ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği
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Üretken yapay zeka, eğitim de dahil olmak üzere hayatımızın birçok alanı için kapsamlı etkileri olan önemli bir teknolojik ilerlemeyi temsil etmektedir. Bu makale, üretken yapay zekanın eğitim alanındaki yansımalarını ve potansiyel rolünü incelemektedir. Çalışma, yapay zeka teknolojilerinin tarihsel gelişimini tartışmakta ve güncel tanımlarını açıklamaktadır. Bu çalışma kapsamında incelenen yayınlara göre insanlığın en sofistike teknolojilerinden biri olan dilin üretken yapay zeka tarafından kullanılmasının önemli bir dönüm noktası olduğu iddia edilirken, bu durumun eğitsel süreçlerin yeniden yapılandırılmasını ve tanımlanmasını gerektirdiği de savunulmaktadır. Çalışmada yapay zeka okuryazarlığı ve komut mühendisliği gibi becerilerin geleceğe daha iyi hazır olabilmek adına gerekli olduğu vurgusu yapılmakta ve üretken yapay zeka ile ortaya çıkan fırsatlar ve tehditler açıklanmaktadır. Bu çalışma üretken yapay zeka teknolojilerinin öğretme ve öğrenme yöntemlerini derinden etkileme potansiyeline sahip olması ve yeni düşünme biçimleri gerektirmesi nedeniyle, yapay zekanın hakim olduğu bir geleceğe hazırlıklı olmanın önemine vurgu yapmaktadır.
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The advantages of GenAI in education depend on the user's competencies in understanding, interpreting and making sense of the generated content.
“Therefore, the advantages of GenAI in education depend on the user's competencies in understanding, interpreting and making sense of the generated content (Bozkurt, 2023;Laupichler et al., 2022).”
From Development and validation of the Generative AI Literacy for Learning Scale (GenAI-LLs) (2025) · cites this paper as Bozkurt, 2023
The abstract (Öz; page not given) says AI literacy and prompt-engineering skills are necessary to prepare for a future shaped by generative AI, and discusses its educational opportunities. It does not specifically say that those advantages depend on users’ ability to understand, interpret, and make sense of generated content. (LLM, conf=0.76)
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Cites
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · see citing works
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · see citing works
Learning to Prompt for Vision-Language Models
Zhou, K., Yang, J., Loy, C. C., & Liu, Z. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01653-1 · Cited by 3,304 · see citing works
Conceptualizing AI literacy: An exploratory review
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100041 · Cited by 2,205 · see citing works
What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00237-x · Cited by 2,003 · see citing works
Self-citationLim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023) · The International Journal of Management Education · doi:10.1016/j.ijme.2023.100790 · Cited by 1,261 · see citing works
Artificial intelligence literacy in higher and adult education: A scoping literature review
Laupichler, M. C., Aster, A., Schirch, J., & Raupach, T. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100101 · Cited by 658 · see citing works
Design Guidelines for Prompt Engineering Text-to-Image Generative Models
Liu, V., & Chilton, L. B. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501825 · Cited by 639 · see citing works
Crawford, J., Cowling, M., & Allen, K.-A. (2023) · Journal of University Teaching and Learning Practice · doi:10.53761/1.20.3.02 · Cited by 547 · see citing works
AI as Agency Without Intelligence: on ChatGPT, Large Language Models, and Other Generative Models
Floridi, L. (2023) · Philosophy & Technology · doi:10.1007/s13347-023-00621-y · Cited by 404 · see citing works
Welcome to the Era of ChatGPT et al.: The Prospects of Large Language Models
Teubner, T., Flath, C. M., Weinhardt, C., van der Aalst, W., & Hinz, O. (2023) · Business & Information Systems Engineering · doi:10.1007/s12599-023-00795-x · Cited by 384 · see citing works
Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., et al. (2023) · Zenodo · doi:10.5281/zenodo.7636568 · Cited by 350 · see citing works
Self-citationBozkurt, A. (2023) · Zenodo · doi:10.5281/zenodo.7716416 · Cited by 224 · see citing works
Self-citation“We Need To Talk About ChatGPT”: The Future of AI and Higher Education
Neumann, M., Rauschenberger, M., & Schön, E.-M. (2023) · Hochschule Hannover · doi:10.25968/opus-2467 · Cited by 212 · see citing works
Flagged first, then by citations
Research works printed but not linked: 6
- Bozkurt, A. (2023). ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği. Alanyazın, 4(1), 63-72. https://doi.org/10.59320/alanyazin.1283282
- [1]Bozkurt A. ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği. Alanyazın (CRES Journal). 2023;4(1):63-72. doi:10.59320/alanyazin.1283282
- Bozkurt, Aras. 2023. “ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği”. Alanyazın 4 (1): 63-72. https://doi.org/10.59320/alanyazin.1283282.
- [1]A. Bozkurt, “ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği”, Alanyazın (CRES Journal), c. 4, sy 1, ss. 63–72, May. 2023, doi: 10.59320/alanyazin.1283282.
- [1]Bozkurt A. ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği. Alanyazın (CRES Journal). 2023;4:63–72.
- [1]Aras Bozkurt. ChatGPT, Üretken Yapay Zeka ve Algoritmik Paradigma Değişikliği. Alanyazın (CRES Journal). 01 Mayıs 2023;4(1):63-72. doi:10.59320/alanyazin.1283282
Cited by
Sorted by citations
Development and validation of the Generative AI Literacy for Learning Scale (GenAI-LLs)
Gümüş, M. M., & KARA, M. (2025) · Australasian Journal of Educational Technology · doi:10.14742/ajet.10236 · Cited by 10 · see citing works
- Authors
- BOZKURT, A.
- Affiliations
- Anadolu University (TR)
- Corresponding author
- BOZKURT, Aras
- ORCID
- BOZKURT, Aras
- Venue
- Alanyazın
- Publisher
- Öncü Okul Yöneticileri Dernegi
- Published
- 2023-05-31
- Volume
- 4
- Issue
- 1
- Pages
- 63-72
- ISSN
- 2718-0808 (ISSN-L)
- OpenAlex
- W4378780863
- Cited by
- 95
- References
- 14
- Citations by year
- 2026: 31 · 2025: 40 · 2024: 21 · 2023: 3
- FWCI
- 17.19
- Type
- journal article
- Language
- tr
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Alanyazın (publishedVersion, cc-by-nc)
- DergiPark (Istanbul University) (submittedVersion, cc-by-nc-nd)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, ChatGPT, artificial intelligence in education, AI literacy, future of teaching and learning, history of artificial intelligence
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