A Generative AI–Supported Production-Based Teacher Education Study: “Twice-Exceptional Digital Stories”

Abstract

This study examines pre-service teachers’ processes of producing digital stories themed around twice-exceptional (2e) students using GenAI tools and the quality of the products that emerged in this process. Designed as a case study within qualitative research designs, the study was conducted with 54 third-year pre-service teachers studying at a faculty of education. During the seven-week production process, the pre-service teachers conducted a GenAI-supported literature review, created a story draft, wrote a script, prepared a storyboard, generated 3D visuals and animations, produced audio elements, and combined all components to obtain digital stories in video format lasting 60–120 seconds. The quality of the digital stories was evaluated by three experts using the “Graded Assessment Scale for Digital Stories.” It was determined that there was a high level of agreement among the experts and that the quality of the digital stories was high. Qualitative data regarding the pre-service teachers’ production process were collected through focus group interviews and analyzed using content analysis. As a result of the content analysis, four themes and fifteen categories were identified: “Emotional Experience Related to the Process,” “Technical and GenAI-Related Problems,” “Collaboration and Production Organization,” and “Learning Outcomes and Awareness Development.” The GenAI-supported production process contributed to shaping pre-service teachers’ pedagogical representations of 2e students within a strength-based and inclusive perspective. The technical challenges and problems experienced during the process, as well as difficulties in establishing and managing collaboration, provide important insights for production-based teacher education practices.

Keywords

• twice exceptional students
• pre-service teachers
• digital story telling
• generative artifical intelligence

Üretken Yapay Zekâ (ÜYZ) Destekli Üretim Temelli Öğretmen Eğitimi Çalışması: “İki Kere Farklı Dijital Hikâyeler”

Abstract

Bu çalışma, öğretmen adaylarının ÜYZ araçlarıyla iki kere farklı (2f) öğrenciler temalı dijital hikâye üretme süreçlerini ve bu süreçte ortaya çıkan ürünlerin niteliğini incelemektedir. Durum çalışması desenine göre yürütülen çalışmaya, bir eğitim fakültesinde öğrenim gören üçüncü sınıf 54 öğretmen adayı katılmıştır. Yedi hafta süren üretim sürecinde öğretmen adayları, ÜYZ destekli literatür taraması yapmış, hikâye taslağı oluşturmuş, senaryo yazmış, hikâye tahtası hazırlamış, 3D görsel ve animasyonlar, sesler üretmiş ve tüm öğeleri birleştirerek 60-120 saniye uzunluğunda video formatında dijital hikâyeler elde etmişlerdir. Dijital hikâyelerin niteliği “Dijital Hikâyeler İçin Dereceli Değerlendirme Ölçeği” kullanılarak üç uzman tarafından değerlendirilmiştir. Uzmanlar arasında yüksek düzeyde uyum olduğu ve dijital hikâyelerin niteliğinin yüksek olduğu belirlenmiştir. Öğretmen adaylarının üretim sürecine ilişkin nitel veriler odak grup görüşmeleriyle toplanmış ve içerik analizi ile çözümlenmiştir. İçerik analizi sonucunda; “Sürece İlişkin Duygusal Deneyim”, “Teknik ve ÜYZ Kaynaklı Sorunlar”, “İş birliği ve Üretim Organizasyonu” ve “Öğrenme Çıktıları ve Farkındalık Gelişimi” olmak üzere dört temaya ve on beş kategoriye ulaşılmıştır. ÜYZ destekli üretim süreci, öğretmen adaylarının 2f öğrencilere yönelik pedagojik temsillerini güçlü yönlere odaklanan kapsayıcı bir bakış açısıyla biçimlendirmelerine katkı sağlamıştır. Süreçte yaşanan teknik zorluklar ile iş birliği sürecindeki aksaklıklar üretim temelli öğretmen eğitimi uygulamalarına yönelik önemli ipuçları sunmaktadır.

