Experiences and Evaluations of Academics on the Use of Artificial Intelligence Tools

Abstract

“This research examines how academics in the social sciences perceive and assess the application of artificial intelligence (AI) technologies in their academic work and educational processes. The study collected qualitative data through in-depth interviews using the conceptual framework of the Technology Acceptance Model. Analysis of the interviews revealed that academics generally exhibit a positive attitude towards AI tools and find them useful for increasing efficiency, saving time, and assisting with various academic/educational tasks. Academic competition and the influence of colleagues are social factors encouraging AI adoption. However, concerns were also raised regarding the quality and reliability of AI outputs (hallucinations, bias) and ethical issues (plagiarism, dependence, reduction of human skills). The cost of paid tools and ambiguity regarding ethical use are also perceived as challenges. Academics emphasize that AI is a supplementary tool and its outputs must be critically evaluated.

Keywords

• Artificial intelligence
• Academy
• Education
• In-depth interview
• Technology acceptance model

Yapay Zekâ Araçlarının Kullanımına İlişkin Akademisyenlerin Deneyim ve Değerlendirmeleri

Abstract

Bu araştırma, sosyal bilimler alanında görev yapan akademisyenlerin yapay zekâ (YZ) teknolojilerini akademik çalışmalarında ve eğitim süreçlerinde nasıl deneyimlediklerini ve değerlendirdiklerini incelemektedir. Çalışma, Teknoloji Kabul Modeli'nin kavramsal çerçevesini kullanarak derinlemesine görüşmeler yoluyla nitel veriler toplamıştır. Görüşmelerin analizi, akademisyenlerin YZ'ye karşı genellikle olumlu bir tutum sergilediğini ve bu araçları verimliliği artırma, zaman tasarrufu sağlama ve çeşitli akademik/eğitimsel görevlerde faydalı bulduklarını ortaya koymuştur. Akademik rekabet ve meslektaşların etkisi YZ kullanımını teşvik eden sosyal faktörlerdendir. Ancak, YZ'nin çıktı kalitesine, güvenilirliğine (halüsinasyonlar, yanlılık) ve etik sorunlara (intihal, bağımlılık, insani becerilerin azalması) dair endişeler de dile getirilmiştir. Ücretli araçların maliyeti ve etik kullanıma yönelik belirsizlikler de zorluk olarak görülmektedir. Akademisyenler, YZ'nin destekleyici bir araç olduğunu ve çıktılarının eleştirel bir şekilde değerlendirilmesi gerektiğini vurgulamaktadır.

Keywords

• Yapay zekâ
• Akademi
• Eğitim
• Derinlemesine görüşme
• Teknoloji kabul modeli

References

1. Baloğlu, G., & Çakalı, K. R. (2023). Is Artificial Intelligence a New Threat to the Academic Ethics?: Enron Scandal Revisited By ChatGPT. İşletme, 4(1), 143-165.
2. Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., Pham, P., Chong, S. W., & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: a call for increased ethics, collaboration, and rigour. International Journal of Educational Technology in Higher Education, 21(4), s. 1-44.
3. Chiu, T. K. (2024). he impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney. Interactive Learning Environments, 32(10), 6187-6203.
4. Cotton, D. R., Cotton, P. A., & Shipway, R. J. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in education and teaching international, 61(2), 228-239.
5. Creswell, J. W., & Creswell, D. J. (2021). Araştırma Tasarımı Nitel, Nicel ve Karma Yöntem Yaklaşımları. Ankara: Nobel.
6. Currie, G. M. (2023). Academic integrity and artificial intelligence: is ChatGPT hype, hero or heresy? Seminars in nuclear medicine, 53(5), 719-730.
7. Davis, F. D. (1989). ). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
8. Dergunova, Y., Aubakirova, R., Yelmuratova, B., Gulmira, T., Yuzikovna, P., & Antikeyeva, S. (2022). Artificial Intelligence Awareness Levels of Students. International Journal of Emerging Technologies in Learning, 17(18), s. 26-37.

