Student Perception of Using Artificial Intelligence in Education
Rapid artificial intelligence (AI) penetration into university education presents opportunities and challenges. One of the issues is how the study materials and general support correlate with the student's perceptions of AI. Teachers should also know in which aspects (or applications fields) of AI students are uneasy and feel fear or danger. In this regard, a survey has been conducted in three countries, Iceland, Slovakia, and Serbia, covering three different European regions and different but intertwined study programs. Our results in the survey opinion mining are intriguing in several ways. For example, it has been shown that business students are more likely to support mandatory AI courses than business informatics students. Next, students feel the danger of applying AI in medicine, even though AI is usually learning from high-quality medical records. In this work, we explored the statistically significant differences in responses, proposed recommendations, and identified topics for future surveys. For example, why are the recognized application fields problematic from the students’ perspective? And handling hesitation in answers because, in a rapidly developing field of AI, it is difficult to express opinions clearly.
Authors
- Eva Rakovská (ORCID: https://orcid.org/0000-0002-6191-184X)
- Hanna Kristín Skaftadóttir (ORCID: https://orcid.org/0000-0001-5228-8294)
- Milica Zukanović (ORCID: https://orcid.org/0000-0003-3650-8327)
- Pavle Milošević (ORCID: https://orcid.org/0000-0002-5943-6023)
- Daša Mokošová (ORCID: https://orcid.org/0000-0003-1829-6957)
- Miroslav Hudec (ORCID: https://orcid.org/0000-0002-2868-0322)
- Nina Barčáková
- Ragnar Már Vilhjálmsson (ORCID: https://orcid.org/0009-0007-5373-0233)
- Haraldur Dadi Ragnarsson (ORCID: https://orcid.org/0009-0009-9032-014X)
Institutions
- University of Belgrade (RS)
- Bifröst University (IS)
- Bratislava University of Economics and Business (SK)
Publication Details
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1109/icedeg65568.2025.11081680
- Primary Topic
- Online Learning and Analytics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agentúra na Podporu Výskumu a Vývoja
- Vedecká Grantová Agentúra MŠVVaŠ SR a SAV