Keywords

• iki kere farklı öğrenciler
• öğretmen adayları
• dijital hikâye anlatımı
• üretken yapay zekâ

References

1. Açar, D., & Gül, M. D. (2025). Academic and socio-emotional experiences of a twice-exceptional student. Behavioral Sciences, 15(10), 1349. https://doi.org/10.3390/bs15101349
2. Akgül, G. (2021). Teachers’ metaphors and views about gifted students and their education. Gifted Education International, 37(3), 273-289. https://doi.org/10.1177/0261429421988927
3. Al Hroub, A. (2021). Utility of psychometric and dynamic assessments for identifying cognitive characteristics of twice-exceptional students. Frontiers in Psychology, 12, 765936. https://doi.org/10.3389/fpsyg.2021.747872
4. Alban-Vera, C. G. (2025). Literary narratives in teacher education: A pedagogical approach for developing critical and reflective competencies in basic education. YUYAY: Estrategias, Metodologías & Didácticas Educativas, 4(2), 50-61. https://doi.org/10.59343/yuyay.v4i2.98
5. Atmaca, F., & Baloğlu, M. (2022). The two sides of cognitive masking: A three-level Bayesian meta-analysis on twice-exceptionality. Gifted Child Quarterly, 66(4), 281–299. https://doi.org/10.1177/00169862221110875
6. Baki, Y. (2019). Türkçe öğretmeni adaylarının yaratıcı yazma becerilerinin geliştirilmesinde dijital öykülerin etkisi. Ana Dili Eğitimi Dergisi, 7(4), 964-995. https://doi.org/10.16916/aded.597269
7. Barbieri, W., & Nguyen, N. N. (2025). Generative AI as a “placement buddy”: Supporting pre-service teachers in work-integrated learning, self-management and crisis resolution. Australasian Journal of Educational Technology, 41(2), 34-49. https://doi.org/10.14742/ajet.10035
8. Büyüköztürk, Ş. (2024). Sosyal bilimler için veri analizi el kitabı: İstatistik, araştırma deseni, SPSS uygulamaları ve yorum (31. bs.). Pegem Akademi.

