Yapay Zekâ ve Pedagoji: Eğitimde Fırsatlar ve Zorluklar

Yazarlar

DOI:

https://doi.org/10.5281/zenodo.12637335

Anahtar Kelimeler:

Yapay zekâ, pedagoji, eğitimde teknoloji entegrasyonu, eğitimde yapay zekâ kullanımı

Özet

Günümüzde eğitime entegre edilmeye çalışılan en yeni teknolojilerden birisi de yapay zekadır. Yapay zekânın eğitimdeki rolünü sadece teknolojik bir yenilik olarak görmek yerine, pedagojik açıdan da işlevi olan bir unsur olarak ele almak, bu teknolojinin eğitime katkısını anlamada yol göstericidir. Bu çalışmanın amacı; yapay zekânın eğitimdeki rolünü ve etkisini pedagojik çerçevede ele alan nitelikli çalışmaları inceleyerek, yapay zekânın pedagojiyi nasıl destekleyebileceğini ve pedagojik açıdan getirebileceği olumsuz durumları ortaya koymak ve bu konudaki Türkçe literatüre katkı sunmaktır. Çalışmada, nitel araştırma yöntemlerinden doküman incelemesi tekniği kullanılmıştır ve araştırmaya kaynak olarak Web of Science veri tabanında yer alan ilgili çalışmalar incelenmiştir. Araştırma sonuçları, yapay zekâ uygulamalarının eğitim süreçlerini dönüştürme potansiyeline sahip olduğunu ve özellikle öğretim yöntemleri, teknikleri ve stratejilerini çeşitli yönlerden destekleyebileceğini ortaya koymaktadır. Yapay zekânın kişiselleştirilmiş ve farklılaştırılmış öğrenme, dil öğrenme, eleştirel düşünme becerileri, aktif öğrenme, uyarlanabilir öğrenme, işbirlikçi öğrenme ortamları yaratma, yaratıcı öğrenme, probleme dayalı öğrenme, proje tabanlı öğrenme, öz yönlendirmeli öğrenme, kendi hızında öğrenme, öz düzenlemeli öğrenme ve simülasyon tabanlı öğrenme gibi pedagojik süreçlere önemli katkılar sunabileceği görülmüştür. Bununla birlikte, yapay zekâ uygulamalarının eğitimde kullanımının bazı pedagojik riskler ve olumsuzluklar barındırdığı da tespit edilmiştir. Dijital okuryazarlık eksikliği, öğrencilerin sosyal becerilerinin gelişememe riski, derin öğrenmenin yerini yüzeysel öğrenmenin alması, yapay zekâya aşırı bağımlılık nedeniyle bilişsel becerilerin gerilemesi ve sürekli takip edilme duygusunun yarattığı olumsuz etkiler bu riskler arasında yer almaktadır. Araştırma sonuçlarına dayanarak, yapay zekânın eğitimde bilinçli ve etkili bir şekilde kullanılmasına katkı sunmak ve gelecekteki araştırmalara yol gösterici olabilmek adına bazı öneriler yapılmıştır.

Referanslar

Andreeva, J. V., Sibgatullina, T., & Ratner, F. L. (2020). Design of students’ creative activity in the conditions of «Digital Freedom»: Comparative analysis of group and individual strategies. ARPHA Proceedings. https://doi.org/10.3897/ap.2.e0131

Arends, R. (2011). Learning to teach. McGraw-Hill Education.

Arf, C. (1959). Makine düşünebilir mi ve nasıl düşünebilir. Atatürk Üniversitesi-Üniversite Çalışmalarını Muhite Yayma ve Halk Eğitimi Yayınları Konferanslar Serisi, (1), 91-103.

Bartolomé, L. I. (1994). Teaching strategies: Their possibilities and limitations. Language and learning: Educating linguistically diverse students, 199-223.

Bautista, R. G. (2015). Optimizing classroom instruction through self-paced learning prototype. Journal of Technology and Science Educaton (JOTSE), 5(3), 184-193.

Bender, S. M. (2024). Awareness of Artificial Intelligence as an essential digital literacy: ChatGPT and Gen-AI in the classroom. Changing English, 1–14. https://doi.org/10.1080/1358684x.2024.2309995

Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., & Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12405-0

Cannon, R. (2001). Pedagogy: A point of view. Teaching in Higher Education, 6(3), 415–419. https://doi.org/10.1080/13562510120061250

Cavanagh, T., Chen, B., Lahcen, R. a. M., & Paradiso, J. R. (2020). Constructing a design framework and pedagogical Approach for adaptive Learning in Higher Education: A Practitioner’s perspective. International Review of Research in Open and Distance Learning, 21(1), 172–196. https://doi.org/10.19173/irrodl.v21i1.4557

Ceylan, S. (2021, April). Artificial Intelligence in Architecture: An Educational Perspective. In CSEDU (1) (pp. 100-107). https://doi.org/10.5220/0010444501000107

Chapelle, C. A. (2009). The relationship between second language acquisition theory and computer‐assisted language learning. The modern language journal, 93, 741-753.

