Öğretmen adaylarının yapay zekaya (YZ) ilişkin metafor algıları

Yıl 2024, Cilt: 7 Sayı: 2, 607 - 630, 30.11.2024

Barış Eriçok , Fatih Karataş , Erkan Yüce

https://doi.org/10.33400/kuje.1511500

Öz

Bu araştırma, öğretmen adaylarının yapay zekâya (YZ) yönelik metafor algılarını incelemektedir. Nitel yöntem ve fenomenoloji deseni kullanılarak yapılan çalışmaya, amaçlı ve kolayda örnekleme yöntemleriyle seçilen 285 öğretmen adayı katılmıştır. Veriler, 2023-2024 akademik yılı bahar döneminde çevrimiçi bir anket aracılığıyla toplanmıştır. İçerik analizi ve beş adımlı veri analizi yöntemleri eşzamanlı olarak uygulanmış; dış uzman değerlendirmesi ve akran değerlendirmesi stratejileriyle çalışmanın inandırıcılığı arttırılmıştır. Araştırma sonuçları, öğretmen adaylarının yapay zekayı, bilgiye hızlı ve kolay erişim sağlayan, öğretme ve öğrenme süreçlerine rehberlik eden destekleyici ve güçlü bir araç olarak algıladığını göstermektedir. Ancak yapay zekânın karmaşıklığı ve çok yönlülüğü, hem potansiyel faydalarını hem de zorluklarını beraberinde getirmektedir. Eğitimde yapay zekâ, öğretmen adayları tarafından yenilikçi ve değerli bir kaynak olarak algılanmakta, öğrencilere ve öğretmenlere önemli fırsatlar sunarken, dikkatli kullanılmadığında potansiyel riskler de barındırmaktadır. Ayrıca, öğretmen adayları yapay zekânın eğitimde büyük faydalar sağlayabileceğini, ancak etik sorunlara da yol açabileceğini belirtmektedir. Bu çalışma, yapay zekâ teknolojilerinin eğitimde etkili kullanımı için öğretmen adaylarının yapay zekâ okuryazarlık düzeylerinin artırılmasının önemini vurgulamaktadır. YZ’nin karmaşıklığı ve çok yönlülüğü ile ilgili algılar, bu teknolojinin eğitimde hem potansiyel faydalar hem de zorluklar sunduğunu vurgulamaktadır. Bu bulgular, öğretmen yetiştirme programlarında YZ odaklı derslerin hazırlanması ve uygulanması, YZ’nin etik kullanımına yönelik yönergelerin oluşturulması ve uygulamaya dayalı atölye çalışmaları düzenlenmesi gerektiğine işaret etmektedir. Eğitimcilerin güncel YZ gelişmelerinden haberdar olmaları için sürekli mesleki gelişim programları sunulmalı ve politika yapıcılar YZ’nin eğitimde kullanımını izlemek ve değerlendirmek için politikalar geliştirmelidir. YZ, eğitim süreçlerinde önemli bir destek sağlarken, dikkatli ve etik bir şekilde kullanılması gerektiği, aksi takdirde çeşitli riskler taşıyabileceği unutulmamalıdır. Bu çalışma, YZ’nin eğitimdeki rolünü daha iyi anlamak ve bu teknolojinin eğitimde etkin kullanımını sağlamak amacıyla gelecekteki araştırmalar için de bir temel oluşturmaktadır.

