PROSPECTIVE TEACHERS’ PERCEPTIONS OF ARTIFICIAL INTELLIGENCE AND REFLECTIONS ON THE USE OF ARTIFICIAL INTELLIGENCE IN EDUCATION

Abstract

It is widely expected that artificial intelligence will cause dramatic transformations in all fields of life, including education. In this study, it was aimed to dig into prospective teachers’ perceptions of artificial intelligence and their perspectives on the use of artificial intelligence in education. In this frame, the phenomenological approach was selected as the appropriate design, and nine prospective teachers, studying in different departments of the faculty of education at a university located in Central Anatolia, formed the study group. A semi-structured interview form was used as the data collection tool and descriptive analysis method was applied to the data. The findings showed that prospective teachers defined artificial intelligence by the features attributed to the human species, they had some misconceptions about artificial intelligence and perceived it as a possible threat to the human species. They presumed that artificial intelligence would have a positive influence on the economic aspects of education. However, they argued that it posed a huge danger to the future of the teaching profession and schooling, and would harm learning enormously. The suggestions prospective teachers made on the appropriate and effective use of artificial intelligence in education ranged from constructing national policies, artificial intelligence training for education staff, and improving educational curricula with artificial intelligence subjects/modules to monitoring. In line with the limitations and findings of the study, it was recommended that the researchers nurture the field of artificial intelligence in education with more qualitative and quantitative research with different stakeholders in the education system; the practitioners were recommended to develop national policies and artificial intelligence legislation.

Keywords

• opportunities
• precautions
• qualitative
• teaching profession
• threats

ADAY ÖĞRETMENLERİN YAPAY ZEKÂ ALGILARI VE EĞİTİMDE YAPAY ZEKÂ KULLANIMINA İLİŞKİN DÜŞÜNCELERİ

Abstract

Yapay zekânın tüm alanlarda olduğu gibi eğitim sektöründe de köklü değişiklikler yaratması beklenmektedir. Bu çalışmada eğitimde yapay zekâyı kullanacak aktörler olarak öğretmen adaylarının yapay zekâyla ilgili algıları ve eğitimde yapay zekânın etkilerine dair düşüncelerini ortaya koymak amaçlanmıştır. Bu çerçevede araştırmanın deseni olgubilim, çalışma grubu ise Orta Anadolu’da bulunan bir üniversitenin eğitim fakültesinde farklı bölümlerde öğrenim gören dokuz öğretmen adayı olarak belirlenmiştir. Yarı yapılandırılmış görüşme formuyla toplanan veriler betimsel teknikle analiz edilmiştir. Bulgular, öğretmen adaylarının yapay zekâyı insana atfedilen özellikler üzerinden tanımladığı, yapay zekâyla ilgili yanlış kavramsallaştırmalara sahip olduğu ve yapay zekâyı zaman zaman bir tehdit olarak algıladığını göstermiştir. Yapay zekânın eğitim ekonomisini olumlu yönde etkileyeceği ancak öğretmenlik mesleğinin ve eğitim kurumlarının yok olma tehlikesinin bulunduğuna dair görüşler öne çıkmış, ayrıca öğrenme üzerinde oldukça olumsuz etkileri olacağı ileri sürülmüştür. Eğitimde yapay zekânın doğru ve etkili bir biçimde kullanılması için sunulan öneriler ulusal politikalar, eğitim paydaşlarına yapay zekâ eğitimi, öğretim programlarında yapay zekâ dersleri/modülleri koyulması ve denetim gibi düşünceler yer almıştır. Çalışmanın sınırlılıkları ve bulguları çerçevesinde araştırmacılara eğitimin farklı paydaşlarıyla yapacakları nitel ve nicel çalışmalarla eğitimde yapay zekâ alan yazınındaki birikimi artırmaları; uygulayıcılara ise ulusal çapta politika belgelerinin ve mevzuatın oluşturulması gibi öneriler sunulmuştur.

