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When Class Time Falls Short: An Alternative Path to Application-Based Learning with GenAI

Yıl 2025, Cilt: 15 Sayı: 1, 128 - 141, 30.06.2025
https://doi.org/10.54370/ordubtd.1691860

Öz

This study examines the impact of GenAI (Generative Artificial Intelligence) supported application-based learning on high school students' academic achievement and course perceptions in the programming languages course. The study was conducted over six weeks with 77 10th-grade students in a public high school. A quasi-experimental design was used, involving two experimental groups and one control group. While one experimental group engaged in application-based activities under teacher guidance in class, the other completed the same activities at out-of-class using ChatGPT prompts. The control group followed the standard curriculum. Quantitative data were collected using an achievement test and course evaluation scale. One-way ANOVA results indicated no statistically significant difference in academic achievement among the groups. But the mean scores of the students in the experimental groups were higher than the control group. Moreover, students in both experimental groups reported significantly more positive course perceptions compared to the control group, particularly in the dimensions of course, instructor, and method-technique. Furthermore, while a weak positive correlation was found between course perception and academic achievement, it was not statistically significant. The findings highlight that although short-term academic gains may not differ significantly, both in-class application-based activities and GenAI-supported out-of-class activities enhance students’ perception of the course. The study underscores the potential of GenAI tools as pedagogical aids in promoting active learning, especially when in-class application time is limited. It suggests increasing the number of application-based course hours in the curriculum and emphasizes that, in cases where this is not possible, GenAI-supported out-of-class activities can be considered as an alternative.

Etik Beyan

There are no ethical issues with the publication of this article.

