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ChatGPT Okuryazarlığı ve Sürdürülebilirlik Algılarının Etkileşimi: Üniversite Düzeyindeki Yabancı Dil Olarak İngilizce Öğrenen Öğrencilerinden Elde Edilen Kanıtlar

Yıl 2026, Cilt: 26 Sayı: 1, 233 - 254, 28.03.2026
https://doi.org/10.18037/ausbd.1749050
https://izlik.org/JA88EP74XJ

Öz

Yapay zekâ (YZ) teknolojileri ve ChatGPT gibi kapsamlı dil modelleri eğitim alanına giderek daha fazla entegre olmaktadır ancak bu uygulamaların sürdürülebilir kullanımı önemli bir endişe kaynağı olarak ortaya çıkmaktadır. Bu çalışma, Türkiye’de üniversite düzeyinde İngilizceyi yabancı dil olarak (EFL) öğrenen öğrencilerin ChatGPT okuryazarlığı ile sürdürülebilirlik algıları arasındaki ilişkiyi incelemektedir. Kesitsel korelasyonel bir tasarım kullanılarak veriler, Türkiye’nin dört şehrindeki (İstanbul, İzmir, Diyarbakır ve Bursa) 147 üniversite öğrencisinden, ChatGPT okuryazarlığı ve sürdürülebilirlik algısını ölçen ölçekler aracılığıyla toplanmıştır. Veriler, Spearman korelasyonu, Mann–Whitney U ve Kruskal–Wallis testleri de dâhil olmak üzere betimsel ve çıkarımsal istatistiklerle analiz edilmiştir. Bulgular, ChatGPT okuryazarlığı ile sürdürülebilirlik algısı arasında istatistiksel olarak anlamlı pozitif bir korelasyon (Spearman ρ = .543, p < .001) olduğunu göstermektedir. Bu korelasyon, yapay zekâ araçlarında daha yüksek okuryazarlığın, çevresel, sosyal ve ekonomik sürdürülebilirlik konularında farkındalık geliştirme olasılığını artırabileceğini ortaya koymaktadır. Mevcut ChatGPT okuryazarlığı düzeyine bakıldığında, öğrenciler eleştirel ve etik boyutlara kıyasla ChatGPT’nin yaratıcı ve iletişimsel uygulamalarında orta düzeyde daha yüksek bir yeterlilik bildirmişlerdir. Benzer şekilde, öğrenciler orta düzeyde yüksek bir sürdürülebilirlik algısı bildirmiş olup bilişsel farkındalık ile davranışsal eylemler arasında bir fark gözlemlenmiştir. Cinsiyet ve bölgesel farklılıklar, sürdürülebilirliğe yönelik duygusal tepkilerdeki cinsiyete dayalı farklılıklar dışında, istatistiksel olarak anlamlı bulunmamıştır. Bulgular, dönüştürücü ve etik uygulamaları teşvik etmek amacıyla yapay zekâ okuryazarlığı ve sürdürülebilirlik eğitimlerinin İngilizce yabancı dil (EFL) müfredatına dâhil edilmesinin artan önemini vurgulamaktadır. Çalışma, ChatGPT okuryazarlığının geliştirilmesinin, öğrencileri karmaşık teknolojik ve ekolojik geleceklere hazırlamak için sürdürülebilirlik hedefleriyle nasıl kesişebileceğini ortaya koymaktadır.