Keywords

• Fırsatlar
• nitel
• öğretmenlik mesleği
• önlemler
• tehditler

References

1. Aggarwal, C. C. (2018). Neural networks and deep learning. Cham: Springer.
2. Akturan, U., & Esen, A. (2008). Fenomenoloji. T. Baş & U. Akturan (Eds.). Nitel araştırma yöntemleri (s. 83-98) Seçkin Yayıncılık.
3. An, X., Chai, C. S., Li, Y., Zhou, Y., Shen, X., Zheng, C., & Chen, M. (2023). Modeling English teachers’ behavioral intention to use artificial intelligence in middle schools. Education and Information Technologies, 28(5), 5187–5208. https://doi.org/10.1007/s10639-022-11286-z
4. Baker, T., & Smith, L. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. Nesta Foundation.
5. Bryant, J., Heitz, C., Sanghvi, S., & Wagle, D. (2020). How artificial intelligence will impact K-12 teachers. McKinsey & Company.
6. Chin, K.-Y., Wu, C. H., & Hong, Z. W. (29 Ağustos- 1 Eylül 2011). A humanoid robot as a teaching assistant for primary education. Fifth International Conference on Genetic and Evolutionary Computing, Kinmen, Taiwan / Xiamen, China. https://doi.org/10.1109/ICGEC.2011.13
7. Chiu, T. K., & Chai, C. S. (2020). Sustainable curriculum planning for artificial intelligence education: A self-determination theory perspective. Sustainability, 12(14), 5568. https://doi.org/10.3390/su12145568
8. Chounta, I. A., Bardone, E., Raudsep, A., & Pedaste, M. (2022). Exploring teachers’ perceptions of artificial intelligence as a tool to support their practice in Estonian K-12 education. International Journal of Artificial Intelligence in Education, 32(3), 725–755. https://doi.org/10.1007/s40593-021-00243-5