Kaynakça

  • Åkerfeldt, A., Kjällander, S., & Petersen, P. (2024). A research review of computational thinking and programming in education. Technology, Pedagogy and Education, 33(3), 375–390. https://doi.org/10.1080/1475939X.2024.2316087
  • Aydınlar, A., Mavi, A., Kütükçü, E., Kırımlı, E. E., Alış, D., Akın, A., & Altıntaş, L. (2024). Awareness and level of digital literacy among students receiving health-based education. BMC Medical Education, 24(1), 38. https://doi.org/10.1186/s12909-024-05025-w
  • Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 12983. https://doi.org/10.3390/su151712983
  • Başol, G. (2019). Eğitimde ölçme ve değerlendirme. Pegem Akademi Yayıncılık.
  • Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
  • Bozkurt, A., & Sharma, R. C. (2023). Generative AI and prompt engineering: The art of whispering to let the genie out of the algorithmic world. Asian Journal of Distance Education, 18(2), i-vii. https://doi.org/10.5281/zenodo.8174941
  • Büyüköztürk, Ş., (2024). Sosyal bilimler için veri analizi el kitabı istatistik, araştırma deseni SPSS uygulamaları ve yorum. Pegem Akademi Yayıncılık.
  • Büyüköztürk, Ş., Akgün, Ö. E., Demirel, F., Karadeniz, Ş., & Çakmak, E. K. (2024). Eğitimde bilimsel araştırma yöntemleri. Pegem Akademi Yayıncılık.
  • Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452. https://doi.org/10.1007/s10956-023-10039-y
  • Dai, Y., Liu, A., & Lim, C. P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. Procedia CIRP, 119, 84-90. https://doi.org/10.1016/j.procir.2023.05.002
  • Dogan, M. E., Goru Dogan, T., & Bozkurt, A. (2023). The use of artificial intelligence (AI) in online learning and distance education processes: A systematic review of empirical studies. Applied Sciences, 13(5), 3056. https://doi.org/10.3390/app13053056
  • Duffy, T.M., & Jonassen, D.H. (1992). Constructivism and the technology of instruction: A conversation (1st ed.). Routledge. https://doi.org/10.4324/9780203461976
  • Hong, E., Wan, M., & Peng, Y. (2011). Discrepancies between students' and teachers' perceptions of homework. Journal of Advanced Academics, 22(2), 280–308. https://doi.org/10.1177/1932202X1102200205
  • Hsu, Y. C., & Ching, Y. H. (2023). Generative artificial intelligence in education, part one: The dynamic frontier. TechTrends, 67(4), 603-607. https://doi.org/10.1007/s11528-023-00863-9
  • Kadaruddin, K. (2023). Empowering education through Generative AI: Innovative instructional strategies for tomorrow's learners. International Journal of Business, Law, and Education, 4(2), 618-625. https://doi.org/10.56442/ijble.v4i2.215
  • Khoo, E., Hight, C., Torrens, R. & Cowie, B. (2017). Software Literacy: Education and beyond. In Software Literacy. Springer Briefs in Education (pp. 91-99). Springer. https://doi.org/10.1007/978-981-10-7059-4_6
  • Kılıç Çakmak, E., Taşkın, N., & Kokoç, M., (2017). Öğrenme yaklaşımlarının öğretim teknolojileri alanındaki yeri ve önemi. In H. F. Odabaşı, B. Akkoyunlu, & A. İşman (Ed.), Eğitim Teknolojileri Okumaları 2017 (pp. 451-465). TOJET- The Turkish Online Journal of Educational Technology. http://www.tojet.net/e-book/eto_2017.pdf
  • Koç, A., & Bulut, İ. (2022). Course evaluation scale (CES): Validity and reliability study. Religious Studies, 25(63), 501-528. https://doi.org/10.15745/da.1159706
  • Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
  • Lodge, J. M., Thompson, K., & Corrin, L. (2023). Mapping out a research agenda for generative artificial intelligence in tertiary education. Australasian Journal of Educational Technology, 39(1), 1-8. https://doi.org/10.14742/ajet.8695
  • Macrides, E., Miliou, O., & Angeli, C. (2022). Programming in early childhood education: A systematic review. International Journal of Child-Computer Interaction, 32, 100396. https://doi.org/10.1016/j.ijcci.2021.100396
  • MEB, (2023). Ortaöğretim bilişim teknolojileri ve yazılım dersi: Öğretim programı. Milli Eğitim Bakanlığı. https://mufredat.meb.gov.tr/ProgramDetay.aspx?PID=1663
  • Medeiros, R. P., Ramalho, G. L., & Falcão, T. P. (2019). A systematic literature review on teaching and learning introductory programming in higher education. IEEE Transactions on Education, 62(2), 77–90. https://doi.org/10.1109/TE.2018.2864133
  • Monib, W. K., Qazi, A., & Mahmud, M. M. (2025). Exploring learners’ experiences and perceptions of ChatGPT as a learning tool in higher education. Education and Information Technologies, 30(1), 917-939. https://doi.org/10.1007/s10639-024-13065-4
  • Núñez, J. C., Suárez, N., Rosário, P., Vallejo, G., Cerezo, R., & Valle, A. (2015). Teachers’ feedback on homework, homework-related behaviors, and academic achievement. The Journal of Educational Research, 108(3), 204–216. https://doi.org/10.1080/00220671.2013.878298
  • Obenza, B. N., Salvahan, A., Rios, A. N., Solo, A., Alburo, R. A., & Gabila, R. J. (2024). University students' perception and use of ChatGPT: Generative artificial intelligence (AI) in higher education. International Journal of Human Computing Studies, 5(12), 5-18. https://ssrn.com/abstract=4724968
  • Pavlik, J. V. (2025). Considering the pedagogical benefits of generative artificial intelligence in higher education: applying constructivist learning theory. In Generative AI in Higher Education (pp. 46-58). Edward Elgar Publishing. https://doi.org/10.4337/9781035326020.00014
  • Reichert, F., Zhang, D., Law, N. W., Wong, G. K., & de la Torre, J. (2020). Exploring the structure of digital literacy competence assessed using authentic software applications. Educational Technology Research and Development, 68, 2991-3013. https://doi.org/10.1007/s11423-020-09825-x
  • Rush Hovde, M., & Renguette, C. C. (2017). Technological literacy: A framework for teaching technical communication software tools. Technical Communication Quarterly, 26(4), 395–411. https://doi.org/10.1080/10572252.2017.1385998
  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson Publications.
  • Vee, A. (2017). Coding literacy: How computer programming is changing writing. Cambridge, MA: MIT Press.
  • Yilmaz, R., & Yilmaz, F. G. K. (2023). The effect of generative artificial intelligence (AI)-based tool use on students' computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 4, 100147. https://doi.org/10.1016/j.caeai.2023.100147

Ders Zamanı Yetmediğinde: GenAI ile Uygulama Tabanlı Öğrenmeye Alternatif Bir Yol

Yıl 2025, Cilt: 15 Sayı: 1, 128 - 141, 30.06.2025
https://doi.org/10.54370/ordubtd.1691860

