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Examining Argument Elements and Logical Fallacies of English Education Students in Oral Discussion Selamat Husni Hasibuan; Y Yusriati; Imelda Darmayanti Manurung
Tell : Teaching of English Language and Literature Journal Vol 8 No 2 (2020): September
Publisher : English Department FKIP Universitas Muhammadiyah Surabaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/tell.v8i2.5771

Abstract

This study aims to report on the argument elements and logical fallacies performed by English education students. This study is framed within a descriptive qualitative study in that it interprets the ways students of English education deliver their arguments. The data were collected through observation, recording and in-depth interviews on the objects studied. The findings of this study showed that the students’ ability to present logical arguments varies with the dominant label in the “non-standard argument” category. In regard to the logical fallacy, hasty generalization becomes the most general logical fallacy found in students’ arguments, followed by the appeal to pity, the appeal to fear, the questionable statistics, the slippery slope, the appeal to the bandwagon, the circular reasoning, the pointing to another wrong, and the personal attack. Based on the interview, lack of understanding of arguments and logical fallacies, limited vocabularies, as well as nervousness are identified as the possible causes of these phenomenons. Finally, it is suggested that students should be given exposures on how to structurize the logical arguments and avoid logical fallacies.
Artificial intelligence-driven innovation in English language education: a thematic literature review and conceptual framework for Indonesian EFL context Imelda Darmayanti Manurung; Faisal Rahman Dongoran; Tengku Winona Emelia; Lia Khalisa
Indonesian Journal Education Vol. 5 No. 2 (2026): Indonesian Journal Education (IJE)
Publisher : Lembaga Riset Mutiara Akbar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56495/ije.v5i2.1662

Abstract

The use of Artificial Intelligence (AI) in English as a Foreign Language (EFL) education has expanded rapidly, transforming learning, assessment, teacher professional development, and educational governance. However, existing studies predominantly examine these dimensions independently, leaving a lack of an integrated conceptual framework to explain AI implementation as a comprehensive educational ecosystem. This study aims to synthesize recent research on AI in EFL education, identify emerging themes, and propose the AI-Integrated EFL Innovation Framework (AIEIF). A Thematic Literature Review was conducted on twelve peer-reviewed international articles published between 2024 and 2025. Data were analyzed through open coding, category development, and thematic synthesis to identify recurring conceptual patterns across studies. The analysis generated five interrelated themes: AI-Supported Student Learning, AI for Teacher Professional Development, AI-Based Assessment Innovation, AI Leadership and Educational Governance, and Challenges and Future Directions. The findings indicate that effective AI implementation depends on the integration of adaptive learning, teacher capacity building, data-driven assessment, institutional leadership, and governance while addressing ethical, technological, policy, and cultural considerations. The proposed AIEIF offers a human-centered conceptual framework that advances AI integration in EFL education and provides a foundation for future empirical research, educational policy, and sustainable AI implementation, particularly in the Indonesian context.