Matematik Öğretmen Adaylarının ChatGPT Kullanımına İlişkin Algılarının Tematik Modellenmesi: Değerlendirmeler, Etik Zorluklar ve Beklentiler

Öz

Üretken yapay zekanın küresel yayılımı, eğitim üzerindeki etkisi açısından tartışılmaktadır. ChatGPT'nin eğitim ortamlarında hızla benimsenmesine rağmen, araştırmaların azlığından dolayı eğitimciler ve kurumlar ChatGPT'nin öğrenci öğrenme eğilimi üzerindeki potansiyel öngörülemeyen ve uzun vadeli sonuçlarıyla yüzleşmeye tam olarak hazır değillerdir. Bu çalışmada, matematik öğretmen adaylarının ChatGPT ile ilgili deneyimleri, ChatGPT'nin faydaları, etik sorunları ve eğitimde ve gelecekteki öğretimde potansiyel kullanımlarına ilişkin algıları incelenmiştir. Bu çalışmanın katılımcıları ikinci ve üçüncü yılındaki 25 matematik öğretmen adayıdır (22 kadın ve 3 erkek). Nitel veriler, yarı yapılandırılmış çevrimiçi görüşme formları ve bunu takip eden odak grup tartışması yoluyla toplanmış ve tematik analiz metodolojisi kullanılarak analiz edilmiştir. ChatGPT'nin benimsenmesi için beş ana temayı içeren bir algısal model geliştirilmiştir: ChatGPT'ye aşinalık, olumlu değerlendirmeler, tatmin edici olmayan deneyimler ve etik kaygılar, matematik öğretmenliği eğitiminde kullanma istekleri ve gelecekteki öğretimlerinde kullanma istekleri. ChatGPT öğretmen adayları için faydalı olarak görülmüş, ancak zorluklar ve etik endişeler dile getirilmiş ve bulguların çıkarımları tartışılmıştır. Bu keşifsel çalışma, eğitimciler, eğitim politika yapıcıları ve gelecekteki araştırmalar için öğretmen eğitimi programlarında yapay zeka ile ilgili mevcut tartışmalara ampirik kanıt sağlayarak katkıda bulunmayı arzulamaktadır.

Anahtar Kelimeler

• Yapay zeka
• Öğretmen eğitimi
• Etik
• Tematik analiz

Thematic Modeling of Preservice Mathematics Teachers’ Reflections on ChatGPT Use: Appraisals, Ethical Challenges and Aspirations

Abstract

The global proliferation of generative AI is being debated because of its implication on education. Despite rapid adoption of ChatGPT-3.5 in educational settings, research is scarce as educators and institutions are not fully prepared to face the potential unforeseen and long-term consequences of ChatGPT on student learning dispositions. This study explored pre-service mathematics teachers' experiences with ChatGPT and their perceptions regarding its affordances, ethical issues, and potential uses in education and future teaching. Using a convenience sampling, 25 second- and third-year pre-service mathematics teachers (22 female and 3 male) participated in the study. Qualitative data were collected from semi-structured online interview forms and a subsequent focus group discussion, which were analyzed using thematic analysis methodology. A perceptual model of ChatGPT adoption (PMCA) including five main themes were developed: familiarity with ChatGPT, positive appraisals, dissatisfactory experiences and ethical concerns, aspirations to use in mathematics teacher education, and aspirations to use for prospective teaching. The research results showed that teacher candidates found using ChatGPT in their education useful, but they also expressed their concerns about the difficulties and ethics of using ChatGPT. This study aims to provide empirical evidence for educators, policy makers, and future research to contribute to the current conversations about AI in teacher education programmes.

