Yabancı dil olarak İngilizce öğrenenlerin yapay zekaya yönelik tutumlarının araştırılması: Faydaları, riskleri ve dil öğreniminde kullanımı

Öz

Eğitim ortamları, yapay zekâ (YZ) nedeniyle sürekli olarak gelişmekte ve hem öğretmenler hem de öğrenciler için yeni fırsatlar sunmaktadır. Bu çalışmanın odak noktası, Yabancı Diller Yüksekokulu'ndaki yabancı dil olarak İngilizce öğrencilerinin yapay zekâya yönelik tutumlarını araştırmaktır. Öğrencilerin yapay zekâ ile ilgili görüşlerine kapsamlı bir genel bakış sağlamak için, keşfedici sıralı karma yöntem yaklaşımının bir parçası olarak yapılandırılmış bir anket ve yarı yapılandırılmış görüşmeler kullanılmıştır. Katılımcıları seçmek için uygun örnekleme yöntemi benimsenmiştir (N = 134). Nicel bulgulara göre, öğrenciler çoğunlukla YZ'nin olası faydalarına katılma veya kesinlikle katılma konusunda olumlu görüşlere sahip olmanın yanı sıra, özelliklerini yenilikçi ve eğitim ortamlarında kullanmaya açıktır. Bu arada, çok sayıda katılımcı, insan iletişiminin azalması ve YZ'nin insan rollerini devralması gibi YZ'den kaynaklanan risklerle ilgili endişelerini dile getirmiştir. Bu karşıt tutumlar, öğrencilerin yapay zekâyı kullanma konusunda hevesli olduklarını, ancak sonuçları konusunda da tereddütlü olduklarını gösteren karmaşık bir bakış açısını ortaya koymuştur. Bu sonuçlar, öğrencilerin YZ'nin pratikliğine ve yaratıcı fırsatlarına değer vermelerine rağmen, etik ve bağımlılıkla ilgili konularda da endişeli olduklarını gösteren nitel verilerle de desteklenmiştir. Sonuçlar, YZ araçlarının dil öğretimine dikkatli ve etik bir şekilde entegre edilmesinin gerekli olduğunu göstermektedir. Öğrencileri YZ'yi etik bir şekilde kullanmaya ve dil öğrenme deneyimlerini geliştirmeye hazırlamak için, hem eğitimcilerin hem de uygulayıcıların dijital yeniliği teşvik etmek ve eleştirel farkındalık arasında bir denge kurmaları gerekmektedir.

Anahtar Kelimeler

• Yapay zeka
• İngilizce öğrenenler
• tutumlar
• karma yöntem araştırması

Exploring EFL learners' attitudes towards artificial intelligence: Benefits, risks and use in language learning

Abstract

Educational landscapes are continuously evolving due to artificial intelligence (AI), offering new opportunities for both teachers and students. The focus of this study is to explore the attitudes of English as a foreign language (EFL) learners at the School of Foreign Languages towards artificial intelligence. To provide an extensive overview of the students' views regarding AI, a structured survey and semi-structured interviews were employed as part of an exploratory sequential mixed-methods approach. Convenient sampling was adopted to select participants (N = 134). According to the quantitative findings, students mostly had positive views on agreeing or strongly agreeing with the possible benefits of AI, as well as being open to using its features in innovative and educational settings. Meanwhile, a significant number of participants expressed their concerns about risks arising from AI, including reduced human contact and AI taking over human roles. These contradictory attitudes revealed a complex perspective, showing that students were enthusiastic about using AI, but also hesitant about the consequences. These results were further supported by qualitative data demonstrating that although students valued the practicality and creative opportunities of AI, they were also worried about ethical and addiction related issues. The results imply that a careful and ethical integration of AI tools into language instruction is necessary. In order to prepare learners to use AI ethically and enhance their language learning experiences, both educators and practitioners need to foster a balance between promoting digital innovation and critical awareness.

