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Usage Areas of Artificial Intelligence in Universities: Potential Benefits and Prospective Challenges

Yıl 2023, Cilt: 19 Sayı: 2, 227 - 239, 31.12.2023
https://doi.org/10.17244/eku.1355304

Öz

In line with the increasing use of data, powerful computing resources, and complex algorithms, Artificial Intelligence (AI) systems have recently been employed by universities in education and training, research and development, and administrative processes. Given its potential to improve student learning outcomes and significantly increase in administrative efficiency, it can be expected that more AI applications will be implemented in higher education as its areas of application continue to expand. On the other hand, the use of AI in higher education may bring a number of challenges such as ethical concerns, human resistance and adoption, integration with existing systems, and limited data availability. In addition, universities may face technical difficulties in the process of using AI systems, the principle of transparency may become a different criterion, the use of these applications may require specialised knowledge and skills, the need for complex legal and regulatory frameworks may increase, and various risks for data privacy and security may arise. Consequently, it is as important to assess the potential challenges that AI may pose in higher education as it is to articulate the beneficial functions for universities. In this context, the present study addresses various debates on the opportunities offered by AI technologies in universities and the accompanying challenges.

Kaynakça

  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101. https://doi.org/10.3390/su14031101
  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Shahid, M. K., Aslam, M., Salim, N. A., & Al-Abyadh, M. H. A. (2023). Leading edge or bleeding edge: Designing a framework for the adoption of ai technology in an educational organization. Sustainability, 15(8), 6540. https://doi.org/10.3390/su15086540
  • Ali, M., & Abdel-Haq, M. K. (2021). Bibliographical analysis of artificial intelligence learning in higher education: Is the role of the human educator and educated a thing of the past? In M. B. Ali & T. Wood-Harper (Eds.), Fostering communication and learning with underutilized technologies in higher education (pp. 36-52). IGI Global.
  • Baird, A., & Schuller, B. (2020). Considerations for a more ethical approach to data in AI: On data representation and infrastructure. Frontiers in Big Data, 3, 25. https://doi.org/10.3389/fdata.2020.00025
  • Besse, P. C., Castets-Renard, C., Garivier, A., & Loubes, J. (2019). Can everyday AI be ethical? Machine learning algorithm fairness. Statistiques et Société, 6(3). https://ssrn.com/abstract=3391288
  • Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape: A review of AI studies in half a century. Sustainability, 13(2), 800. https://doi.org/10.3390/su13020800
  • Bu, Q. (2022). Ethical risks in integrating artificial intelligence into education and potential countermeasures. Science Insights, 41(1), 561. https://doi.org/10.15354/si.22.re067
  • Bustamante, D., & Garcia-Bedoya, O. (2021). Predictive academic performance model to support, prevent and decrease the university dropout rate. In H. Florez, & M. F. Pollo-Cattaneo (Eds.), Proceedings of Applied Informatics: Fourth International Conference (ICAI 2021) (pp. 222-236). Springer. https://doi.org/10.1007/978-3-030-89654-6_16
  • Chan, C. K. Y., & Tsi, L. H. Y. (2023). The AI revolution in education: Will AI replace or assist teachers in higher education? arxiv. https://doi.org/10.48550/arXiv.2305.01185
  • Chatterjee, S., & Sreenivasulu, N. S. (2019). Personal data sharing and legal issues of human rights in the era of artificial intelligence: Moderating effect of government regulation. International Journal of Electronic Government Research, 15(3), 16. https://doi.org/10.4018/IJEGR.2019070102
  • Chatterjee, S., & Bhattacharjee, K. K. (2020). Adoption of artificial intelligence in higher education: A quantitative analysis using structural equation modelling. Education and Information Technology, 25(5), 3443. https://doi.org/10.1007/s10639-020-10159-7
  • Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
  • 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. https://doi.org/10.1080/00131857.2020.1728732
  • Goldrick, M., Stevns, T., & Christensen, L. B. (2014). The use of assistive technologies as learning technologies to facilitate flexible learning in higher education. In K. Miesenberger, D. Fels, D. Archambault, P. Penaz, & W. Zagler (Eds.), Proceedings of Computers Helping People with Special Needs: 14th International Conference (ICCHP 2014) (pp. 342-349). https://doi.org/10.1007/978-3-319-08599-9_52
  • Jianxue, G. (2020). Application of artificial intelligence technology in university teaching system. Frontiers in Art Research, 2(7), 72. https://doi.org/10.25236/FAR.2020.020712
  • Khan, I., Ahmad, A. R., Jabeur, N., & Mahdi, M. N. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environment, 8, 17. https://doi.org/10.1186/s40561-021-00161-y
