OPPORTUNITIES AND CHALLENGES IN AI-ASSISTED LANGUAGE TEACHING: PERCEPTIONS OF PRE-SERVICE EFL TEACHERS

Yıl 2024, , 74 - 83, 19.12.2024

Samet Taşçı , Mehmet Tunaz

https://doi.org/10.47214/adeder.1575897

Öz

The integration of Artificial Intelligence (AI) into foreign language education has transformed how languages are taught and learned, offering adaptive and personalized learning experiences. This study explores the perceptions of pre-service teachers regarding AI applications in language teaching, aiming to identify both the advantages and challenges these technologies present in educational contexts. Using a qualitative research methodology, semi-structured interviews were conducted with 17 pre-service English language teachers, who provided insights into their experiences with AI tools like ChatGPT, Google Assistant, and Grammarly. The findings revealed four primary themes: frequency of AI usage, positive impacts, negative impacts, and applications in language teaching. Pre-service teachers highlighted time-saving, convenience, and enhanced access to information as significant benefits of AI, while expressing concerns over issues like job displacement, dependency on technology, and data privacy. Additionally, participants acknowledged the potential of AI to support individualized learning but raised concerns about equity in access and the risk of reduced critical thinking skills. This study contributes to the growing literature on AI in education, offering insights to inform teacher education programs and educational policies to foster effective and ethical AI integration in language classrooms.

Anahtar Kelimeler

Artificial Intelligence, foreign language education, personalized learning, teacher education.

YAPAY ZEKA DESTEKLİ DİL ÖĞRETİMİNDE FIRSATLAR VE ZORLUKLAR: YABANCI DİL ÖĞRETMEN ADAYLARININ ALGILARI

Öz

Yapay zekânın yabancı dil eğitimine entegrasyonu, dil öğretimi ve öğrenimini dönüştürerek uyarlanabilir ve kişiselleştirilmiş öğrenme deneyimleri sunmaktadır. Bu çalışma, öğretmen adaylarının dil öğretiminde yapay zekâ uygulamalarına ilişkin algılarını inceleyerek bu teknolojilerin eğitim bağlamlarında sunduğu avantajları ve zorlukları belirlemeyi amaçlamaktadır. Nitel araştırma yönteminin kullanıldığı çalışmada, 17 öğretmen adayı ile yarı yapılandırılmış görüşmeler gerçekleştirilmiştir. ChatGPT, Google Asistan ve Grammarly gibi yapay zekâ araçlarıyla ilgili deneyimlerini paylaşan katılımcılar, yapay zekâ kullanım sıklığı, olumlu etkiler, olumsuz etkiler ve dil öğretiminde kullanım alanları olmak üzere dört ana tema ortaya koymuştur. Öğretmen adayları, yapay zekânın zaman kazandırma, pratiklik ve bilgiye kolay erişim gibi faydalarını vurgularken; iş kaybı, teknolojiye bağımlılık ve veri gizliliği gibi konularda endişelerini dile getirmişlerdir. Katılımcılar ayrıca yapay zekânın bireyselleştirilmiş öğrenmeyi destekleme potansiyelini kabul etmiş ancak erişim eşitsizliği ve eleştirel düşünme becerilerinin azalması riskleri konusunda endişelerini belirtmişlerdir. Bu çalışma, dil sınıflarında etkili ve etik yapay zekâ entegrasyonunu desteklemek için öğretmen eğitimi programları ve eğitim politikalarına rehberlik edecek şekilde eğitimde yapay zekâ üzerine literatüre katkı sağlamaktadır.

