data privacy when using public AI platforms, and regulating dependence on AI assistance, particularly under academic pressure. Overall, the results suggest that although students are confident and capable AI users, their critical and ethical AI competencies remain underdeveloped. These findings highlight the need for structured AI literacy instruction in ELT that explicitly addresses evaluation, ethical reasoning, and responsible AI use to better prepare students for AI-integrated academic and professional environments.

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