Kaynakça

  • Arbiv, O. E. (2024). ChatGPT and sustainability in universities: Exploring environmental and educational impacts [Bachelor’s thesis, University of Twente]. https://essay.utwente.nl/essays/100828
  • Arslan, S., & Curle, S. (2024). Institutionalising English as a foreign language teachers for global sustainability: Perceptions of education for sustainable development in Turkey. International Journal of Educational Research, 125, 102353. https://doi.org/10.1016/j.ijer.2024.102353
  • Balcı, Ö. (2024). The role of ChatGPT in English as a foreign language (EFL) learning and teaching: A systematic review. International Journal of Current Educational Studies, 3(1), 66-81. https://doi.org/10.46328/ijces.107
  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  • Carretero, S., Vuorikari, R., & Punie, Y. (2017). DigComp 2.1: The digital competence framework for citizens with eight proficiency levels and examples of use. Publications Office of the European Union. https://doi.org/10.2760/38842
  • Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
  • Chai, C. S., Lin, P. Y., Jong, M. S. Y., Dai, Y., Chiu, T. K., & Qin, J. (2021). Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, 24(3), 89–101. https://www.jstor.org/stable/27032858
  • Chan, A. (2022). GPT-3 and InstructGPT: Technological dystopianism, utopianism, and contextual perspectives in AI ethics and industry. AI and Ethics. https://doi.org/10.1007/s43681-022-00148-6
  • Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Routledge.
  • Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732
  • Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson Education.
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
  • Goodall, G., Mjøen, O. M., Witsø, A. E., Horghagen, S., Hardonk, S., & Kvam, L. (2024). Attitudes towards students with disabilities achieving their educational and work-related goals: A factorial survey experiment among higher education institution employees in Norway. Higher Education, 88(2), 419–465. https://doi.org/10.1007/s10734-023-01123-8
  • Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
  • Homolak, J. (2023). Opportunities and risks of ChatGPT in medicine, science, and academic publishing: A modern Promethean dilemma. Croatian Medical Journal, 64(1), 1–3. https://doi.org/10.3325/cmj.2023.64.1
  • Hornberger, M., Bewersdorff, A., & Nerdel, C. (2023). What do university students know about artificial intelligence? Development and validation of an AI literacy test. Computers and Education: Artificial Intelligence, 5, 100165. https://doi.org/10.1016/j.caeai.2023.100165
  • Kaiser, F. G., & Wilson, M. (2004). Goal-directed conservation behavior: The specific composition of a general performance. Personality and Individual Differences, 36(7), 1531–1544. https://doi.org/10.1016/j.paid.2003.06.003
  • Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
  • Kollmuss, A., & Agyeman, J. (2002). Mind the gap: Why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental Education Research, 8(3), 239–260. https://doi.org/10.1080/13504620220145401
  • Lee, S., & Park, G. (2024). Development and validation of ChatGPT literacy scale. Current Psychology, 43(21), 18992–19004. https://doi.org/10.1007/s12144-024-05723-0
  • Lin, C. C., Huang, A. Y., & Lu, O. H. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10(1), 41. https://doi.org/10.1186/s40561-023-00260-y
  • Lodzikowski, K., Foltz, P. W., & Behrens, J. T. (2024). Generative AI and its educational implications. arXiv [Preprint]. https://arxiv.org/abs/2401.08659
  • Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In *Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems*(Paper No. 1–12). ACM. https://doi.org/10.1145/3313831.3376727
  • Lozano, R., Merrill, M. Y., Sammalisto, K., Ceulemans, K., & Lozano, F. J. (2017). Connecting competences and pedagogical approaches for sustainable development in higher education: A literature review and framework proposal. Sustainability, 9(10), 1889. https://doi.org/10.3390/su9101889
  • Mohamed, A. M. (2024). Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: Perceptions of EFL faculty members. Education and Information Technologies, 29(3), 3195–3217. https://doi.org/10.1007/s10639-023-11917-z
  • Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
  • Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221–4241. https://doi.org/10.1007/s10639-022-11316-w
  • OECD. (2019). OECD learning compass 2030: A series of concept notes. http://www.oecd.org/education/2030-project/contact/OECD_Learning_Compass_2030_Concept_Note_Series.pdf
  • Olsson, D., Gericke, N., & Chang Rundgren, S. N. (2016). The effect of implementation of education for sustainable development in Swedish compulsory schools – Assessing pupils’ sustainability consciousness. Environmental Education Research, 22(2), 176–202. https://doi.org/10.1080/13504622.2015.1005057
  • Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). Routledge.
  • Rane, N. (2023). Roles and challenges of ChatGPT and similar generative artificial intelligence for achieving the sustainable development goals (SDGs). SSRN [Preprint]. https://doi.org/10.2139/ssrn.4603244
  • Salahange, L., Sánchez-Martín, J., Dávila-Acedo, M. A., & Cañada-Cañada, F. (2024). A new validated instrument to assess sustainability perception among university students. Discover Sustainability, 5(1), 400. https://doi.org/10.1007/s43621-024-00623-6
  • Salkind, N. J. (2010). Cross-sectional correlational design. In N. J. Salkind (Ed.), Encyclopedia of research design (Vol. 1, pp. 124–131). SAGE Publications.
  • Sterling, S. (2011). Transformative learning and sustainability: Sketching the conceptual ground. Learning and Teaching in Higher Education, (5), 17–33.
  • Tanveer, M., Hassan, S., & Bhaumik, A. (2020). Academic policy regarding sustainability and artificial intelligence (AI). Sustainability, 12(22), 9435. https://doi.org/10.3390/su12229435
  • UNESCO. (2024). AI competency framework for students. https://doi.org/10.54675/JKJB9835
  • UNESCO. (2017). Education for sustainable development goals: Learning objectives. https://unesdoc.unesco.org/ark:/48223/pf0000247444
  • United Nations. (2015). Transforming our world: The 2030 agenda for sustainable development (A/RES/70/1). https://sdgs.un.org/2030agenda
  • United Nations. (2022). Transforming education: An urgent political imperative for our collective future (Transforming Education Summit). https://www.un.org/en/transforming-education-summit/sg-vision-statement
  • Wang, J., & Fan, W. (2025). The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: Insights from a meta-analysis. Humanities and Social Sciences Communications, 12, Article 621. https://doi.org/10.1057/s41599-025-04787-y
  • Warschauer, M., & Xu, Y. (2024). Generative AI for language learning: Entering a new era. Language Learning & Technology, 28(2), 1–4. https://hdl.handle.net/10125/73569
  • Wiek, A., Withycombe, L., & Redman, C. L. (2011). Key competencies in sustainability: A reference framework for academic program development. Sustainability Science, 6, 203–218. https://doi.org/10.1007/s11625-011-0132-6
  • Younis, B. (2025). The artificial intelligence literacy (AIL) scale for teachers: A tool for enhancing AI education. Journal of Digital Learning in Teacher Education, 41(1), 37–56. https://doi.org/10.1080/21532974.2024.2441682
  • Yuskovych-Zhukovska, V., Poplavska, T., Diachenko, O., Mishenina, T., Topolnyk, Y., & Gurevych, R. (2022). Application of artificial intelligence in education: Problems and opportunities for sustainable development. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 13(Suppl. 1), 339–356. https://doi.org/10.18662/brain/13.1Sup1/322
  • Zawacki-Richter, O., Marín, 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(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

