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

Year 2025, Issue: 75, 306 - 325, 31.07.2025
https://doi.org/10.21764/maeuefd.1631818

Abstract

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.

References

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  • 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.
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  • 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.
  • 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.
  • Genç, E., & Ata, F. (2020). Teachers' attitudes and competencies towards artificial intelligence in education. Journal of Education and Future, 15(1), 79-93.
  • 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.
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  • Habib, H., & Janae, J. (2024). Breaking barriers: How AI is transforming special education classrooms. Bulletin of Engineering Science and Technology, 1(02), 86-108.
  • 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
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Özel eğitim öğretmenlerinin yapay zekâ destekli Web 2.0 araçlarını kullanım durumları

Year 2025, Issue: 75, 306 - 325, 31.07.2025
https://doi.org/10.21764/maeuefd.1631818

Abstract

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.

References

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  • Albion, P. (2008). Web 2.0 in teacher education: Two imperatives for action. Computers in the Schools, 25(3/4), 181–198.
  • 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
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  • 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.
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  • 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.
  • 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
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  • Creswell, J. W. (2017). Nitel yöntemler. S. B. Demir (Ed.), Araştırma deseni: Nitel, nicel ve karma yöntem yaklaşımları içinde (s.183-213). Eğiten Kitap.
  • 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
  • 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
  • Elmas, R., & Geban, Ö. (2012). Web 2.0 tools for 21st century teachers. International Online Journal of Educational Sciences, 4(1), 243-254.
  • 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
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • Genç, E., & Ata, F. (2020). Teachers' attitudes and competencies towards artificial intelligence in education. Journal of Education and Future, 15(1), 79-93.
  • 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.
  • Guba, E. G., & Lincoln, Y. S. (1982). Epistemological and methodological bases of naturalistic inquiry. Educational Communication and Technology Journal, 30(4), 233-252.
  • Habib, H., & Janae, J. (2024). Breaking barriers: How AI is transforming special education classrooms. Bulletin of Engineering Science and Technology, 1(02), 86-108.
  • 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
  • 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
  • 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
  • Kaya, B. N. (2023). Yapay zekâ tabanlı dil modelleri ile ilgili öğretmen görüşlerinin incelenmesi (Yayınlanmamış yüksek lisans tezi). Düzce Üniversitesi, Düzce.
  • 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.
  • 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
  • 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
  • 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
  • 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
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There are 57 citations in total.

Details

Primary Language Turkish
Subjects Mental Disability Education, Autism and Spectrum Disorder Education, Special Education and Disability (Other)
Journal Section Research Article
Authors

Baran Yaşar 0000-0003-1857-6078

Sezgin Vuran 0000-0001-7658-1102

Submission Date February 2, 2025
Acceptance Date July 14, 2025
Publication Date July 31, 2025
Published in Issue Year 2025 Issue: 75

Cite

APA Yaşar, B., & Vuran, S. (2025). Özel eğitim öğretmenlerinin yapay zekâ destekli Web 2.0 araçlarını kullanım durumları. Mehmet Akif Ersoy University Journal of Education Faculty(75), 306-325. https://doi.org/10.21764/maeuefd.1631818

Mehmet Akif Ersoy University Journal of Education Faculty

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