Expectations for the Use of Generative Artificial Intelligence in Higher Education: A Research on the Perceptions of Tourism Faculty Students

Yıl 2024, Cilt: 5 Sayı: 1, 78 - 97, 05.07.2024

Güzide Zeynep Egeli Hülya Kurgun Erdem Aktaş Avşar Kurgun

https://doi.org/10.62001/gsijses.1480930

Öz

Rapid transformation and shaping of the education sector by evolving technologies are inevitable. The study aims to explore the transformative potential of generative artificial intelligence (GenAI) within higher education, particularly in the tourism sector, and investigate students' perspectives on its usage. Existing research on this topic is limited, prompting a qualitative research approach in this study to obtain more in-depth findings. This involved conducting focus group discussions with nine first-year tourism management students who had attended four training seminars on digital transformation and artificial intelligence applications and possessed basic knowledge of the subject. The outcomes of these discussions, covering students' views on the impact of GenAI on academic performance, critical thinking and research skills, its contribution to post-graduation capabilities, potential misuse scenarios, and likely challenges, were subjected to content analysis. Among the primary research findings was that students are aware of security and ethics issues related to generative AI but are not concerned due to the availability of solutions. They perceive GenAI as an opportunity to enhance their learning experiences, academic performances, and future employability, but emphasize the necessity of using it as an auxiliary tool rather than relying entirely on these applications. Additionally, rather than immediately implementing these applications across all higher education institutions and departments, there is an emphasis on the necessity of transitional phase plans. Consequently, the study aimed to propose recommendations to higher education institutions, educators, and students based on both literature and practical insights to develop a framework aimed at a generative AI-centric approach. Moreover, valuable insights were sought to enhance the educational experience of future tourism professionals.

Anahtar Kelimeler

Generative artificial intelligence, higher education, digital transformation, education quality, focus group

Yaratıcı Yapay Zekanın Yükseköğretimde Kullanımına İlişkin Beklentiler: Turizm Fakültesi Öğrencilerinin Algıları Üzerine Bir Araştırma

Öz

Gelişen teknolojiler ile eğitim sektörünün hızla dönüşmesi ve şekillenmesi kaçınılmazdır. Bu araştırmada yaratıcı yapay zekanın turizm alanı başta olmak üzere yükseköğretimde dönüştürücü potansiyelinin incelenmesi ve kullanımına ilişkin öğrencilerin bakış açılarının ortaya konması amaçlanmıştır. Alanyazında konuya ilişkin araştırmalar sınırlı olup, bu çalışmada nitel araştırma yöntemi ile daha derinlemesine bulgular elde edilmesi hedeflenmiştir. Bu kapsamda dijital dönüşüm ve yapay zeka uygulamaları hakkında dört eğitim seminerine katılmış, konuyla ilgili temel bilgiye sahip 1. sınıf turizm işletmeciliği bölümünde öğrenim gören dokuz öğrenci ile odak grup görüşmeleri gerçekleştirilmiştir. Odak grup görüşmeleri sonucunda öğrencilerin yaratıcı yapay zekanın akademik performanslarına, eleştirel düşünme ve araştırma becerileri, etkisi, mezuniyet sonrası yeteneklerine katkısı, hatalı kullanım senaryoları ve muhtemel zorluklar ile ilgili görüşleri içerik analizine tabi tutulmuştur. Temel araştırma bulguları arasında öğrencilerin güvenlik ve etikle ilgili farkındalık sahibi olduğu ancak çözüm yolları olduğu için endişe duymadıkları belirlenmiştir. GenAI’nin öğrenim deneyimlerini, akademik performanslarını ve gelecekte işe alım ve performanslarını geliştirmek için çeşitli açılardan bir fırsat olarak görmekte, ancak onları bir yardımcı araç olarak kullanılması gerekliliğini vurgulamışlardır. Söz konusu uygulamaların etkin bir geçiş dönemi planı ile gerçekleştirilmesi hususunu işaret etmişlerdir. Sonuç olarak araştırma kapsamında yükseköğretimde eğitim kalitesinin geliştirilmesi için alanyazına ve uygulamaya yönelik yükseköğretim kurumlarına, eğiticilere ve öğrencilere yaratıcı yapay zekâ merkezli bir çerçeve sunulmuştur. Aynı zamanda gelecekteki turizm profesyonellerinin eğitim deneyimini geliştirmek için değerli iç görüler elde edilmiştir.