9. Clark, D. (2020). Artificial intelligence for learning: How to use AI to support employee development. Kogan Page Publishers.
10. Cohen, I. L., Liu, X., Hudson, M., Gillis, J., Cavalari, R. N., Romanczyk, R. G., ... & Gardner, J. M. (2017). Level 2 screening with the PDD Behavior Inventory: Subgroup profiles and implications for differential diagnosis. Canadian Journal of School Psychology, 32(3-4), 299-315. https://doi.org/10. 1177/0829573517721127
11. Cooper, H. E., Camic, P. M., Long, D. L., Panter, A. T., Rindskopf, D. E., & Sher, K. J. (2012). APA handbook of research methods in psychology, Vol 2: Research designs: Quantitative, qualitative, neuropsychological, and biological. American Psychological Association.
12. Creswell J. (2008). Basics of qualitative research. SAGE.
13. Creswell, J. W., & Poth, C. N. (2016). Qualitative inquiry and research design: Choosing among five approaches. SAGE.
14. Çelik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: a systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
15. Dillenbourg, P. (2016). The evolution of research on digital education. International Journal of Artificial Intelligence in Education, 26, 544-560. https://doi.org/10.1007/s40593-016-0106-z
16. Edmond, C. (2017). This is when a robot is going to take your job, according to Oxford University. Formative Content, World Economic Forum. An online publication of the World Economic Forum. 29.07.2024 tarihinde https://www.weforum.org/agenda/2017/07/how-long-before-a- robot-takes-your-job-here-s- when-ai-experts-think-it-will-happen adresinden erişilmiştir.
17. Eriçok, B., Karataş, F., & Yüce, E. (2024). Öğretmen adaylarının yapay zekaya ilişkin metafor algıları. Kocaeli Üniversitesi Eğitim Dergisi, 7(2), 607-630. http://doi.org/10.33400/kuje.1511500
18. Edwards, B. I., & Cheok, A. D. (2018). Why not robot teachers: Artificial intelligence for addressing teacher shortage. Applied Artificial Intelligence, 32(4), 345–360. https://doi.org/10.1080/08839514.2018.1464286
19. Federspiel, F., Mitchell, R., Asokan, A., Umana, C., & McCoy, D. (2023). Threats by artificial intelligence to human health and human existence. BMJ Global Health, 8(5), 1-6. https://doi.org/10.1136/bmjgh-2022-010435
20. Haugeland, J. (1989). Artificial intelligence: The very idea. MIT Press.
21. Heffernan, N. T., & Heffernan, C. L. (2014). The ASSISTments ecosystem: Building a platform that brings scientists and teachers together for minimally invasive research on human learning and teaching. International Journal of Artificial Intelligence in Education, 24(4), 470–497. https://doi.org/10.1007/s40593-014-0024-x
22. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign, Boston, USA.
23. Hrastinski, S., Olofsson, A. D., Arkenback, C., Ekström, S., Ericsson, E., Fransson, G., ... & Utterberg, M. (2019). Critical imaginaries and reflections on artificial intelligence and robots in postdigital K-12 education. Postdigital Science and Education, 1, 427-445. https://doi.org/10.1007/s42438-019-00046-x
24. Gardner, H. E. (2000). Intelligence reframed: Multiple intelligences for the 21st century. Hachette Uk.
25. Gaudioso, E., Montero, M., & Hernandez-Del-Olmo, F. (2012). Supporting teachers in adaptive educational systems through predictive models: A proof of concept. Expert Systems with Applications, 39(1), 621–625. https://doi.org/10.1016/j.eswa.2011.07.052
26. Ghafourifar, M., Khorrami, M., Shamsabadi, H., & Ganjali, A. (2017). The Study of phonetic stylistics in the sermons of Nahj al-balagha. Journal of Arabic Language & Literature, 8(2), 19-22.
27. Grace, K., Salvatier, J., Dafoe, A., Zhang, B & Evans, O. (2018). When will AI exceed human performance? Evidence from AI experts. Journal of Artificial Intelligence Research 62, 729-754. https://doi.org/10.48550/arXiv.1705.08807
28. Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260. https://doi.org/10.1126/science.aac4520
29. Karataş, F., Eriçok, B. & Tanrikulu, L. (2024). Reshaping curriculum adaptation in the age of artificial intelligence: Mapping teachers' AI-driven curriculum adaptation patterns. British Educational Research Journal, 00, 1–27. https://doi.org/10.1002/berj.4068
30. Kersting, N. B., Sherin, B. L., & Stigler, J. W. (2014). Automated scoring of teachers’ open-ended responses to video prompts: Bringing the classroom-video-analysis assessment to scale. Educational and Psychological Measurement, 74(6), 950-974. https://doi.org/10.1177/0013164414521634
31. Kılıç, T. (26 Mayıs 2024). İnsan beyninin sınırları. [Video]. Youtube. https://www.youtube.com/watch?v=jUZvlU1It5U
32. Kurzweil, R. (1990). The age of intelligent machines. MIT Press.
33. Lameras, P., & Arnab, S. (2022). Power to the teachers: An exploratory review on artificial intelligence in education. Information (Switzerland), 13(1). https://doi.org/10.3390/info13010014
34. Langran, E., Searson, M., & Trumble, J. (2024). Transforming teacher education in the age of generative AI. M. Searson, E. Langran & J. Trumble (Ed.) Exploring new horizons: Generative artificial intelligence and teacher education (s. 2-13). Association for the Advancement of Computing in Education (AACE).
35. Lee, E., Lee, Y., Kye, B., & Ko, B. (30 Temmuz 2008). Elementary and middle school teachers’, students’ and parents’ perception of robot-aided education in Korea. (Sözlü bildiri). EdMedia, World Conference on Educational Media and Technology, Vienna, Austria.
36. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. SAGE.
37. Lindner, A., & Berges, M. (21-24 Ekim 2020). Can you explain AI to me? Teachers’ pre-concepts about artificial intelligence. (Sözlü bildiri) 2020 IEEE Frontiers in Education Conference (FIE), Uppsala, İsveç.
38. Lindner, A., & Romeike, R. (18-20 Kasım 2019). Teachers’ perspectives on artificial intelligence. (Sözlü bildiri). ISSEP 2019 - 12th International conference on informatics in schools: Situation, evaluation and perspectives. Larnaca, Kıbrıs.
