Abstrakt
The main objective of the present paper is to capture the developments and trends in research on the education of a generational cohort of digital natives using Artificial Intelligence (AI). The starting point of the study is the application of a scientific mapping approach in the research part of the paper. The first phase of the investigation consists of collecting data, i.e., scientific publications from the Web of Science database, and sorting them according to the PRISMA 2020 development scheme. The second phase focuses on the analysis and visualization of the obtained metadata on scientific publications using the VOSviewer software. The obtained records are analyzed based on bibliometric characteristics, namely the co-occurrence of words in abstracts, titles, and author keywords, related to the education of the selected generational cohort. By identifying research trends on the education of Generation Z through artificial intelligence, the study has the potential to stimulate further research on the topic or to highlight specific research directions or under-researched areas within this field.
Bibliografia
Aldosari Share Aiyed M. 2020. The future of higher education in the light of artificial intelligence transformations. International Journal of Higher Education no. 9(3). 145–151. https://doi.org/10.5430/ijhe.v9n3p145.
Zobacz w Google Scholar
Alonso-Rodríguez Ana María. 2024. Towards an ethical framework for artificial intelligence in education. Teoría de la Educación no. 36(2). 79–98. https://doi.org/10.14201/teri.31821.
Zobacz w Google Scholar
Annuš Norbert. 2024. Education in the Age of Artificial Intelligence. TEM Journal nr 13(1). 404–413. https://doi.org/10.18421/TEM131-42.
Zobacz w Google Scholar
Arkhipova Maria V., Belova Elena E., Gavrikova Yuliya A., Pleskanyuk Tatiana N., Arkhipov Anatoly N. 2019. Reaching generation Z: attitude toward technology among the newest generation of school students. W: Perspectives on the Use of New Information and Communication Technology (ICT) in the Modern Economy. Elena G. Popkova, Victoria N. Ostrovskaya (eds.). Cham. 1026–1032. https://doi.org/10.1007/978-3-319-90835-9_114.
Zobacz w Google Scholar
Cabero-Almenara Julio, Martínez-Pérez Silvia, Gutiérrez-Castillo Juan Jesús, Palacios-Rodríguez Antonio. 2022. University students’ perceptions of the use of technologies in educational activities and mental effort invested. RIED. Revista Iberoamericana de Educación a Distancia no. 25(2). 305–326. https://doi.org/10.5944/ried.25.2.32714.
Zobacz w Google Scholar
Chan Cecilia K. Y., Lee Katherine K. W. 2023. The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and millennial generation teachers? Smart Learning Environments no. 10. 60. https://doi.org/10.1186/s40561-023-00269-3.
Zobacz w Google Scholar
Chaudhry Mohammad A., Kazim Ehsan. 2021. Artificial intelligence in education (AIEd): A high-level academic and industry note. In: AI Ethics 2. Jack MacIntyre, Larry Medsker (red.). Cham. 157–165. https://doi.org/10.1007/s43681-021-00074-z.
Zobacz w Google Scholar
Donthu Naveen, Kumar Satish, Mukherjee Debmalya, Pandey Nitesh, Lim Weng Marc. 2021. How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research no. 133. 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070.
Zobacz w Google Scholar
Dunlosky John, Badali Sarah, Rivers Marissa L., Rawson Katherine A. 2020. The role of effort in understanding educational achievement: objective effort as an explanatory construct versus effort as a student perception. Educational Psychology Review no. 32. 1163–1175. https://doi.org/10.1007/s10648-020-09577-3.
Zobacz w Google Scholar
EIM Editorial Team. 2024. How to Gen Z: Adapting Teaching Methods for the Learning Style of Digital Natives. https://eimpartnerships.com/articles/gen-z-learning-style-how-to-adapt-teaching-methods-for-digital-natives.
Zobacz w Google Scholar
Hail Ghilan Al-Madhagy Taufiq, Yusof Shafiz Affendi Mohd, Rashid Ammar, El-Shekeil Ibrahim, Lutfi Abdalwali. 2024. Exploring factors influencing Gen Z’s acceptance and adoption of AI and cloud-based applications and tools in academic attainment. Emerging Science Journal no. 8(3). 815–836. https://doi.org/10.28991/ESJ-2024-08-03-02.
Zobacz w Google Scholar
Karasová Eva, Uherková Marianna. 2023. Navigating the digital age: Exploring effective teaching and learning approaches for university students. In: Marketing Identity: AI – The Future of Today. Monika Prostináková Hossová, Miroslav Martovič, Michal Solík (eds.). Trnava. 184–193. https://doi.org/10.34135/mmidentity-2023-19.
Zobacz w Google Scholar
Miliou Ourania, Angeli Charoula. 2021. Measuring the internet skills of Gen Z students in higher education: Validation of the internet skills scale in university settings. In: 7th International Conference on Higher Education Advances (HEAd’21). Jorge Domenech, Patricia Merello, Elena de la Poza (eds.). València. 1359–1368. https://gdocu.upv.es/alfresco/service/api/node/content/workspace/SpacesStore/00e81572-7166-4cd2-976f-a6b293238aac/6657.pdf?guest=true.