Chaturvedi, I., Cambria, E., & Welsch, R. E. (2023). Teaching simulations supported by artificial intelligence in the real world. Education Sciences, 13(2), 187. https://doi.org/10.3390/educsci13020187

Chen, L., Ifenthaler, D., Yau, J. Y., & Sun, W. (2024). Artificial intelligence in entrepreneurship education: a scoping review. Education + Training. https://doi.org/10.1108/et-05-2023-0169

Christiansen, S., Bøje, R. B., & Frederiksen, K. (2015). The use of problem- and simulation-based learning: The student’s perspective. Nordic Journal of Nursing Research, 35(3), 186–192. https://doi.org/10.1177/0107408315591777

Connolly, C., Hernon, O., Carr, P., Worlikar, H., McCabe, I., Doran, J., Walsh, J. C., Simpkin, A. J., & O’Keeffe, D. T. (2023b). Artificial Intelligence in Interprofessional Healthcare Practice Education – Insights from the Home Health Project, an Exemplar for Change. Computers in the Schools, 40(4), 412–429. https://doi.org/10.1080/07380569.2023.2247393

Cooper, G., & Tang, K. (2024). Pixels and Pedagogy: Examining Science Education Imagery by Generative Artificial Intelligence. Journal of Science Education and Technology. https://doi.org/10.1007/s10956-024-10104-0

Crawford, J., Vallis, C., Yang, J., Fitzgerald, R., O’Dea, C., & Cowling, M. (2023). Editorial: Artificial Intelligence is Awesome, but Good Teaching Should Always Come First. Journal of University Teaching & Learning Practice, 20(7). https://doi.org/10.53761/1.20.7.01

Dai, J., Wang, D., Yang, X., & Wei, X. (2016). Design and implementation of a group decision support system for university innovation projects evaluation. 2016 11th International Conference on Computer Science & Education (ICCSE) (pp. 148-151). IEEE.

Davies, D., Jindal-Snape, D., Collier, C., Digby, R., Hay, P., & Howe, A. (2013). Creative learning environments in education—A systematic literature review. Thinking Skills and Creativity, 8, 80–91. https://doi.org/10.1016/j.tsc.2012.07.004

Doroudi, S. (2020). The Bias-Variance Tradeoff: How Data Science Can Inform Educational Debates. AERA Open, 6(4), 233285842097720. https://doi.org/10.1177/2332858420977208

Duolingo. (t.y.). Hakkımızda - Duolingo. https://www.duolingo.com/info adresinden 30 Haziran 2024 tarihinde erişilmiştir.

Essien, A., Bukoye, O. T., O’Dea, X., & Kremantzis, M. (2024). The influence of AI text generators on critical thinking skills in UK business schools. Studies in Higher Education, 1–18. https://doi.org/10.1080/03075079.2024.2316881

Gabrielli, S., Rizzi, S., Carbone, S., & Donisi, V. (2020). A chatbot-based coaching intervention for adolescents to promote life skills: pilot study. JMIR human factors, 7(1). https://doi.org/10.2196/16762

Galés, N. L., & Gallon, R. (2019). Integrating Education, Technology, and SDG’s: a three-pronged collaboration. Innovations, Technologies and Research in Education, 10–22. https://doi.org/10.22364/atee.2019.itre.01

Graesser, A., & McNamara, D. (2010). Self-Regulated learning in learning environments with pedagogical agents that interact in natural language. Educational Psychologist :/Educational Psychologist, 45(4), 234–244. https://doi.org/10.1080/00461520.2010.515933

Hackathorn, J., Solomon, E. D., Blankmeyer, K. L., Tennial, R. E., & Garczynski, A. M. (2011). Learning by Doing: An Empirical Study of Active Teaching Techniques. Journal of Effective Teaching, 11(2), 40-54.

Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004

Harrington, J. (2024). A Mixed Methods Pilot Study to Evaluate User Engagement with MedMicroMaps: A Novel Interactive E-learning Tool for Medical Microbiology. Medical Science Educator. https://doi.org/10.1007/s40670-024-02047-3

Hasanova, N., Abduazizov, B., & Khujakulov, R. (2021). The main differences between teaching approaches, methods, procedures, techniques, styles and strategies. JournalNX, 7(02), 371-375.