  • Kim, H., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: A status quo bias perspective. Management Information Systems Quarterly, 33(3), 567. https://doi.org/10.2307/20650309
  • Kohli, R., Phutela, S., Garg, A., & Viner, M. (2021). Artificial intelligence technology to help students with disabilities: Promises and implications for teaching and learning. In A. Singh, C. J. Yeh, S. Blanchard, & L. Anunciação (Eds.), Handbook of Research on Critical Issues in Special Education for School Rehabilitation Practices (pp. 238-255). IGI Global.
  • Mclaren, B. M., Scheuer, O., & Miksatko, J. (2010). Supporting collaborative learning and e-discussions using artificial intelligence techniques. International Journal of Artificial Intelligence in Education, 20(1), 1. https://doi.org/10.3233/JAI-2010-0001
  • Meurisch, C., & Mühlhäuser, M. (2021). Data protection in AI services: A survey. ACM Computing Surveys, 54(2), 40. https://doi.org/10.1145/3440754
  • Nieto, Y., García-Díaz, V., Montenegro, C., & Crespo, R. G. (2019). Supporting academic decision making at higher educational institutions using machine learning-based algorithms. Soft Computing, 23(12), 4145. https://doi.org/10.1007/s00500-018-3064-6
  • Niu, K., Cheng, C., Gao, H., & Zhou, X. (2019). Suggestions on accelerating the implementation of artificial intelligence technology in university information system. Proceedings of The 14th International Conference on Computer Science & Education (ICCSE 2019) (pp. 767-770). https://doi.org/10.1109/ICCSE.2019.8845378
  • Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033
  • Pedro, F. (2020). Applications of artificial intelligence to higher education: Possibilities, evidence, and challenges. IUL Research, 1(1), 61. https://doi.org/10.57568/iulres.v1i1.43
  • Rashid, T. A., & Aziz, N. K. (2016). Student academic performance using artificial intelligence. ZANCO Journal of Pure and Applied Sciences, 28(2), 56. https://www.researchgate.net/publication/291262353
  • Razia, B., Awwad, B., & Taqi, N. (2023). The relationship between artificial intelligence (AI) and its aspects in higher education. Development and Learning in Organizations, 37(3), 21. https://doi.org/10.1108/DLO-04-2022-0074
  • Salas-Pilco, S. Z., Xiao, K., & Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8), 569. https://doi.org/10.3390/educsci12080569
  • Silva, J., Romero, L., Solano, D., Fernandez, C., Lezama, O. B. P., & Rojas, K. (2021). Model for predicting academic performance through artificial intelligence. In V. Singh, V. Asari, S. Kumar, & R. Patel (Eds.), Computational methods and data engineering: Advances in intelligent systems and computing (pp. 519-525). Springer.
  • Slimi, Z., & Carballido, B. V. (2023). Navigating the ethical challenges of artificial intelligence in higher education: An analysis of seven global AI ethics policies. TEM Journal, 12(2), 590. https://doi.org/10.18421/TEM122-02
  • Talei, H., Benhaddou, D., Gamarra, C., Benhaddou, M., & Essaaidi, M. (2023). Identifying energy inefficiencies using self-organizing maps: Case of a highly efficient certified office building. Applied Sciences, 13(3), 1666. https://doi.org/10.3390/app13031666
  • Taşçı, G., & Çelebi, M. (2020). Eğitimde yeni bir paradigma: “Yükseköğretimde yapay zekâ”. OPUS International Journal of Society Researches, 16(29), 2346. https://doi.org/10.26466/opus.747634
  • Tiwari, R. (2023). The integration of AI and machine learning in education and its potential to personalize and improve student learning experiences. International Journal of Scientific Research in Engineering and Management, 7(2), 1. https://doi.org/10.55041/ijsrem17645
  • Uzun, Y., Tümtürk, A. Y., & Öztürk, H. (2021). Günümüzde ve gelecekte eğitim alanında kullanılan yapay zeka. 1st International Conference on Applied Engineering and Natural Sciences, 1-3 Kasım, Konya, Türkiye.
  • Wang, Y. (2021). When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale. Studies in Educational Evaluation, 69, 100872. https://doi.org/10.1016/j.stueduc.2020.100872
  • Wei, X., Sun, S., Wu, D., & Zhou, L. (2021). Personalized online learning resource recommendation based on artificial intelligence and educational psychology. Frontiers in Psychology, 12, 767837. https://doi.org/10.3389/fpsyg.2021.767837
  • Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler, H. (2021). Are we there yet? - A systematic literature review on chatbots in education. Frontiers in Artificial Intelligence, 4, 654924. https://doi.org/10.3389/frai.2021.654924
  • Xia, P. (2020). Application scenario of artificial intelligence technology in higher education. In J. Abawajy, K. K. Choo, R. Islam, Z. Xu, & M. Atiquzzaman (Eds.), Proceedings of The International Conference on Applications and Techniques in Cyber Intelligence (ATCI 2019) (pp. 221-226). https://doi.org/10.1007/978-3-030-25128-4_29
  • Yang, S., & Evans, C. (2019). Opportunities and challenges in using AI Chatbots in higher education. Proceedings of The 3rd International Conference on Education and E-Learning (ICEEL'19) (pp. 79-83). https://doi.org/10.1145/3371647.3371659
  • 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, 39. https://doi.org/10.1186/s41239-019-0171-0
  • Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 8812542. https://doi.org/10.1155/2021/8812542

