Approaches of Generation Z towards AI Integration in Pakistani Classrooms
Keywords:
AI integration, Generation Z, Education, Classroom, PakistanAbstract
This research study delves into how Generation Z views the use of AI in schools, in Pakistan. As this is the generation whose upbringing has been aligned with the era of technological advancements, i.e., 1995-2010, and it is considered as a threshold between the Millennials and the Generation AI. By using Google Forms, the authors conducted a survey with Generation Z, Millennials, and Generation X. The survey focused on three ideas; (a) ethical issues related to AI integration (b) Importance of having clear AI policies and guidelines and (c) ensuring fair access to AI technology in the classrooms. The three ideas also serve as predictor variables for this study. These ideas were analyzed through statistical testing. The results show that Generation Z has concerns about ethics (H1: p <.001), values policies (H2: p <.001), and is aware of disparities in AI access among students at diverse levels (H3: p <.001). These findings highlight the worries that Generation Z has about incorporating AI into classrooms, in Pakistan. This study uses Quantitative Comparative Analysis (QCA) to draw results which have policy implications.
Downloads
References
Ahmad, S. F., Han, H., Alam, M. M., Rehmat, M. K., Irshad, M., Arraño-Muñoz, M., & Ariza-Montes, A. (2023). Impact of artificial intelligence on human loss in decision making, laziness and safety in education. Humanities and Social Sciences Communications, 311 (2023). https://doi.org/10.1057/s41599-023-01787-8
Alamäki, A., & Marttinen, K. (2021). Adopting artificial intelligence for the learning and teaching of generation z in higher education. eSignals Research, 2(1). Retrieved from http://urn.fi/URN:NBN:fi-fe2021101450993
Alwin, D. F. (2002). Generations X, Y and Z: Are they Changing America?:. Contexts, 1(4), 42-51. Retrieved 3 13, 2024, from http://ctx.sagepub.com/content/1/4/42.full.pdf
Bostrom, N., & Yudkowsky, E. (2014). The Cambridge Handbook of Artificial Intelligence: The ethics of artificial intelligence. Retrieved 3 13, 2024, from https://intelligence.org/files/ethicsofai.pdf
Boulay, B. d. (2022). Artificial Intelligence in Education and Ethics. In Handbook of Open, Distance and Digital Education (pp. 1-16). Springer. https://doi.org/10.1007/978-981-19-0351-9_6-1
Chan, C. K. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 38. https://doi.org/10.1186/s41239-023-00408-3
Chan, C. K., & Lee, K. K. (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 Learn. Environ, 60 (2023), 10. https://doi.org/10.1186/s40561-023-00269-3
Ho, M.-T., Mantello, P., Ghotbi, N., Nguyen, M.-H., Nguyen, H.-K. T., & Vuong, Q.-H. (2022). Rethinking technological acceptance in the age of emotional AI: Surveying Gen Z (Zoomer) attitudes toward non-conscious data collection. Technology in Society, 70. https://doi.org/10.1016/j.techsoc.2022.102011
Holmes, W., Persson, J., Chounta, I.-A., Wasson, B., & Dimitrova, V. (2022). ARTIFICIAL INTELLIGENCE AND EDUCATION: A critical view through the lens of human rights, democracy and the rule of law. Council of Europe. Retrieved from https://rm.coe.int/artificial-intelligence-and-education-a-critical-view-through-the-lens/1680a886bd
Jabar, M., Chiong-Javier, E., & Sherer, P. P. (2023). Qualitative ethical technology assessment of artificial intelligence (AI) and the internet of things (IoT) among filipino Gen Z members: implications for ethics education in higher learning institutions. Asia Pacific Journal of Education , 2024. https://doi.org/10.1080/02188791.2024.2303048
Kamalov, F., Calonge, D. S., & Gurrib, I. (2023). New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution. Sustainability, 15(16). https://doi.org/10.3390/su151612451
Low, B., Lavin, D., Du, C. R., & Fang, C. (2023). Risk-Informed and AI-Based Bias Detection on Gender, Race, and Income Using Gen-Z Survey Data. IEEE Xplore, 11, 88317 - 88328. https://doi.org/10.1109/ACCESS.2023.3305636
Mahmood, A., Sarwat, Q., & Gordon, C. (2022). A Systematic Review on Artificial Intelligence in Education (AIE) with a focus on Ethics and Ethical Constraints. Pakistan Journal of Multidisciplinary Research, 3(1). Retrieved from https://pjmr.org/pjmr/article/view/245
Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: guidance for policy-makers. UNESCO. https://doi.org/10.54675/PCSP7350
Omoteso, K. (2012). Review: The application of artificial intelligence in auditing: Looking back to the future. Expert Systems With Applications, 39(9), 8490-8495. Retrieved 3 13, 2024, from https://sciencedirect.com/science/article/pii/s095741741200111x
Stahl, B. C., Schroeder, D., & Rodrigues, R. (2023). Ethics of Artificial Intelligence: Case Studies and Options for Addressing Ethical Challenges. Springer. https://doi.org/10.1007/978-3-031-17040-9
Tongco, M. D. (2007). Purposive Sampling as a Tool for Informant Selection. Ethnobotany Research and Applications, 5, 147-158. Retrieved 3 6, 2024, from https://scholarspace.manoa.hawaii.edu/handle/10125/227
Vance, D. E., Talley, M. H., Azuero, A., Pearce, P. F., & Christian, B. J. (2013). Conducting an article critique for a quantitative research study: perspectives for doctoral students and other novice readers. Retrieved 3 6, 2024, from https://dovepress.com/conducting-an-article-critique-for-a-quantitative-research-study-persp-peer-reviewed-article-nrr
Vitezić, V., & Perić, M. (2021). Artificial intelligence acceptance in services: connecting with Generation Z. 41(13-14), 926-946. https://doi.org/10.1080/02642069.2021.1974406
Yu, H., Shum, C., Alcorn, M., Sun, J., & He, Z. (2022). Robots can’t take my job: antecedents and outcomes of Gen Z employees’ service robot risk awareness. International Journal of Contemporary Hospitality Management, 34(8), 2971-2988. https://doi.org/10.1108/IJCHM-10-2021-1312
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2025 The authors
![Creative Commons License](http://i.creativecommons.org/l/by-nc/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.