Anahtar Kelimeler

Yaratıcı yapay zeka, yükseköğretim kurumu, dijital dönüşüm, eğitim kalitesi, odak grup

Kaynakça

• Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), 429. https://doi.org/10.30935/cedtech/13152.
• Brownlee, J. (2019). A gentle introduction to the Progressive Growing GAN. Machine Learning Mastery. https://machinelearningmastery.com/introduction-to-progressive-growing-generative-adversarial-networks/
• Chan, C., Y. K. & Hu, W. (2023). Students' voices on generative AI: Perceptions, benefits, and Cchallenges in higher education. Computer Science, https://doi.org/10.48550/arXiv.2305.00290
• Chang, C.H. & Kidman, G. (2023). The rise of generative artificial intelligence (AI) language models-challenges and opportunities for geographical and environmental education. International Research in Geographical and Environmental Education, 32(2), 85-89. https://doi.org/10.1080/10382046.2023.2194036.
• Chaudhry, M. A., & Kazim, E. (2022). Artificial Intelligence in education (AIEd): A high-level academic and industry note 2021. AI and Ethics, 2, 157–165. https://doi.org/10.1007/s43681-021-00074-z.
• Chen, C.H., Koong, C.S., & Liao, C. (2022). Influences of integrating dynamic assessment into a speech recognition learning design to support students’ English-speaking skills, learning anxiety and cognitive load. Educational Technology & Society, 25(1), 1-14.
• Chen, X. & Ibrahim, Z. (2023). A comprehensive study of emotional responses in AI-enhanced interactive installation art. Sustainability, 15(22), 15830. https://doi.org/10.3390/su152215830.
• Chiu, T.K.F. (2024). A classification tool to foster self-regulated learning with generative artificial intelligence by applying self- determination theory: a case of ChatGPT. Educational Technology Research and Development. https://doi.org/10.1007/s11423-024-10366-w
• Codiste (2024). What is Generative AI? [Key Concept & GenAI Apps]. https://www.linkedin.com/pulse/what-generative-ai-key-concept-genai- apps-codiste-20crf/
• Çetin, M., & Aktaş, A. (2021). Yapay zeka ve eğitimde gelecek senaryoları. OPUS International Journal of Society Researches, 18(Eğitim Bilimleri Özel Sayısı), 4225-4268. https://doi.org/10.26466/opus.911444
• Denny, P., Khosravi, H., Hellas, A., Leinonen, J., & Sarsa, S. (2023). Can we trust AI-generated educational content? Comparative analysis of human and AI-generated learning resources. arXiv:2306.10509. https://hassan-khosravi.net/publications/denny2023a.pdf.
• Durall, E. & Kapros, E. (2020). Co-design for a competency self-assessment chatbot and survey in science education. In P. Zaphiris & A. Ioannou (Eds.), International Conference on Human-Computer Interaction (pp. 13-24). Springer. https://doi.org/10.1007/978-3-030-50506-6_2.
• Ersin, P. & Bayyurt Kerestecioğlu, Y. (2017). Odak grup görüşmeleri. In Nitel Araştırma (pp.202-219), Anı Yayınevi, Ankara.
• Google DeepMind (2024). Wavenet. https://deepmind.google/technologies/wavenet/
• Iqbal, H.M., Parra-Saldivar, R., Zavala-Yoe, R., & Ramirez-Mendoza, R.A. (2020). Smart educational tools and learning management systems: supportive framework. International Journal on Interactive Design and Manufacturing (IJIDeM), 14(4), 1179-1193. https://doi.org/10.1007/s12008-020-00695-4.
• Jaiswal, A. & Arun, C.J. (2021). Potential of artificial intelligence for transformation of the education system in India. International Journal of Education and Development Using Information and Communication Technology, 17(1), 142-158.
• Jhamtani, H. (2022). ProGAN Explained_ Progressive Growing Generative Adversarial Networks. https://www.linkedin.com/pulse/progan- explained-progressive-growing-generative-hitesh-jhamtani/
• Jia, J., Zhang, D. & Gao, F. (2021). Learning analytics and artificial intelligence in mathematics education: A systematic review. International Journal of Educational Research, 107, 101831.
• Kakani, V., Nguyen, V. H., Kumar, B. P., Kim, H., & Pasupuleti, V. R. (2020). A critical review on computer vision and artificial intelligence in food industry. Journal of Agriculture and Food Research, 2, 100033. https://doi.org/10.1016/j.jafr.2020.100033.
• Kaplan-Rakowski, R., Grotewold, K., Hartwick, P., & Papin, K. (2023). Generative AI and Teachers’ Perspectives on Its Implementation in Education. Journal of Interactive Learning Research, 34(2), 313-338.
• Kelly, A., Sullivan, M., & Strampel, K. (2023). Generative artificial intelligence: University student awareness, experience, and confidence in use across disciplines. Journal of University Teaching & Learning Practice, 20(6), 12. https://doi.org/10.53761/1.20.6.12
• Kim, J. (2015). Learnersourcing: Improving learning with collective learner activity (Unpublished PhD Thesis). Massachusetts Institute of Technology.
