Keywords
higher education
Canadian
learners' experiences
How to Cite
Abstract
The integration of artificial intelligence (AI) in higher education (HE) presents both opportunities and challenges to teaching and learning efforts. This pilot study investigates the experiences of HE learners toward generative AI (genAI) at a Canadian polytechnic, focusing on early childhood education (n = 66) and nursing (n = 112) students. Employing a survey methodology, the study utilized an adapted version of the San Diego State University Student AI Survey (Goldberg et al., 2024a). Results revealed limited AI engagement, with low confidence in using genAI and a lack of awareness related to AI developments. Significant differences emerged across several of the survey subscales, with effect sizes ranging from small to large. Overall, findings highlight substantial gaps in AI literacy and understanding of its ethical use, underscoring the need for targeted education, curriculum integration, and institutional guidelines to support learners in informed and responsible AI use.
References
Akgun, S., & Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 Settings. AI and Ethics, 2, 431–440. https://doi.org/10.1007/s43681-021-00096-7
Al-haimi, B., Hujainah, F., Nasir, D., & Alhroob, E. (2021). Higher education institutions with artificial intelligence: Roles, promises, and requirements. In A. Hamdan, A.E. Hassanien, R. Khamis, B. Alareeni, A. Rassazue, B. Awwad, B. (Eds.). Applications of Artificial Intelligence in Business, Education, and Healthcare, (pp. 221–238), Springer, Cham. https://doi.org/10.1007/978-3-030-72080-3_13
Alshamy, A., Al-Harthi, A., & Abdullah, S. (2025). Perceptions of generative AI tools in higher education: Insights from students and academics at Sultan Qaboos University. Education Sciences, 15(4), 501. https://doi.org/10.3390/educsci15040501
Bauer, E., Grieff, S., Graesser, A., Scheiter, K., & Sailer, M. (2025). Looking beyond the hype: Understanding the effects of AI on learning. Educational Psychology Review, 37(45), 1–27. https://doi.org/10.1007/s10648-025-10020-8
Biagini, G. (2025). Towards an AI-literature future: A systematic literature review exploring education, ethics, and applications. International Journal of Artificial Intelligence in Education, 35, 2616–2666. https://doi.org/10.1007/s40593-025-00466-w
Brynjolfsson, E. & McAfee, A. (2017, July 18). The business of artificial intelligence. Harvard Business Review. https://hbr.org/2017/07/the-business-of-artificial-intelligence
Brodheim, T. (2025, May 12). Shaping the future of learning: AI in higher education. EDUCAUSE REVIEW. https://er.educause.edu/articles/sponsored/2025/5/shaping-the-future-of-learning-ai-in-higher-education
Carmi, G. (2025). Learning with generative AI: An empirical study of students in higher education. Educ. Sci., 15(12), 1696. https://doi.org/10.3390/educsci15121696
Cavazos, J., Hauck, K., & Bain, C. (2025). ChatGPT goes to college: Exploring student perspectives on artificial intelligence in the classroom. Society for the Teaching of Psychology, 52(3), 357–368. https://doi.org/10.1177/00986283241268829
Chan, K. (2023, June 10). Is AI changing the rules of academic misconduct? An in-depth look at students’ perceptions of ‘AI-giarism’. Computer Science. Computers and Society, Ithaca Cornell University. http://arxiv.org/abs/2306.03358
Chiu, T., Moorhouse, B., Chai, C., & Ismailov, M. (2023). Teacher support and student motivation to learn with artificial intelligence (AI) based chatbot. Interactive Learning Environments, 32(7), 3240–3256. https://doi.org/10.1080/10494820.2023.2172044
Cohen, J. (2002). Statistical power analysis for the behavioural sciences (3rd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates.
Crain, C., Ewing, A., Billy, I., & Anush, H. (2024). The advantages and disadvantages of AI in higher education. The Business and Management Review, 15(3), 168–178. https://doi.org/10.24052/BMR/V15NU03/ART-16
Floridi, L. & Cowls, J. (2019). A unified framework of five principles for AI society. Harvard Data Science Review, 1(1), 2–15. https://doi.org/10.1162/99608f92.8cd550d1
Goldberg, D., Frazee, J., Hauze, S., Knobel, C., Sheehan, J., & Sobo, E. (2024a, February 29). San Diego State University artificial intelligence survey instrument. The California State University ScholarWorks. https://scholarworks.calstate.edu/concern/publications/qj72pf459
Goldberg, D., Sobo, E., Frazee, J. & Hauze, S. (2024b). Generative AI in higher education: Insights from a campus-wide student survey at a large public university. In J. Cohen & G. Solano (Eds.), Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 757–766). Las Vegas, Nevada, United States: Association for the Advancement of Computing in Education (AACE). https://www.learntechlib.org/primary/p/224037/
Guillén-Yparrea, N. & Hernández-Rodríguez, F. (2024). Unveiling generative AI in higher education: Insights from engineering students and professors. IEEE Global Engineering Education Conference (EDUCON), 1–5. https://doi.org/10.1109/EDUCON60312.2024.10578876
Hashish, E., Alsayed S., & Razek, N. (2025). Embracing Ai in academica: A mixed methods study of nursing students’ and educators’ perspectives on using ChatGPT. PLOS ONE, 20(7): e0327981. https://doi.org/10.1371/journal.pone.0327981
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., & Shum, S. B. (2022). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education, 32, 5040526. https://doi.org/10.1007/s40593-021-00239-1