Hew, K. F., Huang, W., Du, J., & Jia, C. (2023). Using chatbots to support student goal setting and social presence in fully online activities: Learner engagement and perceptions. Journal of Computing in Higher Education, 35(1), 40–68. https://doi.org/10.1007/s12528-022-09338-x

Hood Cattaneo, K. (2017). Telling Active Learning Pedagogies Apart: from theory to practice. Journal of New Approaches in Educational Research (NAER Journal), 6(2), 144-152. University of Alicante. Retrieved June 8, 2024 from https://www.learntechlib.org/p/180107/.

Jiménez-García, E., Orenes-Martínez, N., & López-Fraile, L. A. (2023). Rueda de la Pedagogía para la Inteligencia Artificial: adaptación de la Rueda de Carrington. Revista Iberoamericana De Educación a Distancia, 27(1), 87–113. https://doi.org/10.5944/ried.27.1.37622

Kaddoura, M. (2013). Think pair share: A teaching learning strategy to enhance students' critical thinking. Educational Research Quarterly, 36(4), 3-24.

Karasar, N. (2009). Bilimsel araştırma yöntemleri. Nobel Yayıncılık.

Knox, J., Wang, Y., & Gallagher, M. (2019). Introduction: AI, inclusion, and ‘Everyone Learning Everything.’ In Perspectives on rethinking and reforming education (pp. 1–13). https://doi.org/10.1007/978-981-13-8161-4_1

Kokotsaki, D., Menzies, V., & Wiggins, A. (2016). Project-based learning: A review of the literature. Improving Schools, 19(3), 267–277. https://doi.org/10.1177/1365480216659733

Kong, S., Lee, J. C., & Tsang, O. (2024). A pedagogical design for self-regulated learning in academic writing using text-based generative artificial intelligence tools: 6-P pedagogy of plan, prompt, preview, produce, peer-review, portfolio-tracking. Research and Practice in Technology Enhanced Learning/Research and Practice in Technology Enchanced Learning, 19, 030. https://doi.org/10.58459/rptel.2024.19030

Kucirkova, N., & Gray, S. L. (2023). Beyond personalization: embracing democratic learning within artificially intelligent systems. Educational Theory, 73(4), 469–489. https://doi.org/10.1111/edth.12590

Kumar, J. A. (2021). Educational chatbots for project-based learning: Investigating learning outcomes for a team-based design course. International Journal of Educational Technology in Higher Education, 18(1), 1-28. https://doi.org/10.1186/s41239-021-00302-w

Kumar, R. (2023). Faculty members’ use of artificial intelligence to grade student papers: a case of implications. International Journal for Educational Integrity, 19(1). https://doi.org/10.1007/s40979-023-00130-7

Labadze, L., Grigolia, M., & Machaidze, L. (2023). Role of AI chatbots in education: systematic literature review. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00426-1

Lara, G. E. T. (2023). Artificial intelligence (AI) and the 21st Century University: Discussion on a New University Scenary. Revista Românească Pentru Educaţie Multidimensională, 15(4), 489–506. https://doi.org/10.18662/rrem/15.4/806

Loeckx, J. (2016). Blurring boundaries in Education: Context and impact of MOOCs. International Review of Research in Open and Distance Learning, 17(3). https://doi.org/10.19173/irrodl.v17i3.2395

Mandaniyati, R., & Sophya, I. V. (2017). The Application of Question and Answer Method to Improve the Ability of Students Achievement. BRITANIA Journal of English Teaching, 1(2).

McCarthy, J., Minsky, M. L., & Shannon, C. E. (1955). A proposal for the Dartmouth summer research project on artificial intelligence - August 31, 1955. Ai Magazine, 27(4).

McGuire, A., Qureshi, W., & Saad, M. (2024). A constructivist model for leveraging GenAI tools for individualized, peer-simulated feedback on student writing. International Journal of Technology in Education, 7(2), 326–352. https://doi.org/10.46328/ijte.639

Mirijamdotter, A., Somerville, M. M., & Holst, M. (2006). An interactive and iterative evaluation approach for creating collaborative learning environments. The Electronic Journal of Information Systems Evaluation, 9(2), 83–92. https://scholarlycommons.pacific.edu/libraries-articles/19

Morales-García, W. C., Sairitupa-Sanchez, L. Z., Morales-García, S. B., & Morales-García, M. (2024). Development and validation of a scale for dependence on artificial intelligence in university students. Frontiers in Education, 9. https://doi.org/10.3389/feduc.2024.1323898

Morris, T. H. (2019). Self-directed learning: A fundamental competence in a rapidly changing world. International Review of Education, 65(4), 633–653. https://doi.org/10.1007/s11159-019-09793-2

Nabiyev, V. ve Erümit, A.K. (2020). Eğitimde Yapay Zeka – Kuramdan Uygulamaya. Ankara: Pegem Akademi.

