Generative AI in Student Essays: English Teachers' Perspectives on Effective Assessment Methods
Valentyna Lukianenko – Zoia Kornieva
DOI: 10.18355/XL.2024.17.04.14
Abstract
The increasing use of AI-assisted writing tools in education presents new challenges in ensuring the integrity and originality of student essays. This study investigates English teachers’ perceptions of various essay assessment methods in light of these challenges. Through a mixed-methods approach, combining quantitative Likert-scale data and qualitative open-ended responses, the research reflects the perspectives of 50 experienced educators from the Faculty of Linguistics at the National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute.” The study investigates teachers' familiarity with AI tools, the challenges they face in assessing AI-assisted student work, and their views on AI's role in aiding or potentially hindering student writing skills. Findings indicate that while many educators support AI for tasks like grammar and proofreading, concerns persist over its impact on students' critical thinking and originality. Assessment methods currently in use include in-class handwritten essays, oral defenses, AI-detection software, and portfolios. The results indicate that hybrid assessment methods are rated as the most effective for evaluating AI-influenced essays, indicating a preference for combining traditional and AI-specific techniques. Implications and recommendations for research and practice have been outlined, emphasizing a balanced approach that promotes ethical AI usage, critical thinking, and academic integrity in writing assessments.
Key words: AI in education, essay assessment methods, AI-assisted writing, academic integrity, hybrid assessment approaches, AI detection tools
Pages: 235-250
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