Abstract
AbstractThis study aimed to explore the experiences, perceptions, knowledge, concerns, and intentions of Generation Z (Gen Z) students with Generation X (Gen X) and Generation Y (Gen Y) teachers regarding the use of generative AI (GenAI) in higher education. A sample of students and teachers were recruited to investigate the above using a survey consisting of both open and closed questions. The findings showed that Gen Z participants were generally optimistic about the potential benefits of GenAI, including enhanced productivity, efficiency, and personalized learning, and expressed intentions to use GenAI for various educational purposes. Gen X and Gen Y teachers acknowledged the potential benefits of GenAI but expressed heightened concerns about overreliance, ethical and pedagogical implications, emphasizing the need for proper guidelines and policies to ensure responsible use of the technology. The study highlighted the importance of combining technology with traditional teaching methods to provide a more effective learning experience. Implications of the findings include the need to develop evidence-based guidelines and policies for GenAI integration, foster critical thinking and digital literacy skills among students, and promote responsible use of GenAI technologies in higher education.
Funder
University Grants Committee
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Education
Reference52 articles.
1. Alam, A. (2022). Employing adaptive learning and intelligent tutoring robots for virtual classrooms and smart campuses: reforming education in the age of artificial intelligence. In Lecture Notes in Electrical Engineering (Vol. 914). https://doi.org/10.1007/978-981-17-5601-6_27
2. Bashri, M., & Rafeeq, A. (2020). Media and information literacy among millennials and generation Z in the Arab world: Filling the gap through a skill-based approach (Policy Report No. 4). Konrad-Adenauer-Stiftung e. V.
3. Bencsik, A., Horváth-Csikós, G., & Juhász, T. (2016). Y and Z generations at workplaces. Journal of Competitiveness, 8(3), 90–106. https://doi.org/10.7441/joc.2016.03.06
4. Bíró, G. I. (2014). Didactics 2.0: A pedagogical analysis of gamification theory from a comparative perspective with a special view to the components of learning. WCLTA, 2013(141), 148–151.
5. Bisdas, S., Topriceanu, C.-C., Zakrzewska, Z., Irimia, A.-V., Shakallis, L., Subhash, J., Casapu, M.-M., Leon-Rojas, J., Pinto dos Santos, D., Andrews, D. M., Zeicu, C., Bouhuwaish, A. M., Lestari, A. N., Abu-Ismail, L., Sadiq, A. S., Khamees, A., Mohammed, K. M. G., Williams, E., Omran, A. I., & Ebrahim, E. H. (2021). Artificial intelligence in medicine: A multinational multi-center survey on the medical and dental students’ perception. Frontiers in Public Health, 9, 795284. https://doi.org/10.3389/fpubh.2021.795284
Cited by
57 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献