Abstract
The strong development of artificial intelligence (AI) and its growing application in education are generating debate about its potential and challenges in higher education. This study aims to understand how students' experiences with differentiated active learning methods affect their perceptions of AI's role in academic education. A quantitative survey was conducted using a standardized survey questionnaire, including students from Poland, Romania, Greece and Croatia. The study used a quantitative approach, analysis was conducted in three analytical stages using (1) descriptive statistics, (2) hierarchical cluster analysis using Ward's method, and (3) a detailed description each of the identified groups, which allowed a comparison of their attitudes and experiences in the context of using artificial intelligence in education. The results show that students who have had experience with diverse teaching methods show more enthusiasm for AI, while those who prefer traditional methods are more cautious. Four distinct groups of students were identified who differ in their attitudes toward using AI in learning. The study underscores the importance of incorporating diverse teaching methods and educational technologies to support future competencies.
Paper Type
Short Paper
DOI
10.62036/ISD.2025.122
Between tradition and innovation: students' approach to AI in the context of experienced teaching methods
The strong development of artificial intelligence (AI) and its growing application in education are generating debate about its potential and challenges in higher education. This study aims to understand how students' experiences with differentiated active learning methods affect their perceptions of AI's role in academic education. A quantitative survey was conducted using a standardized survey questionnaire, including students from Poland, Romania, Greece and Croatia. The study used a quantitative approach, analysis was conducted in three analytical stages using (1) descriptive statistics, (2) hierarchical cluster analysis using Ward's method, and (3) a detailed description each of the identified groups, which allowed a comparison of their attitudes and experiences in the context of using artificial intelligence in education. The results show that students who have had experience with diverse teaching methods show more enthusiasm for AI, while those who prefer traditional methods are more cautious. Four distinct groups of students were identified who differ in their attitudes toward using AI in learning. The study underscores the importance of incorporating diverse teaching methods and educational technologies to support future competencies.
Recommended Citation
Palimąka, K., Ociepa-Kicińska, E., Porada-Rochoń, M. & Mierzejewski, M.M. (2025). Between tradition and innovation: students' approach to AI in the context of experienced teaching methodsIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.122