Digital technologies and Generation Z: Shaping future education

Al-Adwan, A. S., Li, N., Al-Adwan, A., Abbasi, G. A., Albelbisi, N. A., & Habibi, A. (2023). Extending the technology acceptance model (TAM) to predict university students’ intentions to use metaverse-based learning platforms. Education and Information Technologies, 28(11), 15381-15413. https://doi.org/10.1007/s10639-023-11816-3

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Al-Rahmi, W. M., Alzahrani, A. I., Yahaya, N., Alalwan, N., & Kamin, Y. B. (2020). Digital communication: Information and communication technology (ICT) usage for education sustainability. Sustainability, 12(12), 5052. https://doi.org/10.3390/su12125052

 Bagdi, H., Bulsara, H. P., Sankar, D., & Sharma, L. (2023). The transition from traditional to digital: factors that propel Generation Z’s adoption of online learning. International Journal of Educational Management, 37(3), 695–717. https://doi.org/10.1108/IJEM-01-2023-0003

Benali, M., & Ally, M. (2020). Towards a conceptual framework highlighting mobile learning challenges. International Journal of Mobile and Blended Learning (IJMBL), 12(1), 51-63. https://doi.org/10.4018/IJMBL.2020010104

Bogoviz, A. V. (2019). Industry 4.0 as a New Vector of Growth and Development of Knowledge Economy. Industry 4.0: Industrial Revolution of the 21st Century, 85–91. https://doi.org/10.1007/978-3-319-94310-7_8

Bogoviz, A. V. (2019). Industry 4.0 as a new vector of growth and development of knowledge economy. Industry 4.0: Industrial Revolution of the 21st Century, 85-91. https://doi.org/10.1007/978-3-319-94310-7_8

Bogoviz, A. V., Lobova, S. V., Karp, M. V., Vologdin, E. V., & Alekseev, A. N. (2019). Diversification of educational services in the conditions of industry 4.0 on the basis of AI training. On the Horizon, 27(3/4), 206-212. https://doi.org/10.1108/OTH-06-2019-0031

Brereton, J. S., & Young, K. (2022). Establishing Social Learning in an Engineering MOOC: Benefits for Diversity and Inclusion in Engineering Education. Sustainability, 14, 5472. https://doi.org/10.3390/su14095472

Cao, J., Bhuvaneswari, G., Arumugam, T., & Aravind, B. R. (2023). The digital edge: examining the relationship between digital competency and language learning outcomes. Frontiers in Psychology, 14, 1187909. https://doi.org/10.3389/fpsyg.2023.1187909

Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264-75278. https:// doi.org/10.1109/ACCESS.2020.2988510

Ciolacu, M., Tehrani, A. F., Binder, L., & Svasta, P. M. (2018). Education 4.0-Artificial Intelligence assisted higher education: early recognition system with machine learning to support students’ success. In 2018 IEEE 24th International Symposium for Design and Technology in Electronic Packaging​ (SIITME) (pp. 23-30). https://doi.org/10.1016/j.gltp.2021.01.004

Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1), 1-22. https://doi.org/10.1186/s41239-023-00392-8

Daineko, L. V., Goncharova, N. V., Larionova, V. A., Ovchinnikova, V. A., V Daineko, L., V Goncharova, N., & A Ovchinnikova, V. (2020). Fostering professional competencies of students with the new approaches in higher education. European Proceedings of Social and Behavioural Sciences, 98. https://doi.org/10.15405/epsbs.2020.12.03.24

Dobos, O., Tóth, I. M., Csiszárik-Kocsir, Garai-Fodor, M., & Kremmer, L. (2022). How Generation Z managers think about the agility in a world of digitalization. In 2022 IEEE 20th Jubilee World Symposium on Applied Machine Intelligence and Informatics (SAMI), 000207-000212.

