Use of AI-powered Web 2.0 tools by special education teachers

Öz

Abstract: Artificial intelligence has brought significant transformation to various aspects of life, including education. AI-supported tools can facilitate many important tasks in educational environments, such as content creation, assessment, and material development. Particularly, AI’s ability to personalize materials can offer substantial contributions to individuals with different needs. However, it has been observed that teachers do not use these tools sufficiently and have not integrated them into their educational environments. This study aims to determine the usage status of AI-supported tools among special education teachers, the challenges they face in using these tools, and their needs in this regard. The study employs a phenomenological design, a qualitative research method. Data was collected from special education teachers through a semi-structured interview form. The collected data were analyzed using content analysis and thematic analysis, which are qualitative analysis methods. According to the research findings, it was found that the special education teachers participating in the study were not well-informed about AI-supported tools and had not integrated them into special education. The lack of knowledge about AI-supported tools also made their use more difficult. Furthermore, the findings highlight that teachers need training on the use of AI-supported tools in special education, and that such training should be conducted face-to-face and in workshop formats.

Anahtar Kelimeler

• Artificial intelligence
• artificial intelligence-supported tools
• web 2.0
• special education

Özel eğitim öğretmenlerinin yapay zekâ destekli Web 2.0 araçlarını kullanım durumları

Öz

Özet: Yapay zekâ, hayatın tüm alanında olduğu gibi eğitimde de önemli boyutlarda dönüşüm sağlamıştır. Yapay zekâ destekli araçlar eğitim ortamlarında içerik hazırlama, değerlendirme yapma ve materyal oluşturma gibi birçok önemli görevi kolaylaştırabilir. Özellikle yapay zekânın, materyalleri bireyselleştirebilmeye olanak sağlaması, farklı gereksinimleri olan bireylere önemli katkılar sunabileceği söylenebilir. Ancak öğretmenlerin bu araçları, yeterince kullanmadıkları ve bu araçları eğitim ortamlarına entegre etmedikleri görülmektedir. Bu araştırmada özel eğitim öğretmenlerinin yapay zekâ destekli araçları kullanım durumları, bu araçları kullanmada öğretmenlerin yaşadıkları güçlükler ve öğretmenlerin bu konudaki ihtiyaçlarının belirlenmesi amaçlanmıştır. Bu araştırmada nitel araştırıma yöntemlerinde olgubilim (fenomenoloji) deseni kullanılmıştır. Yarı yapılandırılmış görüşme formu aracılığıyla özel eğitim öğretmenlerinden veriler toplanmıştır. Toplanan veriler nitel analiz yöntemlerinden içerik analizi ve tematik analiz yöntemi kullanılarak analiz edilmiştir. Araştırma bulgularına göre bu araştırmaya katılan özel eğitim öğretmenlerinin yapay zekâ destekli araçlar ile ilgili pek bilgi sahibi olmadıkları ve bu araçları özel eğitime entegre etmedikleri görülmektedir. Yapay zekâ destekli araçlar ile ilgili bilgi yetersizlikleri, onların bu araçları kullanımlarını da zorlaştırdığı görülmektedir. Ayrıca araştırma bulgularında, yapay zekâ destekli araçların özel eğitimde kullanımı ile ilgili öğretmenlerin eğitimlere ihtiyaç duydukları ve eğitimlerin yüz yüze ve atölye şeklinde olması gerektiği vurgulanmaktadır.