Zobacz w Google Scholar
Nichols Thomas, Wright Meghan C. 2018. Generational differences: Understanding and exploring generation Z. In: Proceedings 2018. Brian W. Kulik (ed.). 198–206. https://swaom.org/wp-content/uploads/2022/02/proceedings-2018-4.pdf.
Zobacz w Google Scholar
Ondrišová Monika. 2011. Bibliometria. Bratysława. Stimul. https://fphil.uniba.sk/fileadmin/fif/katedry_pracoviska/kkiv/Granty_a_projekty/Inwent/bibliometria_ondrisova.pdf.
Zobacz w Google Scholar
OpenAI. 2022. Introducing ChatGPT. https://openai.com/index/chatgpt/.
Zobacz w Google Scholar
Öztürk Oğuzhan, Kocaman Rıdvan, Kanbach Dominik K. 2024. How to design bibliometric research: An overview and a framework proposal. Review of Managerial Science no. 18. 3333-3361. https://doi.org/10.1007/s11846-024-00738-0.
Zobacz w Google Scholar
Pedró Francesc, Subosa Miguel, Rivas Axel, Valverde Paula. 2019. Artificial intelligence in education: challenges and opportunities for sustainable development. Paris. UNESCO.
Zobacz w Google Scholar
Perez-Alvarez Rosa, Villalobos Chávez Carlos Roberto, Cruz Delgado María de los Ángeles, Loría Menéndez José Manuel. 2024. Expectations of higher education teachers regarding the use of AI in education. In: Artificial Intelligence in Education. Anthony M. Olney, Irene-Angelica Chounta, Zhihong Liu, Olga C. Santos, Ig Ibert Bittencourt (eds.). Cham. 208–213. https://doi.org/10.1007/978-3-031-64315-6_16.
Zobacz w Google Scholar
Persada Satria Fadil, Miraja Bobby Ardiansyah, Nadlifatin Reny. 2019. Understanding the generation Z behavior on D-Learning: A Unified Theory of Acceptance and Use of Technology (UTAUT) approach. International Journal of Emerging Technologies in Learning no. 14(5). 20–33. https://doi.org/10.3991/ijet.v14i05.9993.
Zobacz w Google Scholar
Petrovich Eugenio. 2021. Science Mapping and Science Maps. Knowledge Organization no. 48(7–8). 535–562. https://doi.org/10.5771/0943-7444-2021-7-8-535.
Zobacz w Google Scholar
PRISMA. 2020. PRISMA 2020 Flow Diagram. https://www.prisma-statement.org/prisma-2020-flow-diagram.
Zobacz w Google Scholar
Rahiman Habeeb Ur, Kodikal Rashmi. 2023. Revolutionizing education: Artificial intelligence empowered learning in higher education. Cogent Education no. 11(1). 2293431. https://doi.org/10.1080/2331186X.2023.2293431.
Zobacz w Google Scholar
Ryzheva Natalia, Nefodov Dmitry, Romanyuk Svitlana, Marynchenko Hanna, Kudla Maryna. 2024. Artificial Intelligence in higher education: opportunities and challenges. Amazonia Investiga no. 13(73). 284–296. https://doi.org/10.34069/AI/2024.73.01.24.
Zobacz w Google Scholar
Seemiller Corey, Grace Meghan. 2017. Generation Z: Educating and engaging the next generation of students. About Campus no. 22(3). 22–23. https://doi.org/10.1002/abc.21293.
Zobacz w Google Scholar
Tick Andrea. 2018. Research on the digital learning and E-learning behaviour and habits of the early Z generation. In: 22nd International Conference on Intelligent Engineering Systems. Las Palmas de Gran Canaria. 33–38. https://doi.org/10.1109/INES.2018.8523906.
Zobacz w Google Scholar
van Eck Nees Jan, Waltman Ludo. 2014. Visualizing bibliometric networks. In: Measuring scholarly impact: Methods and practice. Ying Ding, Ronald Rousseau, Dietmar Wolfram (eds.). Cham. 285–320. https://doi.org/10.1007/978-3-319-10377-8_13.
Zobacz w Google Scholar
Williams Robert T. 2024. The ethical implications of using generative chatbots in higher education. Frontiers in Education no. 8. art. 1331607. https://doi.org/10.3389/feduc.2023.1331607.
Zobacz w Google Scholar
Zábojník Roman, Hromada Vladimír. 2024. The role of generative AI in empowering generation Z in higher education. In: Marketing Identity: Human vs. Artificial. Monika Prostináková Hossová, Michal Solík, Miroslav Martovič (eds.). Trnava. 758–776. https://doi.org/10.34135/mmidentity-2024-75.
Zobacz w Google Scholar
Zawacki-Richter Olaf, Marín Victoria I., Bond Melissa, Gouverneur Franziska. 2019. Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education no. 16. art. 39. https://doi.org/10.1186/s41239-019-0171-0.
Zobacz w Google Scholar

Utwór dostępny jest na licencji Creative Commons Uznanie autorstwa – Użycie niekomercyjne 4.0 Międzynarodowe.
Prawa autorskie (c) 2026 Annales Universitatis Paedagogicae Cracoviensis | Studia de Cultura
