Öz
Artificial general intelligence (AGI) is expected to cause a revolution similar to the industrial revolution and affect our lives in many ways. The AGI revolution involves not only technological developments but also the process of human adaptation to this change. This study examines the possible implications of AGI on the role of the teacher. AGI is defined as technology with human-level cognitive abilities and has many uses in education and training. There are a limited number of studies in foreign literature examining the possible effects of AGI on teacher roles. In Turkey, there is no study on this subject. This study fills an important gap in order to increase our understanding of the possible effects of AGI, a new technological paradigm on a global scale, in the field of education and training. Document analysis, one of the qualitative research methods, was used in the study. As a result of the study, it was determined that AGI can support teachers in creating personalized learning environments, monitoring student performance, improving educational processes and providing equal opportunities in education. The importance of ethical issues such as personal data privacy, algorithmic bias and fair access were emphasized in the use of AGI. It was emphasized that the responsible and safe use of AGI in educational processes is a necessity. In this context, the necessity of creating a qualified teacher training plan for teachers to effectively adapt to the AGI era is emphasized.
Anahtar Kelimeler
Artificial General Intelligence (AGI) Education Teacher’s Role
Kaynakça
- Abramczyk, A., & Jurkowski, S. (2020). Cooperative learning as an evidence-based teaching strategy: What teachers know, believe, and how they use it. Journal of Education for Teaching, 46(3), 296–308. http://dx.doi.org/10.1080/02607476.2020.1733402
- Bundick, M. J., Quaglia, R. J., Corso, M. J., & Haywood, D. E. (2014). Promoting student engagement in the classroom. Teachers College Record, 116(4), 1–34. http://dx.doi.org/10.1177/016146811411600411
- Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success. Information Systems Frontiers, 25(1), 161–182. http://dx.doi.org/10.1007/s10796-022-10291-4
- Chibuye, M., & Phiri, J. (2023). Towards Artificial General Intelligence-A Survey of Hyperdimensional Computing and Vector Symbolic Architectures with Quantum Computing for Multivariate Predictions. Zambia ICT Journal, 7(2), 1–9. http://dx.doi.org/10.33260/zictjournal.v7i2.265
- Chounta, I.-A., Bardone, E., Raudsep, A., & Pedaste, M. (2022). Exploring teachers’ perceptions of Artificial Intelligence as a tool to support their practice in Estonian K-12 education. International Journal of Artificial Intelligence in Education, 32(3), 725–755. http://dx.doi.org/10.1007/s40593-021-00243-5
- Fei, N., Lu, Z., Gao, Y., Yang, G., Huo, Y., Wen, J., Lu, H., Song, R., Gao, X., & Xiang, T. (2022). Towards artificial general intelligence via a multimodal foundation model. Nature Communications, 13(1), 3094. http://dx.doi.org/10.1038/s41467-022-30761-2
- Flogie, A., & Aberšek, B. (2022). Artificial intelligence in education. Active Learning-Theory and Practice. Gamlath, S. (2022). Peer learning and the undergraduate journey: a framework for student success. Higher Education Research & Development, 41(3), 699–713. http://dx.doi.org/10.1080/07294360.2021.1877625
- Goertzel, B. (2014). Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence, 5(1), 1. http://dx.doi.org/10.2478/jagi-2014-0001
- Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial intelligence in education. Globethics Publications. http://dx.doi.org/10.58863/20.500.12424/4276068
- Kumpulainen, S., & Terziyan, V. (2022). Artificial General Intelligence vs. Industry 4.0: Do They Need Each Other? Procedia Computer Science, 200, 140–150. http://dx.doi.org/10.1016/j.procs.2022.01.213
- Latif, E., Mai, G., Nyaaba, M., Wu, X., Liu, N., Lu, G., Li, S., Liu, T., & Zhai, X. (2023). Artificial general intelligence (AGI) for education. ArXiv Preprint ArXiv:2304.12479.
