SavedAdd your journal

Journals / Bartın Üniversitesi Eğitim Fakültesi Dergisi / 2026 / Volume: 14 Issue: 2

Integrating Generative AI in Education: Implications for School Leadership from Policy Documents Through Bolman and Deal's Four Frame Theory

Ali Duran(TC MİLLİ EĞİTİM BAKANLIĞI AMASYA)0000-0001-6132-4066
Uğur Ferhat Ermiş(AMASYA ÜNİVERSİTESİ)0000-0003-4862-3592
Pages
—
Publication Date
2025-04-30
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This article examinesthe implications, particularly focusing on the roles and responsibilities of school leaders through Bolman and Deal's Four Frame Theory, including Structural, Human Resources, Political, and Symbolic frames.Adopting a qualitative research design based on document analysis, the study analyzes policy documents selected for their relevance to Gen-AI in education and influence on educational leadership.The findings revealed that Bolman and Deal’s Four Frame Theory offers a comprehensive structure for integrating Gen-AI technologies in education.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:As generative artificial intelligence (Gen-AI) technologies continue to evolve, it becomes increasingly important for educators to effectively leverage their benefits within educational settings.The integration of artificial intelligence (Gen-AI) into educationrepresents a significant shift in teaching, learning, and administrative practices.
📊
Key Findings & Data:The Political Frame addresses the strategic negotiation and stakeholder collaboration necessary for Gen-AI integration.
💡
Conclusion & Impact:This article examinesthe implications, particularly focusing on the roles and responsibilities of school leaders through Bolman and Deal's Four Frame Theory, including Structural, Human Resources, Political, and Symbolic frames.Adopting a qualitative research design based on document analysis, the study analyzes policy documents selected for their relevance to Gen-AI in education and influence on educational leadership.The findings revealed that Bolman and Deal’s Four Frame Theory offers a comprehensive structure for integrating Gen-AI technologies in education.
🔬Design:Review
📍Scope:Comprehensive Sample
⚙️Variables:AI integration · enhancing AI competencies · foster ethical AI

Abstract

As generative artificial intelligence (Gen-AI) technologies continue to evolve, it becomes increasingly important for educators to effectively leverage their benefits within educational settings.The integration of artificial intelligence (Gen-AI) into educationrepresents a significant shift in teaching, learning, and administrative practices. This article examinesthe implications, particularly focusing on the roles and responsibilities of school leaders through Bolman and Deal's Four Frame Theory, including Structural, Human Resources, Political, and Symbolic frames.Adopting a qualitative research design based on document analysis, the study analyzes policy documents selected for their relevance to Gen-AI in education and influence on educational leadership.The findings revealed that Bolman and Deal’s Four Frame Theory offers a comprehensive structure for integrating Gen-AI technologies in education. The Structural Frame highlights the need for leadership adaptation, socio-economic considerations, and R&D infrastructure development. The Human Resources Frame highlights the need for staff training, competency enhancement, and Gen-AI-focused educational initiatives. The Political Frame addresses the strategic negotiation and stakeholder collaboration necessary for Gen-AI integration. Finally, the Symbolic Frame underscores the importance of shaping cultural narratives, promoting ethical Gen-AI use, integrating Gen-AI into curricula, and fostering critical Gen-AI literacy. Based on the findings, a prominent conclusion is that school leaders are pivotal in ethically integrating Gen-AI in alignment with global standards and societal values. The study also addresses several limitations and offers recommendations for future research.

🔖

Cite This Article

Duran, A., Ermiş, U. F. (2025). Integrating Generative AI in Education: Implications for School Leadership from Policy Documents Through Bolman and Deal's Four Frame Theory. Bartın Üniversitesi Eğitim Fakültesi Dergisi, Volume: 14 Issue: 2. https://doi.org/10.14686/buefad.1435086

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (37)