Anahtar Kelimeler

eğitimde yapay zekâ, metafor analizi, öğretmen eğitiminde yapay zekâ, yapay zekâ, yapay zekâ okuryazarlığı

Etik Beyan

Araştırma Etiği Bu araştırmanın planlanmasından, uygulanmasına, verilerin toplanmasından verilerin analizine kadar olan tüm süreçte “Yükseköğretim Kurumları Bilimsel Araştırma ve Yayın Etiği Yönergesi” kapsamında uyulması belirtilen tüm kurallara uyulmuştur. Yönergenin ikinci bölümü olan “Bilimsel Araştırma ve Yayın Etiğine Aykırı Eylemler” başlığı altında belirtilen eylemlerden hiçbiri gerçekleştirilmemiştir. Bu çalışmanın yazım sürecinde bilimsel, etik ve alıntı kurallarına uyulmuş; toplanan veriler üzerinde herhangi bir tahrifat yapılmamış ve bu çalışma herhangi başka bir akademik yayın ortamına değerlendirme için gönderilmemiştir. Etik kurul izin bilgileri Etik değerlendirmeyi yapan kurul adı: Aksaray Üniversitesi İnsan Araştırmaları Etik Kurulu Etik değerlendirme karar tarihi: 15.05.2024 Etik değerlendirme belgesi sayı numarası: 2024/02-142

Metaphorical perceptions of pre-service teachers regarding artificial intelligence (AI)

Öz

This study examines pre-service teachers' metaphorical perceptions of artificial intelligence (AI). Employing a qualitative phenomenological approach, the research involved 285 faculty of education students selected through purposive and convenience sampling methods. Data were collected via an online survey during the spring semester of the 2023-2024 academic year. Content analysis and a five-step data analysis method were applied simultaneously, enhanced by external expert evaluations and peer debriefing to bolster the study's credibility. The findings of the research show that pre-service teachers perceive artificial intelligence as a supportive and powerful tool that provides fast and easy access to information and guides teaching and learning processes. However, they also recognize AI’s complexity and versatility, which can present both potential benefits and challenges. AI is perceived by pre-service teachers as an innovative and valuable resource in education, offering significant opportunities for students and teachers while also posing potential risks if not used carefully. Additionally, pre-service teachers noted that AI could offer substantial benefits in education but might also lead to ethical issues. This study highlights the need to improve AI literacy among pre-service teachers to ensure the effective use of AI technologies in education. It suggests that AI-focused courses be developed and integrated into teacher training programs, ethical guidelines for AI use in education be established, and practical workshops be organized. Continuous professional development programs are essential for educators to keep abreast of the latest AI developments, and policymakers should devise strategies to monitor and evaluate AI usage in educational settings. While AI offers significant support in educational processes, its application must be approached with caution to mitigate potential risks. This study lays the groundwork for future research aimed at better understanding AI's role in education and ensuring its effective implementation.

Anahtar Kelimeler

artificial intelligence in education, metaphor analysis, artificial intelligence in teacher education, artificial intelligence, artificial intelligence literacy