Fisher, M. M., & Baird, D. E. (2021). Humanizing User Experience Design Strategies with NEW Technologies: AR, VR, MR, ZOOM, ALLY and AI to Support Student Engagement and Retention in Higher Education. International Perspectives on the Role of Technology in Humanizing Higher Education Innovations in Higher Education Teaching and Learning, 33, 105–129. https://doi.org/10.1108/S2055364120200000033007

Gentina, E. (2020). Generation Z in Asia: a research agenda. The new Generation Z in Asia: Dynamics, differences, digitalisation, 3-19. https://doi.org/10.1108/978-1-80043-220-820201002

Girish, V. G., Kim, M. Y., Sharma, I., & Lee, C. K. (2022). Examining the structural relationships among e-learning interactivity, uncertainty avoidance, and perceived risks of COVID-19: Applying extended technology acceptance model. International Journal of Human–Computer Interaction, 38(8), 742-752. https://doi.org/10.1080/10447318.2021.1970430

Goldin, T., Rauch, E., Pacher, C., & Woschank, M. (2022). Reference architecture for an integrated and synergetic use of digital tools in education 4.0. Procedia Computer Science, 200, 407-417. https://doi.org/10.1016/j.procs.2022.01.239

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

Hamadneh, N. N., Atawneh, S., Khan, W. A., Almejalli, K. A., & Alhomoud, A. (2022). Using Artificial Intelligence to Predict Students’ Academic Performance in Blended Learning. Sustainability, 14(18), 11642. https://doi.org/10.1016/j.gltp.2021.01.004

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Kelly, S., Kaye, S., White, K. M., & Oviedo-, O. (2024). Clearing the way for participatory data stewardship in artificial intelligence development: a mixed methods approach. Ergonomics, 66(11), 1782–1799. https://doi.org/10.1080/00140139.2023.2289864

Khulwa, C. A., & Luthfia, A. (2023, March). Generation Z Students’ Digital Literacy on Online Learning Readiness. In 2023 11th International Conference on Information and Education Technology (ICIET), 360-364. https://doi.org/10.1109/ICIET56899.2023.10111186

McKenzie, S., Coldwell-Neilson, J., & Palmer, S. (2018). Understanding the career development and employability of information technology students. Journal of Applied Research in Higher Education, 10(4), 456-468. https://doi.org/10.1108/JARHE-03-2018-0033

Nabwire, S., Suh, H. K., Kim, M. S., Baek, I., & Cho, B. K. (2021). Application of artificial intelligence in phenomics. Sensors, 21(13), 4363. https://doi.org/10.3390/s21134363

Nathoo, A., Bekaroo, G., Gangabissoon, T., & Santokhee, A. (2020). Using tangible user interfaces for teaching concepts of internet of things Usability and learning effectiveness. Interactive Technology and Smart Education, 17(2), 133–158. https://doi.org/10.1108/ITSE-09-2019-0061

Owoc, M. L., Sawicka, A., & Weichbroth, P. (2021). Artificial intelligence technologies in education: benefits, challenges and strategies of implementation. In IFIP International Workshop on Artificial Intelligence for Knowledge Management, 37-58. https://doi.org/10.1007/978-3-030-85001-2_4

Peng, H. T., Siddiqui, M. M., Rhind, S. G., Zhang, J., da Luz, L. T., & Beckett, A. (2023). Artificial intelligence and machine learning for hemorrhagic trauma care. Military Medical Research, 10(1), 6. https://doi.org/10.1186/s40779-023-00444-0

Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12(1), 1-13. https://doi.org/10.1186/s41039-017-0062-8

Radianti, J., Majchrzak, T. A., Fromm, J., & Wohlgenant, I. (2020). A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778

Roumate, F. (2023). Ethics of Artificial Intelligence, Higher Education, and Scientific Research. In Artificial Intelligence in Higher Education and Scientific Research: Future Development, 129-144. https://doi.org/10.1007/978-981-19-8641-3_10

Sanjeev, M.A., Khademizadeh, S., Arumugam, T., Tripathi, & D.K. (2022). Generation Z and intention to use the digital library: does personality matter? The Electronic Library, 40 (1/2), 18-37. https://doi.org/10.1108/EL-04-2021-0082