Keywords

• Artificial intelligence
• EFL learners
• attitudes
• mixed-methods research

References

1. Aktay, S., Gok, S., & Yildirim, A. (2024). Artificial intelligence attitude scale. International technology and education journal, 8(2), 14-24.
2. BERA. (2018). Ethical guidelines for educational research (4th ed.). British Educational Research Association. https://www.bera.ac.uk/publication/ethical-guidelines-for-educational-research-2018 .
3. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa .
4. Chiu, T. K., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments, 31, 1-17. https://doi.org/10.1080/10494820.2023.2172044 .
5. Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
6. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information System Quarterly, 13(3), 983–1003. https://doi.org/10.2307/249008 .
7. Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5, 1-4. https://doi.org/10.11648/j.ajtas.20160501.11 .
8. Fathali, S., & Okada, T. (2017). A self-determination theory approach to technology-enhanced out-of-class language learning intention: A case of Japanese EFL learners. International Journal of Research Studies in Language Learning, 6(4), 53-64.

9. Grassini, S. (2023). Shaping the future of education: exploring the potential and consequences of AI and ChatGPT in educational settings. Education Sciences, 13(7), 692.
10. Hockly, N. (2023). Artificial intelligence in English language teaching: The good, the bad and the ugly. RELC Journal, 54(2),445-451. https://doi.org/10.1177/00336882231168504 .
11. Holmes, W., Persson, J., Chounta, I.-A., Wasson, B., & Dimitrova, V. (with Europarat). (2022). Artificial intelligence and education: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe.
12. Lin, H. C., Ho, C. F., & Yang, H. (2022). Understanding adoption of artificial intelligence-enabled language e-learning system: An empirical study of UTAUT model. International Journal of Mobile Learning and Organisation, 16(1), 74-94.
13. Liu, G., & Ma, C. (2023). Measuring EFL learners’ use of ChatGPT in informal digital learning of English based on the technology acceptance model. Innovation in Language Learning and Teaching, 1-14.
14. Masgoret, A. M., & Gardner, R. C. (2003). Attitudes, motivation, and second language learning: Meta-analyses of studies by Gardner and associates. Language Learning, 53, 123–163.
15. Phan, T. N. L. (2023). Students' perceptions of the AI technology application in English writing classes. Proceedings of the AsiaCALL International Conference, 4, 45-62. https://doi.org/10.54855/paic.2344 .
16. Sindermann, C., Sha, P., Zhou, M., Wernicke, J., Schmitt, H. S., Li, M., ... & Montag, C. (2021). Assessing the attitude towards artificial intelligence: Introduction of a short measure in German, Chinese, and English language. KI-Künstliche İntelligenz, 35, 109-118.
17. Suh, W., & Ahn, S. (2022). Development and validation of a scale measuring student attitudes toward artificial intelligence. Sage Open, 12(2), https://doi.org/10.1177/21582440221100463 .
18. Tafazoli, D., Gómez Parra, M. E., & Huertas Abril, C. A. (2019). Attitude towards Computer-Assisted Language Learning: Do gender, age and educational level matter? Teaching English with Technology, 19(3), 22-39.
19. Wang, F., King, R. B., Chai, C. S., & Zhou, Y. (2023). University students’ intentions to learn artificial intelligence: the roles of supportive environments and expectancy–value beliefs. International Journal of Educational Technology in Higher Education, 20(1), 51. https://doi.org/10.1186/s41239-023-00417-2 .
20. Yeh, S. C., Wu, A. W., Yu, H. C., Wu, H. C., Kuo, Y. P., & Chen, P. X. (2021). Public perception of artificial intelligence and its connections to the Sustainable Development Goals. Sustainability, 13(16), 9165. https://doi.org/10.3390/su13169165 .
21. Yilmaz, H., Maxutov, S., Baitekov, A., & Balta, N. (2023). Student attitudes towards ChatGPT: A Technology Acceptance Model survey. International Educational Review, 1(1), 57-83. https://doi.org/10.58693/ier.114.
22. Yılmaz Virlan, A., & Tomak, B. (2025). A Q method study on Turkish EFL learners’ perspectives on the use of AI tools for writing: Benefits, concerns, and ethics. Language Teaching Research, 0(0). https://doi.org/10.1177/13621688241308836
23. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – Where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 39. https://doi.org/10.1186/s41239-019-0171-0 .
24. Zou, B., Liviero, S., Hao, M., Wei, C. (2020). Artificial Intelligence Technology for EAP Speaking Skills: Student Perceptions of Opportunities and Challenges. In: Freiermuth, M.R., Zarrinabadi, N. (eds) Technology and the Psychology of Second Language Learners and Users. New Language Learning and Teaching Environments. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-34212-8_17 .