Kaynakça

• Araújo, J. (2024). Can ChatGPT enhance chemistry laboratory teaching? Using prompt engineering to enable AI in generating laboratory activities. Journal of Chemical Education, 101(5), 1858-1864. https://doi.org/10.1021/acs.jchemed.3c00745
• Aydın, Ö., & Karaarslan, E. (2023). Is ChatGPT leading generative AI? What is beyond expectations?. Academic Platform Journal of Engineering and Smart Systems, 11(3), 118-134.
• Barrett, A., & Pack, A. (2023). Not quite eye to A.I.: student and teacher perspectives on the use of generative artificial intelligence in the writing process. International Journal of Educational Technology in Higher Education, 20, 50. https://doi.org/10.1186/s41239-023-00427-0
• Bearman, M., Mahoney, P., Tai, J., Castanelli, D., & Watling, C. (2021). Invoking culture in medical education research: A critical review and metaphor analysis. Medical Education, 55(8), 903-911. https://doi.org/10.1111/medu.14464
• Chan, C. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20, 38. https://doi.org/10.1186/s41239-023-00408-3
• Chen, Y. (2024). Generative ai in medical practice: in-depth exploration of privacy and security challenges. Journal of Medical Internet Research, 26, e53008. https://doi.org/10.2196/53008
• Chien, C. (2019). Creating pathways to developing a “teacher self” through metaphor analysis. Research in Education, 106(1), 41-58. https://doi.org/10.1177/0034523719883663
• Chiu, T., Meng, H., Chai, C., King, I., Wong, S., & Yam, Y. (2022). Creation and evaluation of a pretertiary artificial intelligence (AI) curriculum. Ieee Transactions on Education, 65(1), 30-39. https://doi.org/10.1109/te.2021.3085878
• Conde, J., Reviriego, P., Salvachúa, J., Martínez, G., Hernández, J. A., & Lombardi, F. (2024). Understanding the impact of artificial intelligence in academic writing: metadata to the rescue. Computer, 57(1), 105-109.
• Creswell, J. W. (2007). Qualitative inquiry and research design: Choosing among five approaches (2nd Ed.). Sage Publications, Inc.
• Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory into Practice, 39(3), 124-130.
• Demmen, J., Semino, E., Demjén, Z., Koller, V., Hardie, A., Rayson, P., & Payne, S. (2015). A computer-assisted study of the use of violence metaphors for cancer and end of life by patients, family carers and health professionals. International Journal of Corpus Linguistics, 20(2), 205-231. https://doi.org/10.1075/ijcl.20.2.03dem
• Du, H. (2024). Exploring the effects of AI literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11, 559. https://doi.org/10.1057/s41599-024-03101-6
• Dwivedi, Y., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., … & Williams, D. M. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
• Elstad, E. (2024). High school teachers’ adoption of generative AI. Nordic Journal of Comparative and International Education (Njcie), 8(1). https://doi.org/10.7577/njcie.5736
• Fassbender, W. (2024). “I can almost recognize its voice”: AI and its impact on ethical teacher-centaur labor. English Teaching Practice & Critique, 23(1), 104-117. https://doi.org/10.1108/etpc-08-2023-0101
• Fenech, M., Harrison, L., Press, F., & Sumsion, J. (2020). Using metaphor to illuminate quality in early childhood education. Australasian Journal of Early Childhood, 45(2), 197-210. https://doi.org/10.1177/1836939120918482
• Gao, L. X., & Zhang, L. J. (2020). Teacher learning in difficult times: Examining foreign language teachers’ cognitions about online teaching to tide over Covid-19. Frontiers in Psychology, 11, 549653. https://doi.org/10.3389/fpsyg.2020.549653
• Gentile, M., Ottaviano, S., Perna, S., & Allegra, M. (2023). Do we still need teachers? Navigating the paradigm shift of the teacher's role in the AI era. Frontiers in Education, 8, 1161777. https://doi.org/10.3389/feduc.2023.1161777
• Getenet, S. (2024). Pre-service teachers and ChatGPT in multistrategy problem-solving: Implications for mathematics teaching in primary schools. International Electronic Journal of Mathematics Education, 19(1), em0766. https://doi.org/10.29333/iejme/14141
• Ghamrawi, N. (2023). Exploring the impact of AI on teacher leadership: Regressing or expanding?. Education and Information Technologies, 29(7), 8415-8433. https://doi.org/10.1007/s10639-023-12174-w
• Hashem, R. (2023). AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention. Research and Practice in Technology Enhanced Learning, 19, 023. https://doi.org/10.58459/rptel.2024.19023