Anahtar Kelimeler

Yapay zekâ, yabancı dil eğitimi, kişiselleştirilmiş öğrenme, öğretmen eğitimi

Kaynakça

• Anis, M. (2023). Leveraging Artificial Intelligence for Inclusive English Language Teaching: Strategies and Implications for Learner Diversity. Journal of Multidisciplinary Educational Research, 12(6), 54-70.
• Beaunoyer, E., Dupéré, S., & Guitton, M. J. (2020). COVID-19 and digital inequalities: Reciprocal impacts and mitigation strategies. Computers in Human Behavior, 111, 106424. https://doi.org/10.1016/j.chb.2020.106424
• Bengtsson, M. (2016). How to plan and perform a qualitative study using content analysis. NursingPlus open, 2, 8-14. https://doi.org/10.1016/j.npls.2016.01.001
• Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16-24. https://doi.org/10.1016/j.procs.2018.08.233
• Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. Ieee Access, 8, 75264-75278. https://doi.org/10.1109/ACCESS.2020.2988510
• Cheng, L., Varshney, K. R., & Liu, H. (2021). Socially responsible ai algorithms: Issues, purposes, and challenges. Journal of Artificial Intelligence Research, 71(1), 1137-1181. https://doi.org/10.1613/jair.1.12814
• Dizon, G. & Gayed, J. M. (2021). Examining the impact of Grammarly on the quality of mobile L2 writing. JALT CALL Journal, 17(2), 74–92. https://doi.org/10.29140/jaltcall.v17n2.336
• Edmett, A., Ichaporia, N., Crompton, H., & Crichton, R. (2023). Artificial intelligence and English language teaching: Preparing for the future. London: British Council. https://doi.org/10.57884/78ea-3c69
• Gocen, A., & Aydemir, F. (2020). Artificial intelligence in education and schools. Research on Education and Media, 12(1), 13-21. https://doi.org/10.2478/rem-2020-0003
• 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
• Kahraman, H. T., Sagiroglu, S., & Colak, I. (2010). Development of adaptive and intelligent web-based educational systems. In 2010 4th international conference on application of information and communication technologies (pp. 1-5). IEEE.
• Korkmaz, H., & Akbıyık, M. (2024). Unlocking the potential: Attitudes of tertiary level EFL learners towards using AI in language learning. Participatory Educational Research, 11(6), 1-19. https://doi.org/10.17275/per.24.76.11.6
• Luan, H., Geczy, P., Lai, H., Gobert, J., Yang, S. J., Ogata, H., ... & Tsai, C. C. (2020). Challenges and future directions of big data and artificial intelligence in education. Frontiers in Psychology, 11, 580820. https://doi.org/10.3389/fpsyg.2020.580820
• Nazari, N., Shabbir, M. S. & Setiawan, R. (2021). Application of artificial intelligence powered digital writing assistance in higher education: Randomized controlled trial. Heliyon, 7(5), e07014. https://doi.org/10.1016/j.heliyon.2021.e07014
• Pokrivcakova, S. (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. Journal of Language and Cultural Education, 7(3), 135-153. https://doi.org/10.2478/jolace-2019-0025
• Sadiku, M. N., Musa, S. M., & Chukwu, U. C. (2022). Artificial intelligence in education. iUniverse.
• Saldaña, J. (2016). The coding manual for qualitative researchers. Sage Publications.
• Schulz, R. A. (2007). The challenge of assessing cultural understanding in the context of foreign language instruction. Foreign language annals, 40(1), 9-26. https://doi.org/10.1111/j.1944-9720.2007.tb02851.x
• Sharma, R. C., Kawachi, P., & Bozkurt, A. (2019). The landscape of artificial intelligence in open, online and distance education: Promises and concerns. Asian Journal of Distance Education, 14(2), 1-2.
• Tao, B., Díaz, V., & Guerra, Y. (2019). Artificial intelligence and education, challenges and disadvantages for the teacher. Arctic Journal, 72(12), 30-50.
• Tsai, Y. S., & Gasevic, D. (2017). Learning analytics in higher education---challenges and policies: a review of eight learning analytics policies. In Proceedings of the seventh international learning analytics & knowledge conference (pp. 233-242).
• Tucker, C. (2019). Privacy, algorithms, and artificial intelligence. In A. Agrawal, J. Gans, A. Goldfarb (Eds.), The economics of artificial intelligence (pp. 423‐437). University of Chicago Press. https://doi.org/10.7208/9780226613475