Santoveña-Casal, S., & López, S. R. (2023). Mapping of digital pedagogies in higher education. Education and Information Technologies, 1–22. https://doi.org/10.1007/s10639-023-11888-1

Seemiller, C., & Grace, M. (2017). Generation Z: Educating and Engaging the Next Generation of Students. About Campus: Enriching the Student Learning Experience, 22(3), 21–26. https://doi.org/10.1002/abc.21293

Shahzad, A., Hassan, R., Aremu, A. Y., Hussain, A., & Lodhi, R. N. (2021). Effects of COVID-19 in E-learning on higher education institution students: the group comparison between male and female. Quality & quantity, 55, 805-826. https://doi.org/10.1007/s11135-020-01028-z

Sharma, N., Sharma, R., & Jindal, N. (2021). Machine learning and deep learning applications-a vision. Global Transitions Proceedings, 2(1), 24-28. https://doi.org/10.1016/j.gltp.2021.01.004

Singh, H. (2021). Building effective blended learning programs. Challenges and opportunities for the global implementation of e-learning frameworks, 15-23. https://doi.org/10.4018/978-1-7998-7607-6.ch002

Yenugu, S. (2022). The new National Education Policy (NEP) of India: will it be a paradigm shift in Indian higher education? Perspectives: Policy and Practice in Higher Education. https://doi.org/10.1080/13603108.2022.2078901

Zulkifli, Z., Satria, E., Supriyadi, A., & Santosa, T. A. (2022). Meta-analysis: The effectiveness of the integrated STEM technology pedagogical content knowledge learning model on the 21st century skills of high school students in the science department. Psychology, Evaluation, and Technology in Educational Research, 5(1), 32-42. https://doi.org/10.18502/kss.v3i11.4031

Díaz-Noguera, M. D., Hervás-Gómez, C., De la Calle-Cabrera, A. M., & López-Meneses, E. (2022). Autonomy, motivation, and digital pedagogy are key factors in the perceptions of Spanish higher-education students toward online learning during the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 19(2), 654. https://doi.org/10.3390/ ijerph19020654

Costa, E. A., Rebello, C. M., Schnitman, L., Loureiro, J. M., Ribeiro, A. M., & Nogueira, I. B. (2024). Adaptive digital twin for pressure swing adsorption systems: Integrating a novel feedback tracking system, online learning and uncertainty assessment for enhanced performance. Engineering Applications of Artificial Intelligence, 127, 107364. https://doi.org/10.1016/j.engappai.2023.107364

Gupta, A., Mazumdar, B. D., Mishra, M., Shinde, P. P., Srivastava, S., & Deepak, A. (2023). Role of cloud computing in management and education. Materials Today: Proceedings, 80, 3726-3729. https://doi.org/10.1016/j.matpr.2021.07.370

Wang, K., Li, B., Tian, T., Zakuan, N., & Rani, P. (2023). Evaluate the drivers for digital transformation in higher education institutions in the era of industry 4.0 based on decision-making method. Journal of Innovation & Knowledge, 8(3), 100364. https://doi.org/10.1016/j.jik.2023.100364

Rouse, W. B. (2020). AI as systems engineering augmented intelligence for systems engineers. Insight, 23(1), 52-54. https://doi.org/10.3390/ ijerph19020654

Chen, X., Xie, H., Zou, D., & Hwang, G. J. (2020). Application and theory gaps during the rise of artificial intelligence in education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002

1. Anil Khurana, Department of Management Studies, Deenbandhu Chhotu Ram University of Science and Technology, Murthal (Haryana), India.
   
   anilkhurana.dcrust@gmail.com
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2. Neha Girdhar, Department of Management Studies, Deenbandhu Chhotu Ram University of Science and Technology, Murthal (Haryana), India.
   
   nehagirdhar121@gmail.com
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