Üniversitelerde Yapay Zekanın Kullanım Alanları: Potansiyel Yararları ve Olası Zorluklar

Yıl 2023, Cilt: 19 Sayı: 2, 227 - 239, 31.12.2023
https://doi.org/10.17244/eku.1355304

Öz

Verilerin, güçlü bilgi işlem kaynaklarının ve karmaşık algoritmaların artan kullanımı doğrultusunda, son dönemde üniversiteler tarafından Yapay Zeka (YZ) sistemleri eğitim-öğretim, araştırma-geliştirme ve yönetsel süreçlerde kullanılmaya başlanmıştır. Öğrencilere ilişkin öğrenme sonuçlarını geliştirme ve idari verimliliği önemli ölçüde artırma potansiyeli göz önüne alındığında, kullanım alanları genişlemeye devam ettikçe yükseköğretimde daha fazla YZ uygulamasının hayata geçmesi beklenebilecek bir durumdur. Diğer taraftan, yükseköğretimde YZ kullanımı etik kaygılar, insani direnç ve benimsenme(me), mevcut sistemlerle entegrasyon, sınırlı veri gibi bir dizi zorluğu beraberinde getirebilir. Ayrıca, üniversitelerde YZ sistemlerinin kullanım sürecinde teknik zorluklarla karşılaşabilir, şeffaflık ilkesi farklı bir kriter haline gelebilir, bu uygulamaların kullanımı özel bilgi ve beceri gerektirebilir, karmaşık yasal ve düzenleyici çerçevelere ihtiyaç artabilir ve veri gizliliği ile güvenliği için çeşitli riskler oluşabilir. Sonuç olarak, üniversiteler için faydalı işlevleri dile getirmek kadar, yükseköğretimde YZ’nın neden olabileceği potansiyel zorlukları değerlendirmek de önemlidir. Bu kapsamda, mevcut çalışma üniversitelerde YZ teknolojilerinin sunduğu fırsatlar ile beraberindeki zorluklara dair farklı tartışmalara değinmektedir.