9. Dogan, M. E., Dogan, T. G., & Bozkurt, A. (2023). The Use of Artificial Intelligence (AI) in Online Learning and Distance Education Processes: A Systematic Review of Empirical Studies. Appl. Sci., 13(3056).
10. Economist, T. (2025, 02 25). The danger of relying on OpenAI’s Deep Research. The Economist. https://www.economist.com/finance-and-economics/2025/02/13/the-danger-ofrelying- on-openais-deepresearch? utm_medium=cpc.adword.pd&utm_source=google&ppccampaignID=18151 738051&ppcadID=&utm_campaign=a.22brand_pmax&utm_content=conversion.dire ct-response.anon
11. Endert, A., Ribarsky, W., Turkay, C., William Wong, B. L., Nabney, I., Díaz Blanco, I., & Rossi, F. (2017). The State of the Art in Integrating Machine Learning into Visual Analytics. Computer Graphics Forum, 36, 458-486.
12. Erdem, E. (2024). Yapay uygulamalarının sosyal bilim alanında yapılan çalışmalarda uygulanabilirliği: Chatgpt, Bing ve Youchat örneği. İletişim Bilimi Araştırmaları Dergisi, 4(3), 218-234.
13. Habibi, A., Muhaimin, M., Danibao, B. K., Wibowo, Y. K., Wahyuni, S., & Octavia, A. (2023). ChatGPT in higher education learning: Acceptance and use. Computers and Education: Artificial Intelligence, 5(100190).
14. Hasan, M. R., Chowdhury, N. I., Rahman, M. H., Syed, M. A., & Ryu, J. (2024). Understanding AI Chatbot adoption in education: PLS-SEM analysis of user behavior factors.
15. Computers in Human Behavior: Artificial Humans, 2:2(100098).
16. Hsu, H.-P. (2023). Can Generative Artificial Intelligence Write an Academic Journal Article? Opportunities, Challenges, and Implications. Irish Journal of Technology Enhanced Learning, 7(2), 158-171.
17. Hu, K. (2023, 02 02). ChatGPT sets record for fastest-growing user base - analyst note. Reuters. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-userbase- analyst-note-2023-02-01/
18. Ünal, C., & Yıldırım, H. (2024). Türkiye’deki Akademisyenlerin Yapay Zekâ (YZ) Uygulama ve Araçlarını Kullanımları Hakkında Bir Araştırma. Sinop Üniversitesi Fen Bilimleri Dergisi Sinop Uni J Nat Sci, 9(1), s. 128-144.
19. Kıncal, R. Y. (2017). Bilimsel Araştırma Yöntemleri. Ankara: Nobel. Lee, D., Arnold, M., Srivastava , A., Plastow, K., Strelan, P., Ploeckl , F., Lekkas, D., & Palmer, E. (2024). The impact of generative AI on higher education learning and teaching: A study of educators’ perspectives. Computers and Education: Artificial Intelligence, 6(100221).
20. Livberber, T., & Ayvaz, S. (2023). The impact of Artificial Intelligence in academia: Views of Turkish academics on ChatGPT. Heliyon, 9(9).
21. Machová, K., Szabóova, M., Paralič, J., & Mičko, J. (2023). Detection of emotion by text analysis using machine learning. Frontiers in Psychology, 14(1190326).
22. Mah, D. K., & GroB, N. (2024). Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs. International Journal of Educational Technology in Higher Education, 21(58).
23. Mete, M. H. (2023). Sosyal Bilimlerde Büyük Veri Analitiği, Yapay Zeka ve Makine Öğreniminin Kullanımı. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 23(1), s. 99-120.
24. Morgan, D. L. (2023). Exploring the Use of Artificial Intelligence for Qualitative Data Analysis: The Case of ChatGPT. International Journal of Qualitative Methods, 22, https://doi.org/10.1177/16094069231211248.
25. Mou, X., Ding, X., He, Q., Wang, L., Liang, J., Zhang, X., Sun, L., Lin, J., Zhou, J., Huang, X., & Wei, Z. (2024). From Individual to Society: A Survey on Social Simulation Driven by Large Language Model-based Agents. arXiv preprint arXiv:2412.03563.
26. Nguyen, A., Hong, Y., Dang, B., & Huang, X. (2024). Human-AI collaboration patterns in AIassisted academic writing. Studies in Higher Education, 49(5), 847-864.
27. Nikolopoulou, K. (2024). Generative artificial intelligence in higher education: Exploring ways of harnessing pedagogical practices with the assistance of ChatGPT. International Journal of Changes in Education, 1(2), 103-111.
28. Proudfoot, K. (2023). Inductive/Deductive Hybrid Thematic Analysis in Mixed Methods Research. Journal of Mixed Methods Research, 17(3), 308–326.
29. Saihi, A., Ben-Daya, M., Hariga, M., & Rami, A. (2024). A Structural equation modeling analysis of generative AI chatbots adoption among students and educators in higher education.
30. Computers and Education: Artificial Intelligence, 7(100274).
31. Seunguk, N., Seokjae, H., Sehee, H., Shin, Y., & Roh, Y. (2022). Acceptance Model of Artificial Intelligence (AI)-Based Technologies in Construction Firms: Applying the Technology Acceptance Model (TAM) in Combination with the Technology–Organisation– Environment (TOE) Framework. Buildings, 90(12).
32. Teng, M. F. (2024). "ChatGPT is the companion, not enemies”: EFL learners’ perceptions and experiences in using ChatGPT for feedback in writing. Computers and Education: Artificial Intelligence, 7(100270).
33. Uslu, B. (2023). Üniversitelerde Yapay Zekanın Kullanım Alanları: Potansiyel Yararları ve Olası Zorluklar. Eğitimde Kuram ve Uygulama, 19(2), s. 227-239.
34. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision sciences, 39(2), 273-315.
35. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
36. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
37. Yıldırım, A., & Şimşek, H. (2018). Sosyal Bilimlerde Nitel Araştırma Yöntemleri. İstanbul: Seçkin.
38. YÖK. (2024). Yükseköğretim Kurumları Bilimsel Araştırma Ve Yayın Faaliyetlerinde Üretken Yapay Zekâ Kullanımına Dair Etik Rehber . www.yok.gov.tr. https://www.yok.gov.tr/Documents/2024/yapay-zeka-kullanimina-dair-etikrehber. pdf
39. Yang, Y., Luo, J., Yang, M., Yang, R., & Chen, J. (2024). From surface to deep learning approaches with Generative AI in higher education: an analytical framework of student agency. Studies in Higher Education, 49(5), 817-830.
40. Yuan, Y., & Zhu, W. (2022). Artificial Intelligence-Enabled Social Science: A Bibliometric Analysis. A. H. Sciences (Dü.), 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) içinde (s. 1602-1608). Atlantis Press.
41. Zawacki-Richter, O., Marin, 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(39), s. 1-27.
42. Zheng, L., Fan, Y., Gao, L., Huang, Z., Chen, B., & Long, M. (2024). Using AI-empowered assessments and personalized recommendations to promote online collaborative learning performance. Journal of Research on Technology in Education, s. 1-27.