The Interplay of ChatGPT Literacy and Sustainability Perceptions: Evidence from Tertiary-Level EFL Learners

Yıl 2026, Cilt: 26 Sayı: 1, 233 - 254, 28.03.2026
https://doi.org/10.18037/ausbd.1749050
https://izlik.org/JA88EP74XJ

Öz

Artificial intelligence (AI) technologies, extensive language models like ChatGPT, are becoming increasingly integrated into educational environments; however, their sustainable use is emerging as a substantial concern. This study explores the relationship between ChatGPT literacy and sustainability perceptions of tertiary-level English as a Foreign Language (EFL) learners in Türkiye. Through a cross-sectional correlational design, the data were collected from 147 tertiary-level EFL students across four cities in Türkiye. The participants completed instruments measuring ChatGPT literacy and sustainability perception. The data were analyzed through descriptive and inferential statistics, including Spearman’s correlation, Mann-Whitney U, and Kruskal-Wallis tests. The findings reveal a statistically significant positive correlation (Spearman’s ρ=.543, p <.001) between ChatGPT literacy and sustainability perception, indicating that higher literacy in AI tools may increase the likelihood of developing an awareness of environmental, social, and economic sustainability issues. Regarding the current level of ChatGPT literacy, the learners reported moderately stronger competence in ChatGPT’s creative and communicative applications than in critical and ethical dimensions. Likewise, while the learners reported moderately high sustainability perception, a gap emerged between cognitive awareness and behavioral actions. Gender and regional differences were not statistically significant in either variable, except for gender-based variation in affective responses to sustainability. The findings underline the emerging need to incorporate AI literacy and sustainability education into EFL curricula to promote transformative and ethical practices. The study highlights how fostering ChatGPT literacy can intersect with sustainability goals to prepare learners for complex technological and ecological futures.