• Hieu, H. (2024). Exploring the impact of AI in language education: Vietnamese EFL teachers’ views on using ChatGPT for fairy tale retelling tasks. International Journal of Learning Teaching and Educational Research, 23(3), 486-503. https://doi.org/10.26803/ijlter.23.3.24
• Jayavardhini, P., Mahalakame, R.M., Srinivetha, P., & Eugene Berna, I. (2024). AI study partner: development of an LLM and Gen AI-enhanced study assistant tool. International Journal of Scientific Research in Engineering and Management (IJSREM), 8(3), 1-7.
• Karataş, F., Abedi, F. Y., Ozek Gunyel, F., Karadeniz, D., & Kuzgun, Y. (2024). Incorporating AI in foreign language education: An investigation into ChatGPT’s effect on foreign language learners. Education and Information Technologies. https://doi.org/10.1007/s10639-024-12574-6
• Kim, J., Lee, H., & Cho, Y. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069-6104. https://doi.org/10.1007/s10639-021-10831-6
• Kohnke, L., Moorhouse, B., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868
• Lavrakas, P. J. (2008) (Eds). Encyclopaedia of survey research methods. Sage Publications, Inc.
• Lim, E. (2024). Metaphor analysis on pre-service early childhood teachers’ conception of AI (Artificial Intelligence) education for young children. Thinking Skills and Creativity, 51, 101455. https://doi.org/10.1016/j.tsc.2023.101455
• Mah, C. (2024). Beyond CheatBots: Examining tensions in teachers’ and students’ perceptions of cheating and learning with ChatGPT. Education Sciences, 14(5), 500. https://doi.org/10.3390/educsci14050500
• Montazeri, M. (2024). What are the applications of chatgpt in healthcare: gain or loss?. Health Science Reports, 7(2). https://doi.org/10.1002/hsr2.1878
• Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71, 137–161. https://doi.org/10.1007/s11423-023-10203-6
• Patton, M. Q. (2002). Qualitative research & evaluation methods (3th ed.). Sage Publications, Inc.
• Rajaei, A. (2023). Teaching in the age of AI/ChatGPT in mental-health-related fields. The Family Journal, 32(1), 6-10. https://doi.org/10.1177/10664807231209721
• Rodny-Gumede, Y., & Chasi, C. (2020). Metaphors of transformation of education and fitness for purpose: Towards a humanizing agenda. South African Journal of Higher Education, 34(1), 213-30. https://doi.org/10.20853/34-1-3147
• Scott, D., & Morrison, M. (2006). Key ideas in educational research. Continuum.
• Singh, S. V., & Hiran, K. K. (2022). The impact of AI on teaching and learning in higher education technology. Journal of Higher Education Theory and Practice, 22(13), 135-148. https://doi.org/10.33423/jhetp.v22i13.5514
• Su, J. (2023). AI literacy curriculum and its relation to children's perceptions of robots and attitudes towards engineering and science: An intervention study in early childhood education. Journal of Computer Assisted Learning, 40(1), 241-253. https://doi.org/10.1111/jcal.12867
• Şaban, A. (2006). Functions of metaphor in teaching and teacher education: A review essay. Teaching Education, 17(4), 299-315. https://doi.org/10.1080/10476210601017386
• Şaban, A., Koçbeker, B., & Saban, A. (2007). Prospective teachers' conceptions of teaching and learning revealed through metaphor analysis. Learning and Instruction, 17(2), 123-139. https://doi.org/10.1016/j.learninstruc.2007.01.003
• Weidener, L. (2024). Proposing a principle-based approach for teaching AI ethics in medical education. Jmir Medical Education, 10, e55368. https://doi.org/10.2196/55368
• Yau, K., Chai, C., Chiu, T., Meng, H., King, I., & Yam, Y. (2022). A phenomenographic approach on teacher conceptions of teaching Artificial Intelligence (AI) in k-12 schools. Education and Information Technologies, 28(1), 1041-1064. https://doi.org/10.1007/s10639-022-11161-x
• Zembylas, M. (2004). Emotion metaphors and emotional labor in science teaching. Science Education, 88(3), 301-324. https://doi.org/10.1002/sce.10116
• Zhang, J., & Zhang, Z. (2024). AI in teacher education: Unlocking new dimensions in teaching support, inclusive learning, and digital literacy. Journal of Computer Assisted Learning, 1–15. https://doi.org/10.1111/jcal.12988
• Zheng, L., Fan, Y., Chen, B., Huang, Z., Lei Gao., & Long, M. (2023). An AI-enabled feedback-feedforward approach to promoting online collaborative learning. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12292-5