Original Research
Rethinking Assessment Practices in English Language Teaching in the Age of Generative Artificial Intelligence
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The introduction of Generative Artificial Intelligence (GenAI) has raised several issues in English teaching and assessment such as authorship, academic honesty, and pedagogical appropriateness. Although these tools can be used for feedback, task design, and support, their integration may also result in a number of ethical and instructional challenges. In this sense, this study focuses on how in-service English teachers in Türkiye recognize and respond to GenAI in the context of language assessment. In the study, four frameworks, Teacher Cognition, Language Assessment Literacy, Technological Pedagogical Content Knowledge (TPACK), and Critical Pedagogy, were employed to investigate beliefs, attitudes, and experiences of the participants. Sixteen in-service teachers from different contexts took part in semi-structured interviews. The analysis identified four themes: ethical reasoning and teacher agency, changing conceptions of assessment literacy, technological competence and institutional uncertainty, and equity issues regarding access and student readiness. While participants reported that they used GenAI tools, they also raised some concerns. The participants also stressed lack of clear institutional guidance and training. In addition, the participants reported that they developed alternative assessment practices to reduce AI misuse. This study reveals a teacher-centered, theoretically grounded description of GenAI integration in under-researched educational settings.
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Keywords
Generative Artificial Intelligence; Language Assessment; Teacher Cognition; Critical Pedagogy; Technological Pedagogical Content Knowledge
Author(s) Information
Publisher’s Note
The claims, arguments, and counter-arguments made in this article are exclusively those of the contributing authors. Hence, they do not necessarily represent the viewpoints of the authors’ affiliated institutions, or EUROKD as the publisher, the editors and the reviewers of the article.
Acknowledgements
Not applicable.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
CRediT Authorship Contribution Statement
Hossein Vafadar: Conceptualization, Writing – Review & Editing, Supervision
Batuhan Selvi: Conceptualization, Methodology, Formal Analysis, Writing – Original Draft
Ferzan Atay: Conceptualization, Resources, Writing – Original Draft
Generative AI Use Disclosure Statement
During the revision and preparation of this manuscript, the authors used Claude to improve readability. All content and intellectual contributions were generated by the authors. No generative AI tools were used for data analysis, interpretation, or autonomous content creation. The authors bear full responsibility for the integrity and accuracy of the final manuscript.
Ethics Declarations
World Medical Association (WMA) Declaration of Helsinki–Ethical Principles for Medical Research Involving Human Participants
This study was conducted in accordance with the Declaration of Helsinki and approved by Yozgat Bozok University Social and Human Sciences Ethics Committee. All participation was voluntary, and written informed consent was obtained from all participants prior to data collection. Participants were informed about the study's purpose, procedures, and their right to withdraw at any time without consequences.
Competing Interests
The author(s) declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article.
Data Availability
The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.