Kaynakça

  • Arbiv, O. E. (2024). ChatGPT and sustainability in universities: Exploring environmental and educational impacts [Bachelor’s thesis, University of Twente]. https://essay.utwente.nl/essays/100828
  • Arslan, S., & Curle, S. (2024). Institutionalising English as a foreign language teachers for global sustainability: Perceptions of education for sustainable development in Turkey. International Journal of Educational Research, 125, 102353. https://doi.org/10.1016/j.ijer.2024.102353
  • Balcı, Ö. (2024). The role of ChatGPT in English as a foreign language (EFL) learning and teaching: A systematic review. International Journal of Current Educational Studies, 3(1), 66-81. https://doi.org/10.46328/ijces.107
  • Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
  • Carretero, S., Vuorikari, R., & Punie, Y. (2017). DigComp 2.1: The digital competence framework for citizens with eight proficiency levels and examples of use. Publications Office of the European Union. https://doi.org/10.2760/38842
  • Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The promises and challenges of artificial intelligence for teachers: A systematic review of research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
  • Chai, C. S., Lin, P. Y., Jong, M. S. Y., Dai, Y., Chiu, T. K., & Qin, J. (2021). Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, 24(3), 89–101. https://www.jstor.org/stable/27032858
  • Chan, A. (2022). GPT-3 and InstructGPT: Technological dystopianism, utopianism, and contextual perspectives in AI ethics and industry. AI and Ethics. https://doi.org/10.1007/s43681-022-00148-6
  • Cohen, L., Manion, L., & Morrison, K. (2018). Research methods in education (8th ed.). Routledge.
  • Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732
  • Creswell, J. W. (2012). Educational research: Planning, conducting, and evaluating quantitative and qualitative research (4th ed.). Pearson Education.
  • Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
  • Goodall, G., Mjøen, O. M., Witsø, A. E., Horghagen, S., Hardonk, S., & Kvam, L. (2024). Attitudes towards students with disabilities achieving their educational and work-related goals: A factorial survey experiment among higher education institution employees in Norway. Higher Education, 88(2), 419–465. https://doi.org/10.1007/s10734-023-01123-8
  • Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
  • Homolak, J. (2023). Opportunities and risks of ChatGPT in medicine, science, and academic publishing: A modern Promethean dilemma. Croatian Medical Journal, 64(1), 1–3. https://doi.org/10.3325/cmj.2023.64.1
  • Hornberger, M., Bewersdorff, A., & Nerdel, C. (2023). What do university students know about artificial intelligence? Development and validation of an AI literacy test. Computers and Education: Artificial Intelligence, 5, 100165. https://doi.org/10.1016/j.caeai.2023.100165
  • Kaiser, F. G., & Wilson, M. (2004). Goal-directed conservation behavior: The specific composition of a general performance. Personality and Individual Differences, 36(7), 1531–1544. https://doi.org/10.1016/j.paid.2003.06.003
  • Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
  • Kollmuss, A., & Agyeman, J. (2002). Mind the gap: Why do people act environmentally and what are the barriers to pro-environmental behavior? Environmental Education Research, 8(3), 239–260. https://doi.org/10.1080/13504620220145401
  • Lee, S., & Park, G. (2024). Development and validation of ChatGPT literacy scale. Current Psychology, 43(21), 18992–19004. https://doi.org/10.1007/s12144-024-05723-0
  • Lin, C. C., Huang, A. Y., & Lu, O. H. (2023). Artificial intelligence in intelligent tutoring systems toward sustainable education: A systematic review. Smart Learning Environments, 10(1), 41. https://doi.org/10.1186/s40561-023-00260-y
  • Lodzikowski, K., Foltz, P. W., & Behrens, J. T. (2024). Generative AI and its educational implications. arXiv [Preprint]. https://arxiv.org/abs/2401.08659
  • Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. In *Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems*(Paper No. 1–12). ACM. https://doi.org/10.1145/3313831.3376727
  • Lozano, R., Merrill, M. Y., Sammalisto, K., Ceulemans, K., & Lozano, F. J. (2017). Connecting competences and pedagogical approaches for sustainable development in higher education: A literature review and framework proposal. Sustainability, 9(10), 1889. https://doi.org/10.3390/su9101889