Anahtar Kelimeler

• Yapay zekâ
• yapay zekâ destekli araçlar
• web 2.0
• özel eğitim

Kaynakça

1. Abu Mukh, Y. N., Abd-Rabo, A. M., & Tarteer, S. (2024). Computer competencies needed for implementing artificial intelligence in special education schools from the perspective of pre-service teachers. Trends in Higher Education, 3(3), 602-622.
2. Albion, P. (2008). Web 2.0 in teacher education: Two imperatives for action. Computers in the Schools, 25(3/4), 181–198.
3. Al-Zahrani, A. M., & Alasmari, T. M. (2024). Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications. Humanities and Social Sciences Communications, 11, 912. https://doi.org/10.1057/s41599-024-03432-4
4. Amerikan Psikoloji Derneği (APA) (2020). APA Stil JARS: Dergi Makalesi Raporlama Standardı-https://apastyle.apa.org/jars/qual-table-1.pdf.
5. Araújo, S., Aguiar, M. (2023). Simplifying specialized texts with AI: A ChatGPT-based learning scenario. In Mesquita, A., Abreu, A., Carvalho, J. V., Santana, C., de Mello, C.H.P. (Eds) Perspectives and trends in education and technology. ICITED 2023. Smart Innovation, Systems and Technologies, vol 366. Springer, Singapore. https://doi.org/10.1007/978-981-99-5414-8_55
6. Basilotta-Gómez-Pablos, V., Matarranz, M., Casado-Aranda, L. A., & Otto, A. (2022). Teachers’ digital competencies in higher education: A systematic literature review. International Journal of Educational Technology in Higher Education, 19(1), 1-16.
7. Billingsley, B., Israel, M., & Smith, S. J. (2011) Supporting new special education teachers: How online resources and web 2.0 technologies can help. Teaching Exceptional Children, 43(5), 20-29.
8. Bower, M. (2012). A framework for developing pre-service teachers’ web 2.0 learning design capabilities. In P. C. Mims, & K. A. Persichitte (Eds.), Developing technology-rich teacher education programs: Key issues (pp.58–76). IGI Global.

