Artificial Intelligence Driven Learning for Sustainable Education:
The integration of Artificial Intelligence (AI) with technology-enhanced learning platforms has the potential to improve education and presents a transformative approach to addressing educational challenges. Despite its beneficial impacts on education, concerns about students’ AI literacy have prompted empirical investigations on the perceived AI presences in connection with its usage, benefits, and related risks in classroom instructional practices. This study examined higher vocational students’ perceptions and attitudes on artificial intelligence-driven learning based on survey results. The respondents were 372 undergraduate students in one of higher vocational institutions in Indonesia. The data was collected through questionnaire survey distributed through students’ class WhatsApp group. The questionnaire consisted of two main sections including demographic information and integrated constructs from the Unified Theory of Acceptance and Use of Technology (UTAUT). The data were analyzed using Statistical Package for the Social Sciences (SPSS). The results show that the means scores for each item in the dataset exceeded 3 indicating positive attitudes towards AI usage and effectiveness in academic settings, they mostly agree that AI tools were beneficial in enhancing their academic performance and engagement in their daily college life. This empirical investigation hopefully offers insights for educators, policymakers, and institutions to make informed decision regarding the integration of AI in the instructional practices.
Authors
- Rini Amelia (ORCID: https://orcid.org/0009-0003-2590-7784)
- Rizky Amelia (ORCID: https://orcid.org/0000-0003-4310-8620)
- Rahma Pitria Ningsih (ORCID: https://orcid.org/0000-0002-1988-3814)
- Heppy Mutammimah (ORCID: https://orcid.org/0000-0001-5065-9776)
- Siti Kustini (ORCID: https://orcid.org/0000-0001-8441-9113)
Institutions
- Universitas Achmad Yani (ID)
Publication Details
- Journal
- Proceeding International Seminar of Science and Technology
- Published
- 2025-04-17
- DOI
- https://doi.org/10.33830/isst.v4i1.5224
- Primary Topic
- Smart Cities and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00