Kaynakça

  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Mubarik, M. S., & Hyder, S. I. (2022). Academic and administrative role of artificial intelligence in education. Sustainability, 14(3), 1101. https://doi.org/10.3390/su14031101
  • Ahmad, S. F., Alam, M. M., Rahmat, M. K., Shahid, M. K., Aslam, M., Salim, N. A., & Al-Abyadh, M. H. A. (2023). Leading edge or bleeding edge: Designing a framework for the adoption of ai technology in an educational organization. Sustainability, 15(8), 6540. https://doi.org/10.3390/su15086540
  • Ali, M., & Abdel-Haq, M. K. (2021). Bibliographical analysis of artificial intelligence learning in higher education: Is the role of the human educator and educated a thing of the past? In M. B. Ali & T. Wood-Harper (Eds.), Fostering communication and learning with underutilized technologies in higher education (pp. 36-52). IGI Global.
  • Baird, A., & Schuller, B. (2020). Considerations for a more ethical approach to data in AI: On data representation and infrastructure. Frontiers in Big Data, 3, 25. https://doi.org/10.3389/fdata.2020.00025
  • Besse, P. C., Castets-Renard, C., Garivier, A., & Loubes, J. (2019). Can everyday AI be ethical? Machine learning algorithm fairness. Statistiques et Société, 6(3). https://ssrn.com/abstract=3391288
  • Bozkurt, A., Karadeniz, A., Baneres, D., Guerrero-Roldán, A. E., & Rodríguez, M. E. (2021). Artificial intelligence and reflections from educational landscape: A review of AI studies in half a century. Sustainability, 13(2), 800. https://doi.org/10.3390/su13020800
  • Bu, Q. (2022). Ethical risks in integrating artificial intelligence into education and potential countermeasures. Science Insights, 41(1), 561. https://doi.org/10.15354/si.22.re067
  • Bustamante, D., & Garcia-Bedoya, O. (2021). Predictive academic performance model to support, prevent and decrease the university dropout rate. In H. Florez, & M. F. Pollo-Cattaneo (Eds.), Proceedings of Applied Informatics: Fourth International Conference (ICAI 2021) (pp. 222-236). Springer. https://doi.org/10.1007/978-3-030-89654-6_16
  • Chan, C. K. Y., & Tsi, L. H. Y. (2023). The AI revolution in education: Will AI replace or assist teachers in higher education? arxiv. https://doi.org/10.48550/arXiv.2305.01185
  • Chatterjee, S., & Sreenivasulu, N. S. (2019). Personal data sharing and legal issues of human rights in the era of artificial intelligence: Moderating effect of government regulation. International Journal of Electronic Government Research, 15(3), 16. https://doi.org/10.4018/IJEGR.2019070102
  • Chatterjee, S., & Bhattacharjee, K. K. (2020). Adoption of artificial intelligence in higher education: A quantitative analysis using structural equation modelling. Education and Information Technology, 25(5), 3443. https://doi.org/10.1007/s10639-020-10159-7
  • Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
  • 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. https://doi.org/10.1080/00131857.2020.1728732
  • Goldrick, M., Stevns, T., & Christensen, L. B. (2014). The use of assistive technologies as learning technologies to facilitate flexible learning in higher education. In K. Miesenberger, D. Fels, D. Archambault, P. Penaz, & W. Zagler (Eds.), Proceedings of Computers Helping People with Special Needs: 14th International Conference (ICCHP 2014) (pp. 342-349). https://doi.org/10.1007/978-3-319-08599-9_52
  • Jianxue, G. (2020). Application of artificial intelligence technology in university teaching system. Frontiers in Art Research, 2(7), 72. https://doi.org/10.25236/FAR.2020.020712
  • Khan, I., Ahmad, A. R., Jabeur, N., & Mahdi, M. N. (2021). An artificial intelligence approach to monitor student performance and devise preventive measures. Smart Learning Environment, 8, 17. https://doi.org/10.1186/s40561-021-00161-y
  • Kim, H., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: A status quo bias perspective. Management Information Systems Quarterly, 33(3), 567. https://doi.org/10.2307/20650309
  • Kohli, R., Phutela, S., Garg, A., & Viner, M. (2021). Artificial intelligence technology to help students with disabilities: Promises and implications for teaching and learning. In A. Singh, C. J. Yeh, S. Blanchard, & L. Anunciação (Eds.), Handbook of Research on Critical Issues in Special Education for School Rehabilitation Practices (pp. 238-255). IGI Global.
  • Mclaren, B. M., Scheuer, O., & Miksatko, J. (2010). Supporting collaborative learning and e-discussions using artificial intelligence techniques. International Journal of Artificial Intelligence in Education, 20(1), 1. https://doi.org/10.3233/JAI-2010-0001
  • Meurisch, C., & Mühlhäuser, M. (2021). Data protection in AI services: A survey. ACM Computing Surveys, 54(2), 40. https://doi.org/10.1145/3440754
  • Nieto, Y., García-Díaz, V., Montenegro, C., & Crespo, R. G. (2019). Supporting academic decision making at higher educational institutions using machine learning-based algorithms. Soft Computing, 23(12), 4145. https://doi.org/10.1007/s00500-018-3064-6