39. Long, D., & Magerko, B. (25-30 Nisan 2020). What is AI literacy? Competencies and design considerations. (Sözlü bildiri) Conference on Human Factors in Computing Systems. Honolulu, HI, USA. https://doi.org/10.1145/3313831.3376727
40. Luckin, R., & Cukurova, M. (2019). Designing educational technologies in the age of AI: A learning sciences‐ driven approach. British Journal of Educational Technology, 50(6), 2824-2838. https://doi.org/10.1111/bjet.12861
41. Lui, A., & Lamb, G. W. (2018). Artificial intelligence and augmented intelligence collaboration: regaining trust and confidence in the financial sector. Information & Communications Technology Law, 27(3), 267-283. https://doi.org/10.1080/13600834.2018.1488659
42. Nilsson, N. J. (1998). Artificial intelligence: a new synthesis. Morgan Kaufmann.
43. Paterson, C. (2017). Artificial intelligence in education: Where it is at, where its headed. Getting Smart. An online publication. 28.07.2024 tarihinde http://www.gettingsmart.com/2017/10/artificial-intelligence-in- education/ adresinden erişilmiştir.
44. Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1–13. https://doi.org/10.1186/s41039-017-0062-8
45. Polak, S., Schiavo, G., & Zancanaro, M. (30 Nisan – 6 Mayıs 2022). Teachers’ perspective on artificial intelligence education: an initial investigation. (Sözlü bildiri) Conference on Human Factors in Computing Systems - Proceedings. New Orleans, USA. https://doi.org/10.1145/3491101.3519866
46. Russel, S. & Norvig, P. (2010). Artificial intelligence: A modern approach. Pearson Education. Salovey, P., & Mayer, J. D. (1990). Emotional intelligence. Imagination, Cognition and Personality, 9(3), 185-211.
47. Sánchez Prieto, J., Trujillo Torres, J. M., Gómez García, M., & Gómez García, G. (2020). Gender and digital teaching competence in dual vocational education and training. Education Sciences, 10(3), 84. https://doi.org/10.3390/educsci10030084
48. Schank, R. C. (1987). What is AI, anyway?. AI Magazine, 8(4), 59-69. https://doi.org/10.1609/aimag.v8i4.623
49. Seldon, A., & Abidoye, O. (2018). The fourth education revolution: Will artificial intelligence liberate or infantilise humanity. University of Buckingham.
50. Seufert, S., Guggemos, J., & Sailer, M. (2020). Technology-related knowledge, skills, and attitudes of pre-and in-service teachers: The current situation and emerging trends. Computers in Human Behavior, 115, 106552. https://doi.org/10.1016/j.chb.2020.106552
51. Smith, J. A. (2018). “Yes it is phenomenological”: A reply to Max Van Manen’s critique of interpretative phenomenological analysis. Qualitative Health Research, 28(12), 1955-1958. https://doi.org/10.1177/1049732318799577
52. T.C. Cumhurbaşkanlığı (2021). Ulusal yapay zeka stratejisi 2021-2025. 31.07.2024 tarihinde https://cbddo.gov.tr/SharedFolderServer/Genel/File/TR-UlusalYZStratejisi2021-2025.pdf adresinden erişilmiştir.
53. T.C. Cumhurbaşkanlığı (2021). Ulusal yapay zeka stratejisi 2024-2025 eylem planı. 31.07.2024 tarihinde https://cbddo.gov.tr/SharedFolderServer/Genel/File/UlusalYapayZekaStratejisi2024- 2025EylemPlani.pdf adresinden erişilmiştir.
54. Tegmark, M. (2017). Life 3.0: Being human in the age of artificial intelligence. Random House
55. Tekin, N. (2023). Eğitimde yapay zekâ: Türkiye kaynaklı araştırmaların eğilimleri üzerine bir içerik analizi. Necmettin Erbakan Üniversitesi Ereğli Eğitim Fakültesi Dergisi, 5(Özel Sayı), 387- 411. https://doi.org/10.51119/ereegf.2023.49
56. Umut, T. N. & Öntaş, T. (2024). Eğitimde yapay zekâ kullanımına ilişkin düzenleme ihtiyacı ve öneriler. Politika Notu, Enstitü Sosyal.
57. UNESCO (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development education sector. United Nations Educational, Scientific and Cultural Organization, Paris, France. 29.07.2024 tarihinde https://en.unesco.org/themes/education- policy- adresinden erişilmiştir.
58. Vlasova, E. Z., Avksentieva, E. Y., Goncharova, S. V., & Aksyutin, P. A. (2019). Artificial intelligence-The space for the new possibilities to train teachers. Espacios, 40(9), 1-17.
59. Watkins, J.(2017). Why you should care: Because the future ain’t slowing down for nobody. The daily dosage. Ozy Poll publications online. 28.07.2024 tarihinde https://www.ozy.com/acumen/ozy-poll-full-results/80468 adresinden erişilmiştir.
60. Winston, P. H. (1992). Artificial intelligence. Addison-Wesley Longman Publishing.
61. Westermann, K., Rummel, N., & Holz, L. (21-25 Şubat 2012). Taking up pre-concepts promotes understanding. Contributions to teaching mathematics 2012 digital. (Sözlü Bildiri). 46th Conference for Mathematics Education. Münster: WTMVerlag.
62. Wogu, I., Assibong, P., Deborah Udoh, O., Misra, S., Fadeke Olu-Owolabi, E., Assibong, P. A., & Udoh, O. D. (2018). Artificial intelligence, artificial teachers and the fate of learners in the 21st century education sector: Implications for theory and practice. International Journal of Pure and Applied Mathematics, 119(16), 2245-2259.
63. Yıldırım, A., & Şimşek, H. (2008). Sosyal bilimlerde nitel araştırma yöntemleri. Seçkin Yayıncılık
64. Yudkowsky, E. (2008). Artificial intelligence as a positive and negative factor in global risk. N. Bostrom & M. M. Ćirković (Eds.) Global catastrophic risks (s. 308-345). Oxford University Press.
65. Zhang, W. R. (2017). From equilibrium-based business intelligence to information conservational quantum-fuzzy cryptography—a cellular transformation of bipolar fuzzy sets to quantum intelligence machinery. IEEE Transactions on Fuzzy Systems, 26(2), 656-669. https://doi.org/10.1109/TFUZZ.2017.2687408.
66. Zheng, N. N., Liu, Z. Y., Ren, P. J., Ma, Y. Q., Chen, S. T., Yu, S. Y., ... & Wang, F. Y. (2017). Hybrid- augmented intelligence: collaboration and cognition. Frontiers of Information Technology & Electronic Engineering, 18(2), 153-179. https://doi.org/10.1631/FITEE.1700053