9. Cornoldi, C., Giofrè, D., & Toffalini, E. (2023). Cognitive characteristics of intellectually gifted children with a diagnosis of ADHD. Intelligence, 97, 101702. https://doi.org/10.1016/j.intell.2023.101736
10. Creswell, J. W. (2020). Educational research: Planning, conducting, and evaluating quantitative and qualitative research. Pearson Higher Ed.
11. Çoruk, H., & Seferoğlu, S. S. (2020). The effect of digital storytelling process on the development of reflective thinking skills of learners. Instructional Technology and Lifelong Learning, 1(1), 1-23.
12. Elo, S., & Kyngas, H. (2008). The qualitative content analysis process. Journal of Advanced Nursing, 62(1), 107–115. https://doi.org/10.1111/j.1365-2648.2007.04569.x
13. Espino, C. (2025). Pre-service teachers’ perspectives on generative AI: Insights, applications, and challenges in the classroom. International Journal on Studies in Education, 7(3), 732-747. https://doi.org/10.46328/ijonse.1930
14. Feldman-Maggor, Y., Blonder, R., & Alexandron, G. (2024). Perspectives of generative aı in chemistry education within the TPACK framework. Journal of Science Education and Technology, 34, 1- 12. https://doi.org/10.1007/s10956-024-10147-3
15. Firat, T., & Bildiren, A. (2023). The characteristics of gifted children with learning disabilities according to preschool teachers. Early Years, 43(4–5), 921–937. https://doi.org/10.1080/09575146.2022.2034755
16. Foley Nicpon, M., & Assouline, S. G. (2020). High ability students with coexisting disabilities: Implications for school psychological practice. Psychology in the Schools, 57(10), 1567–1582. https://doi.org/10.1002/pits.22342
17. George, D., & Mallery, P. (2018). Descriptive statistics. In IBM SPSS statistics 25 step by step (pp. 126-134). Routledge.
18. Giri, D., & Sharma, J. (2024). Transformative effects of animation, virtual reality, and augmented reality in education- A Study. ShodhKosh: Journal of Visual and Performing Arts, 4(2SE), 237–246. https://doi.org/10.29121/shodhkosh.v4.i2SE.2023.563
19. Gürsoy, G. (2021). Digital storytelling: Developing 21st century skills in science education. European Journal of Educational Research, 10(1), 97-113. https://doi.org/10.12973/eu-jer.10.1.97
20. Hutchins, E. (1995). Cognition in the Wild. MIT press.
21. Iqbal, J., Hashmi, Z., Asghar, M., & Abid, M. (2025). Generative AI tool use enhances academic achievement in sustainable education through shared metacognition and cognitive offloading among preservice teachers. Scientific Reports, 15, 16610. https://doi.org/10.1038/s41598-025-01676-x
22. Istenic Starcic, A., Cotic, M., Solomonides, I., & Volk, M. (2016). Engaging preservice primary and preprimary school teachers in digital storytelling for the teaching and learning of mathematics. British Journal of Educational Technology, 47(1), 29-50. https://doi.org/10.1111/bjet.12253
23. Karataş, S., Bozkurt, Ş., & Hava, K. (2016). The perspective of history pre-service teachers’ towards the use of digital storytelling in educational environments. Journal of New Results in Science, 13, 500-509. https://doi.org/10.14687/ijhs.v13i1.3167
24. Keary, A., Wood, N., Barley, K., & Carabott, K. (2022). Generating reflections through professional collaborative storytelling. Australian Journal of Teacher Education (Online), 47(2), 44-59.
25. Kenshinbay, T., Ghorbandordinejad, F., Bolatova, A., & Kiyassova, K. (2025). Enhancing language teacher reflection through narrative techniques: Character development and critical incident analysis: language teacher reflection through narrative techniques. Bulletin of Language and Literature Studies, 2(1). https://doi.org/10.59652/blls.v2i1.482
26. Khan, S. A., Poletti, G., Khan, F. N., & Hussain, S. (2025). Digital storytelling: A pedagogical approach to enhance young learners social-emotional skills. Review of Education, Administration & Law, 8(2), 219-228. https://doi.org/10.47067/real.v8i2.421
27. Kong, S., & Yang, Y. (2024). A human-centered learning and teaching framework using generative artificial intelligence for self-regulated learning development through domain knowledge learning in k–12 settings. IEEE Transactions on Learning Technologies, 17, 1588-1599. https://doi.org/10.1109/tlt.2024.3392830
28. Krippendorff, K. (2018). Content analysis: An introduction to its methodology (4th ed.). Sage.
29. Lakhe Shrestha, B. L., Dahal, N., Hasan, M. K., Paudel, S., & Kapar, H. (2025, June). Generative AI on professional development: a narrative inquiry using TPACK framework. Frontiers in Education, 10, Article 1550773. https://doi.org/10.3389/feduc.2025.1550773
30. Lawson, A. P., White, J., & Williams, J. (2025). Building bridges for twice-exceptional students: a case study in a secondary school. Education Sciences, 15(9), 1260. https://doi.org/10.3390/educsci15091260
31. Lewis, K. D., & Milam, M. E. (2026). Powerful learning: Dual differentiation for twice-exceptional learners. Journal of Advanced Academics, 37(1), 147-175. https://doi.org/10.1177/1932202X251396237
32. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Newberry Park.
33. McCoach, D. B., Siegle, D., & Rubenstein, L. D. (2020). Pay attention to inattention: Exploring ADHD symptoms in a sample of underachieving gifted students. Gifted Child Quarterly, 64(1), 3–17.https://doi.org/10.1177/0016986219901320
34. Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). Sage.
35. Minnaert, A. (2022). Inclusive support to safeguard the strengths of twice-exceptional students. Madridge Journal of Behavioural and Social Sciences, 5(1), 86-88. https://doi.org/10.18689/mjbss-1000115