Keywords

• Artificial intelligence
• Teacher education
• Ethics
• Thematic analysis

Kaynakça

1. Ahsan, K., Akbar, S., & Kam, B. (2021). Contract cheating in higher education: a systematic literature review and future research agenda. Assessment & Evaluation in Higher Education, 47(4), 523-539. https://doi.org/10.1080/02602938.2021.1931660
2. Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive tutors: Lessons learned. Journal of the Learning Sciences, 4(2), 167–207. https://doi.org/10.1207/s15327809jls0402_2
3. Antonenko, P., & Abramowitz, B. (2023). In-service teachers’(mis) conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64-78. https://doi.org/10.1080/15391523.2022.2119450
4. Belda-Medina, J., & Kokošková, V. (2023). Integrating chatbots in education: insights from the Chatbot-Human Interaction Satisfaction Model (CHISM). International Journal of Educational Technology in Higher Education, 20(1), 62. https://doi.org/10.1186/s41239-023-00432-3
5. Berendt, B., Littlejohn, A., & Blakemore, M. (2020). AI in education: Learner choice and fundamental rights. Learning, Media and Technology, 45(3), 312–324. https://doi.org/10.1080/17439884.2020.1786399
6. Blanchard, E. G. (2015). Socio-cultural imbalances in AIED research: Investigations, implications and opportunities. International Journal of Artificial Intelligence in Education, 25, 204-228. https://doi.org/10.1007/s40593-014-0027-7
7. Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
8. Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138, 107468. https://doi.org/10.1016/j.chb.2022.107468