- Lin, B., Chen, Z., Li, M., Lin, H., Xu, H., Zhu, Y., Liu, J., Cai, W., Yang, L., & Zhao, S. (2023). Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining. ArXiv Preprint ArXiv:2304.14204.
- Mahler, T. (2022). Regulating artificial general intelligence (AGI). In Law and Artificial Intelligence: Regulating AI and Applying AI in Legal Practice (pp. 521–540). Springer.
- McLean, S., Read, G. J. M., Thompson, J., Baber, C., Stanton, N. A., & Salmon, P. M. (2023). The risks associated with Artificial General Intelligence: A systematic review. Journal of Experimental & Theoretical Artificial Intelligence, 35(5), 649–663. http://dx.doi.org/10.1080/0952813X.2021.1964003
- Memarian, B., & Doleck, T. (2023). Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI), and higher education: A systematic review. Computers and Education: Artificial Intelligence, 100152. http://dx.doi.org/10.1016/j.caeai.2023.100152
- Nazaretsky, T., Yolcu, H. H., Ariely, M., & Alexandron, G. (2023). Towards Automated Assessment of Scientific Explanations in Turkish using Language Transfer.
- Obaid, O. I. (2023). From Machine Learning to Artificial General Intelligence: A Roadmap and Implications. Mesopotamian Journal of Big Data, 2023, 81–91. http://dx.doi.org/10.58496/MJBD/2023/012
- Pennachin, C., & Goertzel, B. (2007). Contemporary approaches to artificial general intelligence. In Artificial general intelligence (pp. 1–30). Springer.
- Poulos, A., & Mahony, M. J. (2008). Effectiveness of feedback: The students’ perspective. Assessment & Evaluation in Higher Education, 33(2), 143–154. http://dx.doi.org/10.1080/02602930601127869
- Rich, A. S., & Gureckis, T. M. (2019). Lessons for artificial intelligence from the study of natural stupidity. Nature Machine Intelligence, 1(4), 174–180. http://dx.doi.org/10.1038/s42256-019-0038-z
- Savoldi, B., Gaido, M., Bentivogli, L., Negri, M., & Turchi, M. (2021). Gender bias in machine translation. Transactions of the Association for Computational Linguistics, 9, 845–874. http://dx.doi.org/10.1162/tacl_a_00401
- Wentzel, K. R., & Watkins, D. E. (2002). Peer relationships and collaborative learning as contexts for academic enablers. School Psychology Review, 31(3), 366–377. http://dx.doi.org/10.1080/02796015.2002.12086161
- Yıldırım, Ş. (2006). Yıldırım A. & Şimşek H.(2006). Sosyal Bilimlerde Nitel Araştırma Yöntemleri, 5.
- Zhai, X., & Nehm, R. H. (2023). AI and formative assessment: The train has left the station. Journal of Research in Science Teaching. http://dx.doi.org/10.1002/tea.21885
- Zhao, L., Zhang, L., Wu, Z., Chen, Y., Dai, H., Yu, X., Liu, Z., Zhang, T., Hu, X., Jiang, X., Li, X., Zhu, D., Shen, D., & Liu, T. (2023). When Brain-inspired AI Meets AGI. http://dx.doi.org/10.1016/j.metrad.2023.100005
Öz
Yapay genel zekânın (YGZ), endüstri devrimine benzer bir devrime neden olacağı kabul edilmekte ve yaşamımızı birçok yönden etkileyeceği düşünülmektedir. YGZ devrimi, sadece teknolojik gelişmeleri değil, aynı zamanda insanların bu değişime adapte olma sürecini içermektedir. Bu çalışma, YGZ’nın öğretmen rolüne yapabileceği muhtemel etkileri incelemektedir. YGZ, insan düzeyinde bilişsel yeteneklere sahip teknoloji olarak tanımlanmakta ve eğitim-öğretimde birçok kullanım alanına sahiptir. YGZ’nın öğretmen rollerine muhtemel etkilerini inceleyen yabancı literatürde sınırlı sayıda çalışma bulunmaktadır. Türkiye özelinde ise bu konuda herhangi bir çalışmaya rastlanmamıştır. Bu çalışma, küresel ölçekte yeni bir teknolojik paradigma olan