Öz

Bu çalışmada GenAI (Üretken Yapay Zekâ) destekli öğrenmenin lise öğrencilerinin programlama dilleri dersindeki akademik başarılarına ve ders algılarına etkisi incelenmektedir. Çalışma, bir devlet lisesindeki 77 onuncu sınıf öğrencisi ile altı hafta boyunca yürütülmüştür. İki deney grubu ve bir kontrol grubunun yer aldığı yarı deneysel bir tasarım kullanılmıştır. Bir deney grubu, sınıfta öğretmen rehberliğinde uygulamalı programlama etkinliklerine katılırken, diğeri aynı etkinlikleri ChatGPT tarafından oluşturulan istemleri kullanarak sınıf dışında tamamlamıştır. Kontrol grubu standart müfredatı takip etmiştir. Nicel veriler, bir başarı testi ve ders değerlendirme ölçeği kullanılarak toplanmıştır. Tek yönlü ANOVA sonuçları, gruplar arasında akademik başarıda istatistiksel olarak anlamlı bir fark olmadığını göstermiş olsa da deney grubundaki öğrencilerin puanları daha yüksektir. Ayrıca, her iki deney grubundaki öğrenciler ders, öğretmen ve yöntem-teknik boyutlarında, kontrol grubuna kıyasla daha olumlu ders algısına sahiptir. Ders algısı ile akademik başarı arasında anlamlı olmayan zayıf bir pozitif ilişki bulunmuştur. Bulgular, kısa vadeli akademik kazanımların önemli ölçüde farklılık göstermeyebileceğini vurgulasa da hem sınıf içi etkinlilerin hem de GenAI destekli sınıf dışı etkinliklerin öğrencilerin ders algısını geliştirdiğini ortaya koymaktadır. Çalışma, özellikle sınıfta içi uygulama süresi sınırlı olduğunda, GenAI araçlarının aktif öğrenmeyi teşvik etmedeki pedagojik potansiyeline işaret etmektedir. Bu bağlamda bu çalışma uygulama tabanlı sınıf içi etkinliklerin artırılmasını ve mümkün olmadığı durumlarda GenAI destekli etkinliklerin alternatif olarak değerlendirilebileceğini vurgulamaktadır.