9. Celik, 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
10. Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success. Information Systems Frontiers, 25(1), 161–182. https://doi.org/10.1007/s10796-022-10291-4
11. Cohen L, Manion L, Morrison K (2013). Research methods in education, 7th edn. Taylor and Francis, Routledge, New York
12. Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452. https://doi.org/10.1007/s10956-023-10039-y
13. Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.10 80/00131857.2020.1728732
14. Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 1-12. https://doi.org/10.1080/14703297.2023.2190148
15. Crompton, H., & Burke, D. (2022). Artificial intelligence in K-12 education. SN Social Sciences, 2(7), 113. https://doi.org/10.1007/s43545-022-00425-5
16. Cu, M. A., & Hochman, S. (2023). Scores of Stanford students used ChatGPT on final exams. The Stanford Daily. https://stanforddaily.com/2023/01/22/scores-of-stanford-students-used-chatgpt-on-final-exams-survey-suggests/
17. DeMink-Carthew, J. (2018). Learning to teach in a “World Not Yet Finished”: Social justice education in the middle level preservice teacher classroom. Middle School Journal, 49(4), 24-34. https://doi.org/10.1080/00940771.2018.1488471
18. Edwards, C., Edwards, A., Spence, P. R., & Lin, X. (2018). I, teacher: using artificial intelligence (AI) and social robots in communication and instruction. Communication Education, 67(4), 473–480. https://doi.org/10.1080/03634523.2018.1502459
19. Essel, H. B., Vlachopoulos, D., Tachie-Menson, A., Johnson, E. E., & Baah, P. K. (2022). The impact of a virtual teaching assistant (chatbot) on students' learning in Ghanaian higher education. International Journal of Educational Technology in Higher Education, 19(1), 1-19. https://doi.org/10.1186/s41239-022-00362-6
20. Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2023). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 1-15. https://doi.org/10.1080/14703297.2023.2195846
21. Flick, U. (2009). An introduction to qualitative research. Sage.
22. Glaser, B. & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. Sage.
23. Goel, A. K., & Joyner, D. A. (2017). Using AI to teach AI: Lessons from an online AI class. AI Magazine, 38(2), 48–58.
24. Green, J., & Thorogood, N. (2014). Qualitative methods for health research (4th ed.). Sage.
25. Holloway, I., & Todres, L. (2003). The status of method: Flexibility, consistency and coherence. Qualitative Research, 3, 345–357. doi:10.1177/1468794103033004
26. Holmes, W., & Miao, F. (2023). Guidance for generative AI in education and research. UNESCO Publishing.
27. Hopp, C., & Speil, A. (2021). How prevalent is plagiarism among college students? Anonymity preserving evidence from Austrian undergraduates. Accountability in Research, 28(3), 133–148. https://doi.org/10.1080/08989621.2020.1804880
28. Hotaman, D. (2010). The teaching profession: knowledge of subject matter, teaching skills and personality traits. Procedia-Social and Behavioral Sciences, 2(2), 1416-1420. https://doi.org/10.1016/j.sbspro.2010.03.211
29. Hung, J., & Chen, J. (2023). The Benefits, Risks and Regulation of Using ChatGPT in Chinese Academia: A Content Analysis. Social Sciences, 12(7), 380. https://doi.org/10.3390/socsci12070380
30. Joo, Y. J., Park, S., & Lim, E. (2018). Factors influencing preservice teachers’ intention to use technology: TPACK, teacher self-efficacy, and technology acceptance model. Educational Technology & Society, 21(3), 48–59.
31. Kim, J., Lee, H., & Cho, Y. H. (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
32. Lincoln, Y. S. & Guba, E. (1985). Naturalistic Inquiry. Beverly Hills, CA: Sage.
33. Liu, S. H. (2012). A multivariate model of factors influencing technology use by preservice teachers during practice teaching. Journal of Educational Technology & Society, 15(4), 137-149.
34. Liu, W. (2023). The cognitive basis of thematic analysis. International Journal of Research & Method in Education, 1-11. https://doi.org/10.1080/1743727x.2023.2274337
35. Lozano, A., & Blanco Fontao, C. (2023). Is the Education System Prepared for the Irruption of Artificial Intelligence? A Study on the Perceptions of Students of Primary Education Degree from a Dual Perspective: Current Pupils and Future Teachers. Education Sciences, 13(7), 733. https://doi.org/10.3390/educsci13070733
36. Luckin, R., Cukurova, M., Kent, C., & du Boulay, B. (2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076
37. Moore, R. L., Jiang, S., & Abramowitz, B. (2023). What would the matrix do?: a systematic review of K-12 AI learning contexts and learner-interface interactions. Journal of Research on Technology in Education, 55(1), 7-20. https://doi.org/10.1080/15391523.2022.2148785
38. Nowell, L. S., Norris, J. M., White, D. E., & Moules, N. J. (2017). Thematic analysis: Striving to meet the trustworthiness criteria. International Journal of Qualitative Methods, 16(1), 160940691773384. https://doi.org/10.1177/1609406917733847
39. Orduña-Malea, E., & Cabezas-Clavijo, Á. (2023). ChatGPT and the potential growing of ghost bibliographic references. Scientometrics, 128(9), 5351–5355. https://doi.org/10.1007/s11192-023-04804-4
40. Pavlik, J. V. (2023). Collaborating with ChatGPT: Considering the implications of generative artificial intelligence for journalism and media education. Journalism & Mass Communication Educator, 78(1), 84–93. https://doi.org/10.1177/10776958221149577
41. Pham, S. T. H., & Sampson, P. M. (2022). The development of artificial intelligence in education: A review in context. Journal of Computer Assisted Learning, 38(5), 1408–1421. https://doi.org/10.1111/jcal.12687
42. 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
43. Reiss, M. J. (2021). The use of Al in education: Practicalities and ethical considerations. London Review of Education, 19(1), 1-14. https://doi.org/10.14324/lre.19.1.05
44. Roscoe, R. D., Salehi, S., Nixon, N., Worsley, M., Piech, C., & Luckin, R. (2022). Inclusion and Equity as a Paradigm Shift for Artificial Intelligence in Education. In F. Ouyang, P. Jiao, B. M. McLaren & A. H. Alavi (Eds.), Artificial Intelligence in STEM Education, 359–374. https://doi.org/10.1201/9781003181187-28
45. Sáiz-Manzanares, M. C., Marticorena-Sánchez, R., Martín-Antón, L. J., Díez, I. G., & Almeida, L. (2023). Perceived satisfaction of university students with the use of chatbots as a tool for self-regulated learning. Heliyon, 9(1), e12843. https://doi.org/10.1016/j.heliyon.2023.e12843
46. Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International Journal of Educational Technology in Higher Education, 18(1), 1-23. https://doi.org/10.1186/s41239-021-00292-9
47. Shin, D. (2022). Teaching mathematics integrating intelligent tutoring systems: investigating prospective teachers’ concerns and TPACK. International Journal of Science and Mathematics Education, 20, 1659–1676. https://doi.org/10.1007/s10763-021-10221-x
48. Shoufan, A. (2023). Exploring students’ perceptions of ChatGPT: Thematic analysis and follow-up survey. IEEE Access, 11, 38805-38818. https://doi.org/10.1109/access.2023.3268224
49. Tapan-Broutin, M. S. (2023). Matematik Öğretmen Adaylarının ChatGPT ile Başlangıç Deneyimlerinde Sordukları Soruların İncelenmesi [Examination of Questions Asked by Pre-Service Mathematics Teachers in Their Initial Experiences with ChatGPT]. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 36 (2), 707-732.
50. Vaughn, S., Schumm, J. S., Sinagub J., & Sinagub J. M. (1996). Focus group interviews in education and psychology. Sage.
51. Wogu, I. A. P., Misra, S., Olu-Owolabi, E. F., Assibong, P. A., Udoh, O. D., Ogiri, S. O., & Damasevicius, R. (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.
52. 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), 1-27. https://doi.org/10.1186/s41239-019-0171-0