Nichols, T. P., Thrall, A., Quiros, J., & Dixon‐Román, E. (2024). Speculative Capture: Literacy after Platformization. Reading Research Quarterly, 59(2), 211–218. https://doi.org/10.1002/rrq.535

Peng, H., Ma, S., & Spector, J. M. (2019). Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment. Smart Learning Environments, 6(1). https://doi.org/10.1186/s40561-019-0089-y

Petersen, A. K., & Gundersen, P. B. (2019). Challenges in designing personalised learning paths in SPOCs. Designs for Learning, 11(1), 72–79. https://doi.org/10.16993/dfl.112

Saltman, K. J. (2020). Artificial intelligence and the technological turn of public education privatization: In defence of democratic education. London Review of Education, 18(2). https://doi.org/10.14324/lre.18.2.04

Shah, R. K., & Campus, S. (2021). Conceptualizing and defining pedagogy. IOSR journal of research & method in education, 11(1), 6-29.

Sims, R. (2012). Beyond instructional design: Making learning design a reality. Journal of Learning Design, 1(2). https://doi.org/10.5204/jld.v1i2.11

So, H., & Kim, B. (2009). Learning about problem based learning: Student teachers integrating technology, pedagogy and content knowledge. Australasian Journal of Educational Technology, 25(1). https://doi.org/10.14742/ajet.1183

Song, P., & Wang, X. (2020). A bibliometric analysis of worldwide educational artificial intelligence research development in recent twenty years. Asia Pacific Education Review/Asia Pacific Education Review, 21(3), 473–486. https://doi.org/10.1007/s12564-020-09640-2

Tam, W., Huynh, T., Tang, A., Luong, S., Khatri, Y., & Zhou, W. (2023). Nursing education in the age of artificial intelligence powered Chatbots (AI-Chatbots): Are we ready yet? Nurse Education Today, 129, 105917. https://doi.org/10.1016/j.nedt.2023.105917

Tsui, L. (2002). Fostering Critical Thinking through Effective Pedagogy. The Journal of Higher Education, 73(6), 740–763. https://doi.org/10.1080/00221546.2002.11777179

Turing, A. M. (1950). Computing machinery and intelligence. In Parsing the Turing Test: Philosophical and Methodological Issues in the Quest for the Thinking Computer. https://doi.org/10.1007/978-1-4020-6710-5_3

Useche, A. C., Galvis, Á. H., Arceo, F. D., Rivera, A. E. P., & Muñoz-Reyes, C. (2022). Reflexive pedagogy at the heart of educational digital transformation in Latin American higher education institutions. International Journal of Educational Technology in Higher Education, 19(1). https://doi.org/10.1186/s41239-022-00365-3

Vančová, H. (2023). AI and AI-powered tools for pronunciation training. Journal of Language and Cultural Education, 11(3), 12–24. https://doi.org/10.2478/jolace-2023-0022

Wang, C., & Lin, J. J. (2023). Utilizing artificial intelligence to support analyzing self-regulated learning: A preliminary mixed-methods evaluation from a human-centered perspective. Computers in Human Behavior, 144, 107721. https://doi.org/10.1016/j.chb.2023.107721

Wise, K. C., & Okey, J. R. (1983). A meta‐analysis of the effects of various science teaching strategies on achievement. Journal of Research in Science Teaching, 20(5), 419–435. https://doi.org/10.1002/tea.3660200506

Xiaolei, S., & Teng, M. F. (2024). Three-Wave Cross-Lagged model on the correlations between critical thinking skills, Self-Directed learning competency and AI-Assisted writing. Thinking Skills and Creativity, 52, 101524. https://doi.org/10.1016/j.tsc.2024.101524

Xu, M., David, J. M., & Kim, S. H. (2018). The Fourth Industrial Revolution: Opportunities and challenges. International Journal of Financial Research, 9(2), 90. https://doi.org/10.5430/ijfr.v9n2p90

Yıdırım, A., & Şimşek, H. (2008). Sosyal bilimlerde nitel araştırma yöntemleri (7. Baskı). Seçkin Yayıncılık.

İndir

Yayınlanmış

2024-06-30

Nasıl Atıf Yapılır

Altun, E. (2024). Yapay Zekâ ve Pedagoji: Eğitimde Fırsatlar ve Zorluklar. Dijital Teknolojiler Ve Eğitim Dergisi, 3(1), 80–95. https://doi.org/10.5281/zenodo.12637335
Views
  • Özet 363
  • PDF 168

Benzer Makaleler

1 2 > >> 

Bu makale için ayrıca gelişmiş bir benzerlik araması başlat yapabilirsiniz.