Kaynakça

  • Åkerfeldt, A., Kjällander, S., & Petersen, P. (2024). A research review of computational thinking and programming in education. Technology, Pedagogy and Education, 33(3), 375–390. https://doi.org/10.1080/1475939X.2024.2316087
  • Aydınlar, A., Mavi, A., Kütükçü, E., Kırımlı, E. E., Alış, D., Akın, A., & Altıntaş, L. (2024). Awareness and level of digital literacy among students receiving health-based education. BMC Medical Education, 24(1), 38. https://doi.org/10.1186/s12909-024-05025-w
  • Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023). Transforming education: A comprehensive review of generative artificial intelligence in educational settings through bibliometric and content analysis. Sustainability, 15(17), 12983. https://doi.org/10.3390/su151712983
  • Başol, G. (2019). Eğitimde ölçme ve değerlendirme. Pegem Akademi Yayıncılık.
  • Baidoo-Anu, D., & Ansah, L. O. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. Journal of AI, 7(1), 52-62. https://doi.org/10.61969/jai.1337500
  • Bozkurt, A., & Sharma, R. C. (2023). Generative AI and prompt engineering: The art of whispering to let the genie out of the algorithmic world. Asian Journal of Distance Education, 18(2), i-vii. https://doi.org/10.5281/zenodo.8174941
  • Büyüköztürk, Ş., (2024). Sosyal bilimler için veri analizi el kitabı istatistik, araştırma deseni SPSS uygulamaları ve yorum. Pegem Akademi Yayıncılık.
  • Büyüköztürk, Ş., Akgün, Ö. E., Demirel, F., Karadeniz, Ş., & Çakmak, E. K. (2024). Eğitimde bilimsel araştırma yöntemleri. Pegem Akademi Yayıncılık.
  • Cooper, G. (2023). Examining science education in ChatGPT: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452. https://doi.org/10.1007/s10956-023-10039-y
  • Dai, Y., Liu, A., & Lim, C. P. (2023). Reconceptualizing ChatGPT and generative AI as a student-driven innovation in higher education. Procedia CIRP, 119, 84-90. https://doi.org/10.1016/j.procir.2023.05.002
  • Dogan, M. E., Goru Dogan, T., & Bozkurt, A. (2023). The use of artificial intelligence (AI) in online learning and distance education processes: A systematic review of empirical studies. Applied Sciences, 13(5), 3056. https://doi.org/10.3390/app13053056
  • Duffy, T.M., & Jonassen, D.H. (1992). Constructivism and the technology of instruction: A conversation (1st ed.). Routledge. https://doi.org/10.4324/9780203461976
  • Hong, E., Wan, M., & Peng, Y. (2011). Discrepancies between students' and teachers' perceptions of homework. Journal of Advanced Academics, 22(2), 280–308. https://doi.org/10.1177/1932202X1102200205
  • Hsu, Y. C., & Ching, Y. H. (2023). Generative artificial intelligence in education, part one: The dynamic frontier. TechTrends, 67(4), 603-607. https://doi.org/10.1007/s11528-023-00863-9
  • Kadaruddin, K. (2023). Empowering education through Generative AI: Innovative instructional strategies for tomorrow's learners. International Journal of Business, Law, and Education, 4(2), 618-625. https://doi.org/10.56442/ijble.v4i2.215
  • Khoo, E., Hight, C., Torrens, R. & Cowie, B. (2017). Software Literacy: Education and beyond. In Software Literacy. Springer Briefs in Education (pp. 91-99). Springer. https://doi.org/10.1007/978-981-10-7059-4_6
  • Kılıç Çakmak, E., Taşkın, N., & Kokoç, M., (2017). Öğrenme yaklaşımlarının öğretim teknolojileri alanındaki yeri ve önemi. In H. F. Odabaşı, B. Akkoyunlu, & A. İşman (Ed.), Eğitim Teknolojileri Okumaları 2017 (pp. 451-465). TOJET- The Turkish Online Journal of Educational Technology. http://www.tojet.net/e-book/eto_2017.pdf
  • Koç, A., & Bulut, İ. (2022). Course evaluation scale (CES): Validity and reliability study. Religious Studies, 25(63), 501-528. https://doi.org/10.15745/da.1159706
  • Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
  • Lodge, J. M., Thompson, K., & Corrin, L. (2023). Mapping out a research agenda for generative artificial intelligence in tertiary education. Australasian Journal of Educational Technology, 39(1), 1-8. https://doi.org/10.14742/ajet.8695
  • Macrides, E., Miliou, O., & Angeli, C. (2022). Programming in early childhood education: A systematic review. International Journal of Child-Computer Interaction, 32, 100396. https://doi.org/10.1016/j.ijcci.2021.100396
  • MEB, (2023). Ortaöğretim bilişim teknolojileri ve yazılım dersi: Öğretim programı. Milli Eğitim Bakanlığı. https://mufredat.meb.gov.tr/ProgramDetay.aspx?PID=1663
  • Medeiros, R. P., Ramalho, G. L., & Falcão, T. P. (2019). A systematic literature review on teaching and learning introductory programming in higher education. IEEE Transactions on Education, 62(2), 77–90. https://doi.org/10.1109/TE.2018.2864133
  • Monib, W. K., Qazi, A., & Mahmud, M. M. (2025). Exploring learners’ experiences and perceptions of ChatGPT as a learning tool in higher education. Education and Information Technologies, 30(1), 917-939. https://doi.org/10.1007/s10639-024-13065-4
  • Núñez, J. C., Suárez, N., Rosário, P., Vallejo, G., Cerezo, R., & Valle, A. (2015). Teachers’ feedback on homework, homework-related behaviors, and academic achievement. The Journal of Educational Research, 108(3), 204–216. https://doi.org/10.1080/00220671.2013.878298
  • Obenza, B. N., Salvahan, A., Rios, A. N., Solo, A., Alburo, R. A., & Gabila, R. J. (2024). University students' perception and use of ChatGPT: Generative artificial intelligence (AI) in higher education. International Journal of Human Computing Studies, 5(12), 5-18. https://ssrn.com/abstract=4724968
  • Pavlik, J. V. (2025). Considering the pedagogical benefits of generative artificial intelligence in higher education: applying constructivist learning theory. In Generative AI in Higher Education (pp. 46-58). Edward Elgar Publishing. https://doi.org/10.4337/9781035326020.00014
  • Reichert, F., Zhang, D., Law, N. W., Wong, G. K., & de la Torre, J. (2020). Exploring the structure of digital literacy competence assessed using authentic software applications. Educational Technology Research and Development, 68, 2991-3013. https://doi.org/10.1007/s11423-020-09825-x
  • Rush Hovde, M., & Renguette, C. C. (2017). Technological literacy: A framework for teaching technical communication software tools. Technical Communication Quarterly, 26(4), 395–411. https://doi.org/10.1080/10572252.2017.1385998
  • Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson Publications.
  • Vee, A. (2017). Coding literacy: How computer programming is changing writing. Cambridge, MA: MIT Press.
  • Yilmaz, R., & Yilmaz, F. G. K. (2023). The effect of generative artificial intelligence (AI)-based tool use on students' computational thinking skills, programming self-efficacy and motivation. Computers and Education: Artificial Intelligence, 4, 100147. https://doi.org/10.1016/j.caeai.2023.100147
Toplam 32 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgi Sistemleri Eğitimi, Yapay Zeka (Diğer)
Bölüm Araştırma Makaleleri
Yazarlar

Necati Taşkın 0000-0001-8519-6185

Yayımlanma Tarihi 30 Haziran 2025
Gönderilme Tarihi 5 Mayıs 2025
Kabul Tarihi 21 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 15 Sayı: 1

Kaynak Göster

APA Taşkın, N. (2025). When Class Time Falls Short: An Alternative Path to Application-Based Learning with GenAI. Ordu Üniversitesi Bilim ve Teknoloji Dergisi, 15(1), 128-141. https://doi.org/10.54370/ordubtd.1691860