  1. Arslan, İ., & Yiğit, M. F. (2024). A review of studies on school administrators' technology leadership in Türkiye. Kastamonu Eğitim Dergisi, 32(1), 51-70. https://doi.org/10.24106/kefdergi.1426474
  2. Asdal, K., & Reinertsen, H. (2021). Doing document analysis: A practice-oriented method. Sage.
  3. Baidoo-Anu, D., & Owusu Ansah, L. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
  4. Bauchner, E. (2014). Document analysis. Mason Crest.
  5. Baxter, J., Floyd, A., & Jewitt, K. (2023). Pandemic, a catalyst for change: Strategic planning for digital education in English secondary schools, before during and post Covid. British Educational Research Journal, 49(2), 329-351. https://doi.org/10.1002/berj.3845
  6. Bolman, L. G., & Deal, T. E. (2014). How great leaders think: The art of reframing. Jossey-Bass.
  7. Bolman, L. G., & Deal, T. E. (2017). Reframing organizations: Artistry, choice, and leadership (6th ed.). Jossey-Bass.
  8. Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 1-25. https://doi.org/10.1186/s41239-023-00408-3
  9. Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies, and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 1-17. https://doi.org/10.1080/10494820.2023.2253861
  10. Crawford, J., Cowling, M., & Allen, K. A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching & Learning Practice, 20(3), 02. https://doi.org/10.53761/1.20.3.02
  11. Dexter, S., & Richardson, J. W. (2020). What does technology integration research tell us about the leadership of technology?. Journal of Research on Technology in Education, 52(1), 17-36. https://doi.org/10.1080/15391523.2019.1668316
  12. Farzan, M. (2023). Towards ethical AI in schools: An educator's guide to responsible implementation. Social Sciences Spectrum, 2(1), 97-103.
  13. Fleming-May, R. A., & Douglass, K. (2014). Framing librarianship in the academy: An analysis using Bolman and Deal’s model of organizations. College & Research Libraries, 75(3), 381-405. https://doi.org/10.5860/crl13-432
  14. Foltynek, T., Bjelobaba, S., Glendinning, I., Khan, Z. R., Santos, R., Pavletic, P., & Kravjar, J. (2023). ENAI recommendations on the ethical use of Artificial Intelligence in education. International Journal for Educational Integrity, 19(12). https://doi.org/10.1007/s40979-023-00133-4
  15. Fullan, M., Azorín, C., Harris, A., & Jones, M. (2023). Artificial intelligence and school leadership: challenges, opportunities and implications. School Leadership & Management, 1–8. https://doi.org/10.1080/13632434.2023.2246856
  16. García-Peñalvo, F. J. (2023). La percepción de la Inteligencia Artificial en contextos educativos tras el lanzamiento de ChatGPT: disrupción o pánico [The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: Disruption or Panic?] Education in the Knowledge Society (EKS), 24, 1-9. https://doi.org/10.14201/eks.31279
  17. Groenland, E., Dana, L. (2020). Qualitative methodologies and data collection methods: Toward increased rigour in management research. World Scientific Publishing Company.
  18. Holmes, W. T. (2023). Motivating language theory, the four frames and change: An infused model. Development and Learning in Organizations, 38(2), 16-19. https://doi.org/10.1108/DLO-04-2023-0105
  19. Holmes W., Bialik M., Fadel C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. The Center for Curriculum Redesign.
  20. Jauhiainen, J. S., & Guerra, A. G. (2023). Generative AI and ChatGPT in school children’s education: Evidence from a school lesson. Sustainability, 15(18), 14025. 1-22 https://doi.org/10.3390/su151814025
  21. Kilag, O. K. T., Uy, F. T., Abendan, C. F. K., & Malbas, M. H. (2023). Teaching leadership: an examination of best practices for leadership educators. Science and Education, 4(7), 430-445.
  22. Linder, G., & Zhang, L. (2020). A look into organising in the era of AI [Master’s Thesis, Lund University].
  23. Mustafa, D. (2023). Smart classrooms bright minds: The intersection of education and artificial intelligence. Journal Environmental Sciences and Technology, 2(1), 150-158.
  24. Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2 (100020) https://doi.org/10.1016/j.caeai.2021.100020
  25. Photinopoulos, A. (2021). Bolman and Deal’s four frames and the Quality Standards Academic Committee: An analysis of select past and future leadership decisions [Master’s Thesis, University of Alberta].
  26. Rawlinson, D. (2015). An applied organizational analysis of school factors affecting technology integration within the context of literacy instruction [Doctoral Dissertation, University of Central Florida].
  27. Reyneke, J. A. (2023, June 18). Best practices and future directions in AI-integration for elementary schools. Medium. https://medium.com/@janelreyneke/best-practices-and-future-directions-in-ai-integration-for-elementary-schools-176b98e8c6c9
  28. Seiradakis, E. V. (2023). School leaders’ perceptions on barriers for creating inclusive intercultural environments and potential generative AI benefits. European Journal of Alternative Education Studies, 8(4). https://doi.org/10.46827/ejae.v8i4.5154
  29. Sherman, W. H., & Crum, K. S. (2007). Student achievement: Elementary principal catalysts-instructional leadership in reading. International Journal of Educational Reform, 16(4), 390–410. doi:10.1177/105678790701600405
  30. Sornberger, D. (2023, August 4). How AI can reshape the face of school leadership. https://leadinglearninglab.com/how-ai-can-reshape-the-face-of-school-leadership/
  31. Tabish, F. (2023). AI in education: A double-edged sword of innovation and ethical dilemmas. Social Sciences Spectrum, 2(1), 82-88. https://sss.org.pk/index.php/sss/article/view/22/21
  32. Tyson, M. M., & Sauers, N. J. (2021). School leaders’ adoption and implementation of artificial intelligence. Journal of Educational Administration, 59(3), 271-285. https://doi.org/10.1108/JEA-10-2020-0221
  33. Wilson, D. R. (2018). Principals’ actions for influencing technology integration within small city school districts. Sage Graduate School [Doctoral Dissertation, The Sage Colleges].
  34. Wu, Y. (2023). Integrating generative AI in education: How ChatGPT brings challenges for future learning and teaching. Journal of Advanced Research in Education, 2(4), 6-10. https://doi.org/10.56397/JARE.2023.07.02
  35. Yilmaz, Y., Ruan, B., Thomas, P., Tran, V., & Chan, T. M. (2021). Reframing organizations in the digital age: A qualitative study exploring institutional social media adoption involving emergency physicians and other researchers. F1000Research, 10(1048), 1-30. https://doi.org/10.12688/f1000research.73439.2
  36. Yu, H., & Guo, Y. (2023). Generative artificial intelligence empowers educational reform: current status, issues, and prospects. Frontiers in Education, 8,1-10. https://doi.org/10.3389/feduc.2023.1183162
  37. Yu, H., & Guo, Y. (2023). Generative artificial intelligence empowers educational reform: current status, issues, and prospects. Frontiers in Education, 8,1-10. https://doi.org/10.3389/feduc.2023.1183162