Holmes, W. & Tuomi, I. (2022). State of the art and practice in AI in education. European Journal of Education, 57(4), 542–570. https://doi.org/10.1111/ejed.12533
Hu, S., Fengfeng, K., Vyortkina, D., Hu, P., Luby, S., O’Shea, J. (2024). Artificial intelligence in higher education: Applications, challenges, and policy development and further considerations. In L.W., Perna (Ed.). Higher Education: Handbook of Theory and Research, (pp. 1–52). https://doi.org/10.1007/978-3-031-51930-7_13-1
Humber and Guelph-Humber Libraries. (nd). Algorithms and you. Humber Libraries. https://library.humber.ca/tutorials/ai-algorithms-you
Jayawardena, C., Gunathilake, Y., & Ihalagedara, D. (2025). Dental students’ learning experience: Artificial intelligence vs human feedback on assignments. International Dental Journal, 10(75), 100–108. https://doi.org/10.1016/j.identj.2024.12.022
Luckin, R., Cukurova, M., Kent, C., & du Boulay, B. (2022). Empowering educators to be AI-ready. Computers and Education: Artificial Intelligence, 3, 100076. https://doi.org/10.1016/j.caeai.2022.100076
Liu, D. & Bates, S. (2025). Generative AI in higher education. Current practices and ways forward. Association of Pacific Rim Universities. https://www.apru.org/resources_report/whitepaper-generative-ai-in-higher-education-current-practices-and-ways-forward/
Lund, B., Lee, T.H., Mannuru, N., & Arutla, N. (2025). AI and academic integrity: Exploring student perceptions and implications for higher education. Journal of Academic Ethics, 23(1), 1–21. https://doi.org/10.1007/s10805-025-09613-3
Meakin, L. (2024). Exploring the impact of generative artificial intelligence on higher education students’ utilization of library resources: A critical examination. Information Technology and Libraries, 43(3), 1–13. https://doi.org/10.5860/ital.v43i3.17246
Mrabet, J. & Studholme, R. (2023, March 9). GPT: A friend or foe? Conference Proceedings, In the International Conference on Computational Intelligence and Knowledge Economy (ICCIKE), Dubai, United Arab Emirates. https://doi.org/10.1109/ICCIKE58312.2023.10131713
OECD. (2021). State of implementation of the OECD AI principles: Insights from national AI policies, OECD Digital Economy Papers, 311, OECD Publishing, Paris. https:/doi.org/10.1787/1cd40c44-en
Priya, D. & Vijayalakshmi, R. (2024). Grammar correction AI tools for English language teachers in higher education. IJIRT, 11(5), 380–383. https://doi.org/10.64643/IJIRTV11I5-168294-459
Rajki, Z., Dringó-Horváth, I., & Nagy, J. (2025). Artificial intelligence in higher education: Students’ artificial intelligence use and its influencing factors. Journal of University Teaching & Learning Practice, 22(2), 1–21. https://doi.org/10.53761/j0rebh67
Redecker, C. (2017). European framework for digital competence of educators: DigComEdu. Publications Office of the European Union. https://dx.doi.org/10.2760/159770
Rony, M., Ahmad, S., Das, D., Tanha, S., Deb, T., Akter, M., Khatun, M., Khalil, M., Peu, U., Parvin, M., Alrazeeni, D., & Akter, F. (2025). Nursing students’ perspectives on integrating artificial intelligence into clinical practice and training: A qualitative descriptive study. Health Science Reports. 8:370728. https://doi.org/10.1002/hsr2.70728
Selwyn, N. (2023). Teaching in the age of artificial intelligence. In B. Bloomfield (Ed.), Education in the 2030s: The big education challenges of our times; No. 2 (pp. 16–18). Monash University. https://doi.org/10.26180/25583571.v1
Sevnarayan, K. & Potter, M. (2024). Generative artificial intelligence in distance education: Transformations, challenges, and impact on academic integrity and student voice. Journal of Applied Learning & Teaching, 7(1), 1–11. https://doi.org/10.37074/jalt.2024.7.1.41
Strielkowski, W., Grebennikova, V., Lisovskiy, A., Rakhimova, G., & Vasileva, T. (2024). AI-driven adaptive learning for sustainable educational transformation. Sustainable Development, 33(2), 1921–1947. https://doi.org/10.1002/sd.3221
Taber, K. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Res Sci Educ, 48, 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
Teng, M., Singla, R., Yau, O., Lamoureux, D., Gupta, A, Hu, Z., Hu, R., Aissious, A., Eaton, S., Hamm, C., Hu, S., Kelly, D., MacMillan, K., Malik, S., Mazzoli, V., Ten, Y., Laricheva, M., Jarus, T., & Field, T. (2022). Health care students’ perspectives on artificial intelligence: Countrywide survey in Canada. JMIR Medical Education, 8(1), e33390. https://doi.org/10.2196/33390
Wang, S., Sun, Z., & Chen, Y. (2023). Effects of higher education institutes’ artificial intelligence capability on students’ self-efficacy, creativity and learning performance. Education and Information Technologies, 28(5), 4919–4939. https://doi.org/10.1007/s10639-022-11338-4
Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1798995
Zawacki-Richter, O., Marin, V., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(39), 1–27. https://doi.org/10.1186/s41239-019-0171-0
Zhang, X., Zhang, P., Shen, Y., Liu, M., Wang, Q, Gaševic, D., & Fan, Y. (2024). A systematic literature review of empirical research on applying generative artificial intelligence in education. Frontiers of Digital Education 1(3), 223–245. https://doi.org/10.1007/s44366-024-0028-5
Zhou, X., Zhang, J., & Chan, C. (2024). Unveiling students’ experiences and perceptions of artificial intelligence usage in higher education. Journal of University Teaching and Learning Practice, 21(6), 126–145. https://doi.org/10.53761/xzjprb23
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