36. Mittal, U., Sai, S., Chamola, V., & Sangwan, D. (2024). A comprehensive review on generative ai for education. IEEE Access, 12, 142733-142759. https://doi.org/10.1109/access.2024.3468368
37. Ning, Y., Zhang, C., Xu, B., Zhou, Y., & Wijaya, T. T. (2024). Teachers’ AI-TPACK: Exploring the relationship between knowledge elements. Sustainability, 16(3), 978. https://doi.org/10.3390/su16030978
38. Oh, S. (2025). Integration of MATH41 and Generative AI in pre-service mathematics teacher education: An empirical study on lesson design competency. IEEE Access, 13, 128959-128973. https://doi.org/10.1109/access.2025.3586593
39. Opoku, M., Nketsia, W., Amponteng, M., Mprah, W., & Kumi, E. (2023). Attitudes and self-efficacy of preservice teachers toward teaching gifted and talented students. Journal for the Education of the Gifted, 46, 167- 193. https://doi.org/10.1177/01623532231162673
40. Özcan, S., Kukul, V., & Karataş, S. (2016). Dijital hikâyeler için dereceli değerlendirme ölçeği. 10th International Computer and Instructional Technologies Symposium (ICITS) Bildiri Kitabı, 118–126.
41. Palmieri, S., Lotti, G., Bisson, M., D’Ascenzi, E., & Spinò, C. (2025). Fostering embodied and attitudinal change through immersive storytelling: A hybrid evaluation approach for sustainability education. Sustainability, 17(17), 7885. https://doi.org/10.3390/su17177885
42. Parsons, S., & Kovshoff, H. (2025). ‘I am’Digital Stories as a praxeological methodology for supporting the voices and transitions of autistic children. International Journal of Qualitative Methods, 24, 16094069251355986. https://doi.org/10.1177/16094069251355986
43. Pfeiffer, S. I., Maralani, F. M., & Prado, R. M. (2025). The often perplexing and challenging work with the twice-exceptional student. Academia Mental Health and Well-Being, 2(4),1-9. https://doi.org/10.20935/MHealthWellB7990
44. Reis, S. M., Baum, S. M., & Burke, E. (2014). An operational definition of twice-exceptional learners: Implications for gifted education. Gifted Child Quarterly, 58(3), 217–230. https://doi.org/10.1177/0016986214534976
45. Robin, B. (2006, March). The educational uses of digital storytelling. In Society for information technology & teacher education international conference (pp. 709-716). Association for the Advancement of Computing in Education (AACE).
46. Robinson, D., & Young, D. (2020). The relationship between teachers’ inclusion-related knowledge, skills, and attitudes and student outcomes: A review of recent literature. Exceptionality Education International, 29(2), 18-41. https://doi.org/10.5206/eei.v29i2.9400
47. Sarıca, H. Ç. (2023). Emotions and digital storytelling in the educational context: A systematic review. Review of Education, 11(3), e3430. https://doi.org/10.1002/rev3.3430
48. Smeets, K., Rohaan, E., Peijnenburg, J., Samsen-Bronsveld, E., & Bakx, A. (2023). Elementary teachers’ knowledge, attitude, and professional development needs concerning gifted students and their educational needs in the Netherlands. Gifted and Talented International, 38, 91- 106. https://doi.org/10.1080/15332276.2023.2237553
49. Sun, Y., & Huang, Y. (2025). Exploring the role of generative AI in collaborative lesson planning for pre‐service teachers. Journal of Computer Assisted Learning, 41(4), e70098. https://doi.org/10.1111/jcal.70098
50. Şakar, S., & Baloğlu, M. (2025). An investigation of studies on twice exceptionality in Türkiye. Ankara Üniversitesi Eğitim Bilimleri Fakültesi Özel Eğitim Dergisi, 26(2), 253-271. https://doi.org/10.21565/ozelegitimdergisi.1415769
51. Şen, E. Ö. (2024). Creating digital storytelling as digital materials in mathematics education. Journal of Qualitative Research in Education, 40, 55-81. https://doi.org/10.14689/enad.40.1965
52. Teo, Y.-X., & Geuan, J. W. (2025). Integrating animation and ımmersive media into educational storytelling: A Mixed-method classroom study. International Journal of Creative Multimedia, 6(2), 185–201. https://doi.org/10.33093/ijcm.2025.6.2.9
53. van den Berg, G., & du Plessis, E. (2023). ChatGPT and Generative AI: possibilities for its contribution to lesson planning, critical thinking and openness in teacher education. Education Sciences, 13(10), 998. https://doi.org/10.3390/educsci13100998
54. Yakut, A. D., & Akgül, S. (2022). Pre-service special education teachers’ perceptions of competence, willingness of working, and challenges of working with respect to subfields of special education. Educational Academic Research, 47, 41-54. https://doi.org/10.5152/AUJKKEF.2022.1028595
55. Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024). Promises and challenges of generative artificial intelligence for human learning. Nature Human Behaviour, 8, 1839- 1850. https://doi.org/10.1038/s41562-024-02004-5
56. Yenioğlu, S., Melekoğlu, M., & Yenioğlu, B. (2022). A single-subject case study of twice exceptionality. Gifted Education International, 38, 256- 272. https://doi.org/10.1177/02614294211064772
57. Yıldırım, A., & Şimşek, H. (2021). Sosyal bilimlerde nitel araştırma yöntemleri (12. bs.). Seçkin Yayıncılık. Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Sage Publications.
58. Zhang, Y., Tian, H. & Lu, J. (2025). The relationship between higher-order thinking and problem-solving skills development among pre-service teachers using generative AI: an analysis based on moderated mediation. BMC Psychology, 13, 1094. https://doi.org/10.1186/s40359-025-03404-6