  • Niu, K., Cheng, C., Gao, H., & Zhou, X. (2019). Suggestions on accelerating the implementation of artificial intelligence technology in university information system. Proceedings of The 14th International Conference on Computer Science & Education (ICCSE 2019) (pp. 767-770). https://doi.org/10.1109/ICCSE.2019.8845378
  • Okonkwo, C. W., & Ade-Ibijola, A. (2021). Chatbots applications in education: A systematic review. Computers and Education: Artificial Intelligence, 2, 100033. https://doi.org/10.1016/j.caeai.2021.100033
  • Pedro, F. (2020). Applications of artificial intelligence to higher education: Possibilities, evidence, and challenges. IUL Research, 1(1), 61. https://doi.org/10.57568/iulres.v1i1.43
  • Rashid, T. A., & Aziz, N. K. (2016). Student academic performance using artificial intelligence. ZANCO Journal of Pure and Applied Sciences, 28(2), 56. https://www.researchgate.net/publication/291262353
  • Razia, B., Awwad, B., & Taqi, N. (2023). The relationship between artificial intelligence (AI) and its aspects in higher education. Development and Learning in Organizations, 37(3), 21. https://doi.org/10.1108/DLO-04-2022-0074
  • Salas-Pilco, S. Z., Xiao, K., & Hu, X. (2022). Artificial intelligence and learning analytics in teacher education: A systematic review. Education Sciences, 12(8), 569. https://doi.org/10.3390/educsci12080569
  • Silva, J., Romero, L., Solano, D., Fernandez, C., Lezama, O. B. P., & Rojas, K. (2021). Model for predicting academic performance through artificial intelligence. In V. Singh, V. Asari, S. Kumar, & R. Patel (Eds.), Computational methods and data engineering: Advances in intelligent systems and computing (pp. 519-525). Springer.
  • Slimi, Z., & Carballido, B. V. (2023). Navigating the ethical challenges of artificial intelligence in higher education: An analysis of seven global AI ethics policies. TEM Journal, 12(2), 590. https://doi.org/10.18421/TEM122-02
  • Talei, H., Benhaddou, D., Gamarra, C., Benhaddou, M., & Essaaidi, M. (2023). Identifying energy inefficiencies using self-organizing maps: Case of a highly efficient certified office building. Applied Sciences, 13(3), 1666. https://doi.org/10.3390/app13031666
  • Taşçı, G., & Çelebi, M. (2020). Eğitimde yeni bir paradigma: “Yükseköğretimde yapay zekâ”. OPUS International Journal of Society Researches, 16(29), 2346. https://doi.org/10.26466/opus.747634
  • Tiwari, R. (2023). The integration of AI and machine learning in education and its potential to personalize and improve student learning experiences. International Journal of Scientific Research in Engineering and Management, 7(2), 1. https://doi.org/10.55041/ijsrem17645
  • Uzun, Y., Tümtürk, A. Y., & Öztürk, H. (2021). Günümüzde ve gelecekte eğitim alanında kullanılan yapay zeka. 1st International Conference on Applied Engineering and Natural Sciences, 1-3 Kasım, Konya, Türkiye.
  • Wang, Y. (2021). When artificial intelligence meets educational leaders’ data-informed decision-making: A cautionary tale. Studies in Educational Evaluation, 69, 100872. https://doi.org/10.1016/j.stueduc.2020.100872
  • Wei, X., Sun, S., Wu, D., & Zhou, L. (2021). Personalized online learning resource recommendation based on artificial intelligence and educational psychology. Frontiers in Psychology, 12, 767837. https://doi.org/10.3389/fpsyg.2021.767837
  • Wollny, S., Schneider, J., Di Mitri, D., Weidlich, J., Rittberger, M., & Drachsler, H. (2021). Are we there yet? - A systematic literature review on chatbots in education. Frontiers in Artificial Intelligence, 4, 654924. https://doi.org/10.3389/frai.2021.654924
  • Xia, P. (2020). Application scenario of artificial intelligence technology in higher education. In J. Abawajy, K. K. Choo, R. Islam, Z. Xu, & M. Atiquzzaman (Eds.), Proceedings of The International Conference on Applications and Techniques in Cyber Intelligence (ATCI 2019) (pp. 221-226). https://doi.org/10.1007/978-3-030-25128-4_29
  • Yang, S., & Evans, C. (2019). Opportunities and challenges in using AI Chatbots in higher education. Proceedings of The 3rd International Conference on Education and E-Learning (ICEEL'19) (pp. 79-83). https://doi.org/10.1145/3371647.3371659
  • 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, 39. https://doi.org/10.1186/s41239-019-0171-0
  • Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021). A review of artificial intelligence (AI) in education from 2010 to 2020. Complexity, 8812542. https://doi.org/10.1155/2021/8812542
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Yükseköğretim Çalışmaları (Diğer)
Bölüm Makaleler
Yazarlar

Baris Uslu 0000-0001-5941-1507

Erken Görünüm Tarihi 13 Ekim 2023
Yayımlanma Tarihi 31 Aralık 2023
Gönderilme Tarihi 5 Eylül 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 19 Sayı: 2

Kaynak Göster

APA Uslu, B. (2023). Üniversitelerde Yapay Zekanın Kullanım Alanları: Potansiyel Yararları ve Olası Zorluklar. Eğitimde Kuram Ve Uygulama, 19(2), 227-239. https://doi.org/10.17244/eku.1355304