  • Mohamed, A. M. (2024). Exploring the potential of an AI-based Chatbot (ChatGPT) in enhancing English as a Foreign Language (EFL) teaching: Perceptions of EFL faculty members. Education and Information Technologies, 29(3), 3195–3217. https://doi.org/10.1007/s10639-023-11917-z
  • Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
  • Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221–4241. https://doi.org/10.1007/s10639-022-11316-w
  • OECD. (2019). OECD learning compass 2030: A series of concept notes. http://www.oecd.org/education/2030-project/contact/OECD_Learning_Compass_2030_Concept_Note_Series.pdf
  • Olsson, D., Gericke, N., & Chang Rundgren, S. N. (2016). The effect of implementation of education for sustainable development in Swedish compulsory schools – Assessing pupils’ sustainability consciousness. Environmental Education Research, 22(2), 176–202. https://doi.org/10.1080/13504622.2015.1005057
  • Pallant, J. (2020). SPSS survival manual: A step by step guide to data analysis using IBM SPSS (7th ed.). Routledge.
  • Rane, N. (2023). Roles and challenges of ChatGPT and similar generative artificial intelligence for achieving the sustainable development goals (SDGs). SSRN [Preprint]. https://doi.org/10.2139/ssrn.4603244
  • Salahange, L., Sánchez-Martín, J., Dávila-Acedo, M. A., & Cañada-Cañada, F. (2024). A new validated instrument to assess sustainability perception among university students. Discover Sustainability, 5(1), 400. https://doi.org/10.1007/s43621-024-00623-6
  • Salkind, N. J. (2010). Cross-sectional correlational design. In N. J. Salkind (Ed.), Encyclopedia of research design (Vol. 1, pp. 124–131). SAGE Publications.
  • Sterling, S. (2011). Transformative learning and sustainability: Sketching the conceptual ground. Learning and Teaching in Higher Education, (5), 17–33.
  • Tanveer, M., Hassan, S., & Bhaumik, A. (2020). Academic policy regarding sustainability and artificial intelligence (AI). Sustainability, 12(22), 9435. https://doi.org/10.3390/su12229435
  • UNESCO. (2024). AI competency framework for students. https://doi.org/10.54675/JKJB9835
  • UNESCO. (2017). Education for sustainable development goals: Learning objectives. https://unesdoc.unesco.org/ark:/48223/pf0000247444
  • United Nations. (2015). Transforming our world: The 2030 agenda for sustainable development (A/RES/70/1). https://sdgs.un.org/2030agenda
  • United Nations. (2022). Transforming education: An urgent political imperative for our collective future (Transforming Education Summit). https://www.un.org/en/transforming-education-summit/sg-vision-statement
  • Wang, J., & Fan, W. (2025). The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: Insights from a meta-analysis. Humanities and Social Sciences Communications, 12, Article 621. https://doi.org/10.1057/s41599-025-04787-y
  • Warschauer, M., & Xu, Y. (2024). Generative AI for language learning: Entering a new era. Language Learning & Technology, 28(2), 1–4. https://hdl.handle.net/10125/73569
  • Wiek, A., Withycombe, L., & Redman, C. L. (2011). Key competencies in sustainability: A reference framework for academic program development. Sustainability Science, 6, 203–218. https://doi.org/10.1007/s11625-011-0132-6
  • Younis, B. (2025). The artificial intelligence literacy (AIL) scale for teachers: A tool for enhancing AI education. Journal of Digital Learning in Teacher Education, 41(1), 37–56. https://doi.org/10.1080/21532974.2024.2441682
  • Yuskovych-Zhukovska, V., Poplavska, T., Diachenko, O., Mishenina, T., Topolnyk, Y., & Gurevych, R. (2022). Application of artificial intelligence in education: Problems and opportunities for sustainable development. BRAIN. Broad Research in Artificial Intelligence and Neuroscience, 13(Suppl. 1), 339–356. https://doi.org/10.18662/brain/13.1Sup1/322
  • Zawacki-Richter, O., Marín, 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(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0
Toplam 45 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka (Diğer), İletişim Eğitimi
Bölüm Araştırma Makalesi
Yazarlar

Halenur Ocaktan Çeliktürk 0000-0001-6802-9625

Serhat Başar 0000-0001-9716-4308

Gönderilme Tarihi 23 Temmuz 2025
Kabul Tarihi 4 Şubat 2026
Yayımlanma Tarihi 28 Mart 2026
DOI https://doi.org/10.18037/ausbd.1749050
IZ https://izlik.org/JA88EP74XJ
Yayımlandığı Sayı Yıl 2026 Cilt: 26 Sayı: 1

Kaynak Göster

APA Ocaktan Çeliktürk, H., & Başar, S. (2026). The Interplay of ChatGPT Literacy and Sustainability Perceptions: Evidence from Tertiary-Level EFL Learners. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 26(1), 233-254. https://doi.org/10.18037/ausbd.1749050