YGZ’nın eğitim-öğretim alanındaki muhtemel etkilerine dair anlayışımızı artırmak adına önemli bir boşluğu doldurmaktadır. Çalışmada, nitel araştırma yöntemlerinden doküman analizi kullanılmıştır. Çalışma sonucunda, YGZ'nın kişiselleştirilmiş öğrenme ortamları oluşturma, öğrenci performansını izleme, eğitim-öğretim süreçlerini geliştirme ve eğitimde fırsat eşitliği sağlama konularında öğretmenlere destek olabileceği belirlenmiştir. YGZ kullanımında, kişisel veri gizliliği, algoritmik önyargı ve adil erişim gibi etik konuların önemi vurgulanmıştır. YGZ’nın eğitim-öğretim süreçlerinde sorumlu ve güvenli bir şekilde kullanılımının bir gereklilik olduğu üzerinde durulmuştur. Bu bağlamda, öğretmenlerin YGZ çağına etkili bir şekilde adapte olabilmeleri için nitelikli bir öğretmen eğitimi planının oluşturulması zorunluluğu ortaya çıkarılmıştır.
Anahtar Kelimeler
Kaynakça
- Abramczyk, A., & Jurkowski, S. (2020). Cooperative learning as an evidence-based teaching strategy: What teachers know, believe, and how they use it. Journal of Education for Teaching, 46(3), 296–308. http://dx.doi.org/10.1080/02607476.2020.1733402
- Bundick, M. J., Quaglia, R. J., Corso, M. J., & Haywood, D. E. (2014). Promoting student engagement in the classroom. Teachers College Record, 116(4), 1–34. http://dx.doi.org/10.1177/016146811411600411
- Chen, Y., Jensen, S., Albert, L. J., Gupta, S., & Lee, T. (2023). Artificial intelligence (AI) student assistants in the classroom: Designing chatbots to support student success. Information Systems Frontiers, 25(1), 161–182. http://dx.doi.org/10.1007/s10796-022-10291-4
- Chibuye, M., & Phiri, J. (2023). Towards Artificial General Intelligence-A Survey of Hyperdimensional Computing and Vector Symbolic Architectures with Quantum Computing for Multivariate Predictions. Zambia ICT Journal, 7(2), 1–9. http://dx.doi.org/10.33260/zictjournal.v7i2.265
- Chounta, I.-A., Bardone, E., Raudsep, A., & Pedaste, M. (2022). Exploring teachers’ perceptions of Artificial Intelligence as a tool to support their practice in Estonian K-12 education. International Journal of Artificial Intelligence in Education, 32(3), 725–755. http://dx.doi.org/10.1007/s40593-021-00243-5
- Fei, N., Lu, Z., Gao, Y., Yang, G., Huo, Y., Wen, J., Lu, H., Song, R., Gao, X., & Xiang, T. (2022). Towards artificial general intelligence via a multimodal foundation model. Nature Communications, 13(1), 3094. http://dx.doi.org/10.1038/s41467-022-30761-2
- Flogie, A., & Aberšek, B. (2022). Artificial intelligence in education. Active Learning-Theory and Practice. Gamlath, S. (2022). Peer learning and the undergraduate journey: a framework for student success. Higher Education Research & Development, 41(3), 699–713. http://dx.doi.org/10.1080/07294360.2021.1877625
- Goertzel, B. (2014). Artificial general intelligence: concept, state of the art, and future prospects. Journal of Artificial General Intelligence, 5(1), 1. http://dx.doi.org/10.2478/jagi-2014-0001
- Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial intelligence in education. Globethics Publications. http://dx.doi.org/10.58863/20.500.12424/4276068
- Kumpulainen, S., & Terziyan, V. (2022). Artificial General Intelligence vs. Industry 4.0: Do They Need Each Other? Procedia Computer Science, 200, 140–150. http://dx.doi.org/10.1016/j.procs.2022.01.213
- Latif, E., Mai, G., Nyaaba, M., Wu, X., Liu, N., Lu, G., Li, S., Liu, T., & Zhai, X. (2023). Artificial general intelligence (AGI) for education. ArXiv Preprint ArXiv:2304.12479.