• Kizilcec, R. F. & Lee, H. (2022). Algorithmic fairness in education. In W. Holmes & K. Porayska-Pomsta (Eds.), The Ethics of Artificial Intelligence in Education (pp. 1-29). Routledge.
• Krüger, D. (2023). Generative AI (GenAI): The evolution of creativity through technology. https://www.valantic.com/en/blog/generative-ai- genai/
• Krueger, R.A. (1994). Focus Groups: A Practical Guide For Applied Research. London: SAGE. Krueger, R.A. and Casey, M.A. (2000) Focus groups: A practical guide for applied research. Sage Publications Inc, Thousand Oaks.
• Law, L. (2024). Application of generative artificial intelligence (GenAI) in language teaching and learning: A scoping literature review. Computers and Education Open, 6, 100174. https://doi.org/10.1016/j.caeo.2024.100174
• Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., & Darwis, A. (2023). Exploring artifcial intelligence in academic essay: Higher education student’s perspective. International Journal of Educational Research Open, 5, 100296. https://doi.org/10.1016/j.ijedro.2023.100296
• Marescotti, D., Narayanamoorthy, C., Bonjour, F., Kuwae, K., Graber, L., Calvino-Martin, F., Ghosh, S. & Hoeng, J. (2022). AI-driven laboratory workflows enable operation in the age of social distancing. SLAS Technology, 27(3), 195-203. https://doi.org/10.1016/j.slast.2021.12.001.
• Marr, B. (2023). A simple guide to the history of Generative AI. https://bernardmarr.com/a-simple-guide-to-the-history-of-generative-ai/
• Molina, F., Molina, M. D., & Molina, C. (2022). Motivating learning through digital apps: The importance of relatedness satisfaction. International Journal of Human-Computer Interaction. https:// doi.org/10.1080/10447318.2022.2097777
• Open AI ( 2022). Introducing ChatGPT. https://openai.com/blog/chatgpt
• Rasul, T., Nair, S., Kalendra, D., Robin, M., Santini, F., O., Ladeira, W., J., Sun, M., Day, I., Rather, R., A. ve Heathcote, L. (2023). The role of ChatGPT in higher education: Benefits, challenges, and future research directions, Journal of Applied Learning & Teaching, 6 (1), 1-16, https:// doi.org/ 10. 370 74/ jalt.2023.6.1.29
• Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154.
• Rodrigues, R. (2020). Legal and human rights issues of AI: Gaps, challenges and vulnerabilities. Journal of Responsible Technology, 4, 100005. https://doi.org/10.1016/j.jrt.2020.100005
• Roman, D. (2023). The history of Generative AI (GenAI). https://wearebrain.com/blog/the-history-of-generative-ai-genai
• Rudolph, J., Tan, S., ve Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?, Journal of Applied Learning & Teaching, 6(1), 342-363, https://doi.org/10.37074/jalt.2023.6.1.9
• Ruiz-Rojas, L. I., Acosta-Vargas, P., De-Moreta-Llovet, J., & Gonzalez-Rodriguez, M. (2023). Empowering Education with Generative Artificial Intelligence Tools: Approach with an Instructional Design Matrix. Sustainability, 15(15), 11524. https://doi.org/10.3390/su151511524
• Schroeder, K. T., Hubertz, M., Van Campenhout, R., & Johnson, B. G. (2022). Teaching and learning with AI-generated courseware: Lessons from the classroom. Online Learning, 26(3), 73-87.
• Schulze, J. (2024). What Is GPT? GPT-3, GPT-4, and More Explained. https://www.coursera.org/articles/what-is-gpt?
• Shah, S.M.H. (2024). What is Generative AI (GenAI)? Definition, Tools and more... https://www.linkedin.com/pulse/what-generative-ai-genai- definition-tools-more-shah-w02te/
• Shakhadri, S.A.G. (2021). Progressive Growing GAN- ProGAN. https://www.analyticsvidhya.com/blog/2021/05/progressive-growing-gan-progan/
• Staff, C. (2024). What Is Generative AI? Definition, Applications, and Impact. https://www.coursera.org/articles/what-is-generative-ai? isNewUser=true Țală, M. L., Müller, C. N., Năstase, I. A., & Gheorghe, G. (2024). Exploring university students' perceptions of generative artificial intelligence in education. Amfiteatru Economic Journal, 26(65), 71-88.
• Toloka Team (2023). History of generative AI. https://toloka.ai/blog/history-of-generative-ai/
• UNESCO. (2019). Artificial intelligence in education: Opportunities, challenges and risks. UNESCO Educational, Scientific and Cultural Organization. Paris, France.
• University of Michigan (2024). About Generative Artificial Intelligence. https://genai.umich.edu/about-generative-ai
• Yıldırım, A. & Şimşek, H. (2016) Sosyal Bilimlerde Nitel Araştırma Yöntemleri (10. Baskı). Seçkin Yayınevi: Ankara
• Yilmaz, R., & Yilmaz, F. G. K. (2023). The efect of generative artifcial intelligence (AI)-based-tool use on students’ computational thinking skills, programming self-efcacy and motivation. Computers and Education: Artifcial Intelligence, 4, Article 100147. https://doi.org/10.1016/j.caeai.2023.100147
• Yusuf, A., Pervin, N. & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21 (21). https://doi.org/10.1186/s41239-024-00453-6