9. Boyle, J. R., & Kennedy, M. J. (2019). Innovations in Classroom Technology for Students with Disabilities. Intervention in School and Clinic, 55(2), 67-70. https://doi.org/10.1177/1053451219837716
10. Büyüköztürk, Ş., Çakmak, E. K., Akgün, O. E., Karadeniz, S. ve Demirel, F. (2021). Bilimsel araştırma yöntemleri. Pegem Akademi.
11. Choi, S., Jang, Y., & Kim, H. (2023). Influence of pedagogical beliefs and perceived trust on teachers’ acceptance of educational artificial intelligence tools. International Journal of Human–Computer Interaction, 39(4), 910-922.
12. 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
13. Creswell, J. W. (2016). Nitel araştırma yöntemleri: Beş yaklaşıma göre nitel araştırma ve araştırma deseni. M. Bütün ve S. B. Demir (Çev.). Siyasal Kitabevi Yayınları.
14. Creswell, J. W. (2017). Nitel yöntemler. S. B. Demir (Ed.), Araştırma deseni: Nitel, nicel ve karma yöntem yaklaşımları içinde (s.183-213). Eğiten Kitap.
15. Davulcu, G., & Tezer, M. (2020). An evaluation of the news about people with disabilities published in the written media. Contemporary Educational Researches Journal, 10(1), 7- 20. https://doi.org/10.18844/cerj.v10i1.4610
16. El-Adl, A., & Alkharusi, H. (2020). Relationships between self-regulated learning strategies, learning motivation and mathematics achievement. Cypriot Journal of Educational Sciences, 5(1), 104-111. https://doi.org/10.18844/cjes.v15i1.4461
17. Elmas, R., & Geban, Ö. (2012). Web 2.0 tools for 21st century teachers. International Online Journal of Educational Sciences, 4(1), 243-254.
18. Ertmer, P. A., Ottenbreit-Leftwich, A. T., Sadik, O., Sendurur, E., & Sendurur, P. (2012). Teacher beliefs and technology integration practices: A critical relationship. Computers & Education, 59(2), 423-435. https://doi.org/10.1016/j.compedu.2012.02.001
19. Eser, M. (2020). Öğretmen adaylarının web 2.0 hızlı içerik geliştirme öz-yeterlik inançlarının incelenmesi. Öğretim Teknolojisi ve Hayat Boyu Öğrenme Dergisi, 1(1), 122-137.
20. Fernández-Batanero, J. M., Montenegro-Rueda, M., Fernández-Cerero, J., & García-Martínez, I. (2022). Digital competences for teacher professional development. Systematic review. European Journal of Teacher Education, 45(4), 513-531.
21. Fletcher, G., Levin, D., Lipper, K., & Leichty, R. (2014). The accessibility of learning content for all students, including students with disabilities, must be addressed in the shift to digital instructional materials. SETDA Policy Brief. State Educational Technology Directors Association.
22. Galindo-Domínguez, H., Delgado, N., Losada, D., & Etxabe, J. M. (2024). An analysis of the use of artificial intelligence in education in Spain: The in-service teacher’s perspective. Journal of Digital Learning in Teacher Education, 40(1), 41-56.
23. García-Peñalvo, F. J., & Corell, A. (2020). The COVID-19: The enzyme of the digital transformation of teaching or the reflection of a methodological and competence crisis in higher education? Campus Virtuales, 9(2), 83-98.
24. Genç, E., & Ata, F. (2020). Teachers' attitudes and competencies towards artificial intelligence in education. Journal of Education and Future, 15(1), 79-93.
25. Giorgi, A., Giorgi, B., & Morley, J. (2017). The descriptive phenom¬enological psychological method. In C. Willig, & W. S. Rogers (Eds.), The sage handbook of qualitative research in psychology (pp. 176–192). Sage.
26. Guba, E. G., & Lincoln, Y. S. (1982). Epistemological and methodological bases of naturalistic inquiry. Educational Communication and Technology Journal, 30(4), 233-252.
27. Habib, H., & Janae, J. (2024). Breaking barriers: How AI is transforming special education classrooms. Bulletin of Engineering Science and Technology, 1(02), 86-108.
28. Huang, X. (2021). Aims for cultivating students’ key competencies based on artificial intelligence education in China. Education and Information Technologies, 26, 5127–5147. https://doi.org/10.1007/s10639-021-10530-2
29. İbrahim, N., Chandra, A. Y., Saari, E. M., Prasetyaningrum, P. T., & Pratama, I. (2023). The effectiveness of Web 2.0 tools training workshop using Canva and Figma in developing creative visual content. Asian Journal of Assessment in Teaching and Learning, 13(2), 35-45. https://doi.org/10.37134/ajatel.vol13.2.4.2023
30. Karakuş, N. ve Er, Z. (2021). Türkçe öğretmeni adaylarının web 2.0 araçlarının kullanımıyla ilgili görüşleri. IBAD Sosyal Bilimler Dergisi, 9, 177-197. https://doi.org/10.21733/ibad.837184
31. Kaya, B. N. (2023). Yapay zekâ tabanlı dil modelleri ile ilgili öğretmen görüşlerinin incelenmesi (Yayınlanmamış yüksek lisans tezi). Düzce Üniversitesi, Düzce.
32. Korucu, A. T. ve Çakır, H. (2015). Dinamik web teknolojilerine ile geliştirilen işbirlikli öğrenme ortamını kullanan öğretmen adaylarının görüşleri. Adıyaman Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 2015(19), 221-254.
33. Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022). Artificial intelligence literacy in higher and adult education: A scoping literature review. Computers and Education: Artificial Intelligence, 3, 100101. https://doi.org/10.1016/j.caeai.2022.100101
34. Leaton Gray, S. (2020). Artificial intelligence in schools: Towards a democratic future. London Review of Education, 18(2), 163-177. https://doi.org/10.18546/LRE.18.2.04