- Lin, B., Chen, Z., Li, M., Lin, H., Xu, H., Zhu, Y., Liu, J., Cai, W., Yang, L., & Zhao, S. (2023). Towards Medical Artificial General Intelligence via Knowledge-Enhanced Multimodal Pretraining. ArXiv Preprint ArXiv:2304.14204.
- Mahler, T. (2022). Regulating artificial general intelligence (AGI). In Law and Artificial Intelligence: Regulating AI and Applying AI in Legal Practice (pp. 521–540). Springer.
- McLean, S., Read, G. J. M., Thompson, J., Baber, C., Stanton, N. A., & Salmon, P. M. (2023). The risks associated with Artificial General Intelligence: A systematic review. Journal of Experimental & Theoretical Artificial Intelligence, 35(5), 649–663. http://dx.doi.org/10.1080/0952813X.2021.1964003
- Memarian, B., & Doleck, T. (2023). Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI), and higher education: A systematic review. Computers and Education: Artificial Intelligence, 100152. http://dx.doi.org/10.1016/j.caeai.2023.100152
- Nazaretsky, T., Yolcu, H. H., Ariely, M., & Alexandron, G. (2023). Towards Automated Assessment of Scientific Explanations in Turkish using Language Transfer.
- Obaid, O. I. (2023). From Machine Learning to Artificial General Intelligence: A Roadmap and Implications. Mesopotamian Journal of Big Data, 2023, 81–91. http://dx.doi.org/10.58496/MJBD/2023/012
- Pennachin, C., & Goertzel, B. (2007). Contemporary approaches to artificial general intelligence. In Artificial general intelligence (pp. 1–30). Springer.
- Poulos, A., & Mahony, M. J. (2008). Effectiveness of feedback: The students’ perspective. Assessment & Evaluation in Higher Education, 33(2), 143–154. http://dx.doi.org/10.1080/02602930601127869
- Rich, A. S., & Gureckis, T. M. (2019). Lessons for artificial intelligence from the study of natural stupidity. Nature Machine Intelligence, 1(4), 174–180. http://dx.doi.org/10.1038/s42256-019-0038-z
- Savoldi, B., Gaido, M., Bentivogli, L., Negri, M., & Turchi, M. (2021). Gender bias in machine translation. Transactions of the Association for Computational Linguistics, 9, 845–874. http://dx.doi.org/10.1162/tacl_a_00401
- Wentzel, K. R., & Watkins, D. E. (2002). Peer relationships and collaborative learning as contexts for academic enablers. School Psychology Review, 31(3), 366–377. http://dx.doi.org/10.1080/02796015.2002.12086161
- Yıldırım, Ş. (2006). Yıldırım A. & Şimşek H.(2006). Sosyal Bilimlerde Nitel Araştırma Yöntemleri, 5.
- Zhai, X., & Nehm, R. H. (2023). AI and formative assessment: The train has left the station. Journal of Research in Science Teaching. http://dx.doi.org/10.1002/tea.21885
- Zhao, L., Zhang, L., Wu, Z., Chen, Y., Dai, H., Yu, X., Liu, Z., Zhang, T., Hu, X., Jiang, X., Li, X., Zhu, D., Shen, D., & Liu, T. (2023). When Brain-inspired AI Meets AGI. http://dx.doi.org/10.1016/j.metrad.2023.100005
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Eğitim Teknolojisi ve Bilgi İşlem |
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 29 Ocak 2024 |
| Gönderilme Tarihi | 30 Ekim 2023 |
| Kabul Tarihi | 27 Ocak 2024 |
| Yayımlandığı Sayı | Yıl 2024 Cilt: 10 Sayı: 1 |