35. Mayer, D., & Oancea, A. (2021). Teacher education research, policy and practice: Finding future research directions. Oxford Review of Education, 47(1), 1-7. https://doi.org/10.1080/03054985.2020.1856820
36. McKnight, K., O'Malley, K., Ruzic, R., Horsley, M. K., Franey, J. J., & Bassett, K. (2016). Teaching in a digital age: How educators use technology to improve student learning. Journal of Research on Technology in Education, 48(3), 194-211. https://doi.org/10.1080/15391523.2016.1175856
37. Mikeladze, T., Meijer, P. C., & Verhoeff, R. P. (2024). A comprehensive exploration of artificial intelligence competence frameworks for educators: A critical review. European Journal of Education, 59(3), e12663. https://doi.org/10.1111/ejed.12663
38. Miles, M, B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded Sourcebook. (2nd ed). Sage
39. Najibufahmi, M., Fitri, A., Azizah, D., Utami, R., Hidayah, N., Fajar, D. A., Kuncoro, S., & Rencani, K. D. (2025). Pendampingan penyusunan perangkat pembelajaran berbasis Canva AI pada MGMP Matematika SMP. Surya Abdimas, 9(1), 26–35. https://doi.org/10.37729/abdimas.v9i1.5270
40. Nezhyva, L. L., Palamar, S. P., & Semenii, N. O. (2024). The using of digital tools in the project activities of students of pedagogical specialties of higher education institutions. Information Technologies and Learning Tools, 101(3), 71-85.
41. Okolo, C. M., Englert, C. S., Bouck, E. C., & Heutsche, A. (2014). The impact of professional development on teachers’ technology integration practices for students with disabilities: A mixed-methods study. Journal of Special Education Technology, 29(4), 17–32. https://doi.org/10.1177/01626434140290010
42. Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27, 7893–7925. https://doi.org/10.1007/s10639-022-10925-9
43. Özçınar, Z., Sakhieva, R., Pozharskaya, E., Popova, O., Melnik, M. ve Matvienko, V. (2020). Öğrencilerin web 2.0 araçları ve eğitim uygulamalarına ilişkin algıları. Uluslararası Öğrenmede Gelişen Teknolojiler Dergisi (iJET), 15 (23), 220-233.
44. Patton, M. K. (2018). Nitel araştırma ve değerlendirme yöntemleri. M. Bütün ve S. B. Demir (Çev.). Pegem Akademi Yayıncılık.
45. Riestra-González, M., Paule-Ruíz, M. D. P., & Ortin, F. (2021). Massive LMS log data analysis for the early prediction of course-agnostic student performance. Computers & Education, 163, 104-108. https://doi.org/10.1016/j.compedu.2020.104108
46. Ruci, W. H. N., Arief, M., Wakhid, N., Winarno, W., Mutmainah, S., & Pradipta, D. A. (2025, Şubat). Artificial intelligence for creative project in small business. International Joint Conference on Arts and Humanities 2024 (IJCAH 2024) (ss. 1347-1351). Atlantis Press. https://doi.org/10.2991/978-2-38476-317-7_131
47. Starks, A. C., & Reich, S. M. (2023). “What about special ed?”: Barriers and enablers for teaching with technology in special education. Computers & Education, 193, 104665. https://doi.org/10.1016/j.compedu.2022.104665
48. Tenenbaum, J. M. (2006). AI meets Web 2.0: Building the web of tomorrow, today. AI Magazine, 27(4), 47. https://doi.org/10.1609/aimag.v27i4.1909
49. Theodorou, P., & Meliones, A. (2019). Developing apps for people with sensory disabilities and implications for technology acceptance models. Global Journal of Information Technology: Emerging Technologies, 9(2), 33-40. https://doi.org/10.18844/gjit.v9i2.4431
50. Tondeur, J., Van Braak, J., Ertmer, P. A., & Ottenbreit-Leftwich, A. (2017). Understanding the relationship between teachers’ pedagogical beliefs and technology use in education: A systematic review of qualitative evidence. Educational Technology Research and Development, 65, 555-575. https://doi.org/10.1007/s11423-016-9481-2
51. Troussas, C., Krouska, A., & Virvou, M. (2020). Using a multi-module model for learning analytics to predict learners’ cognitive states and provide tailored learning pathways and assessment. In Machine Learning Paradigms (pp. 9–22). Springer.
52. Vellonen, V., Sointu, E., Valtonen, T., & Tukiainen, M. (2025). Pre-service special education teachers’ perceptions of applying technologies in education. Journal of Special Education Technology, 0(0). https://doi.org/10.1177/01626434251314044
53. Wei, Y., Yang, Q., Chen, J., & Hu, J. (2018). The exploration of a machine learning approach for the assessment of learning styles changes. Mechatronic Systems and Control, 46(3), 121–126. https://doi.org/10.2316/journal.201.2018.3.201-2979
54. Yıldırım, A. ve Şimşek, H. (2021). Nitel araştırma yöntemleri. Seçkin Yayınları.
55. Yue, M., Jong, M. S. Y., & Ng, D. T. K. (2024). Understanding K–12 teachers’ technological pedagogical content knowledge readiness and attitudes toward artificial intelligence education. Educational Technology & Society, 1-32. https://doi.org/10.1007/s10639-024-12621-2
56. Zhou, L., Gao, L., & Liu, J. (2020). AIpowered assistive technology for special education: A systematic review. Assistive Technology, 32(4), 198–208.
57. Zamora, J. T., & Zamora, J. J. M. (2022). 21st Century Teaching Skills and Teaching Standards Competence Level of Teacher. International Journal of Learning, Teaching and Educational Research, 21(5), 220-238.