| Title: | Artificial intelligence in higher education teaching : usage, attitudes and trust among Croatian educators |
|---|
| Authors: | ID Luketić, Daliborka (Author)
ID Diković, Marina (Author) |
|---|
| Files: |  PDF - Source file, download (256,42 KB)
MD5: 7933F587E01E37C196108F1017CDC368
URL of processed file: https://www.sodobna-pedagogika.net/en/articles/01-2026_artificial-intelligence-in-higher-education-teaching-usage-attitudes-and-trust-among-croatian-educators/
 URL - Source URL, visit https://www.sodobna-pedagogika.net/en/articles/01-2026_artificial-intelligence-in-higher-education-teaching-usage-attitudes-and-trust-among-croatian-educators/
|
|---|
| Language: | English |
|---|
| Typology: | 1.01 - Original Scientific Article |
|---|
| Organization: |  ZDPDS - Association of Societies of Educational Workers of Slovenia
|
|---|
| Abstract: | Artificial intelligence (AI) provides numerous benefits for higher education, such as personalised learning, task automation and enhanced teaching methods. However, it also raises concerns regarding trust and acceptance among educators. Examining the factors that influence teachers’ trust and their attitudes towards adopting or rejecting AI technologies is essential for supporting the constructive and responsible integration of AI into higher education. This study explores the key determinants that shape university teachers’ trust in and attitudes regarding AI in academic instruction. Specifically, it investigates how general attitudes on AI, prior experience with AI tools, perceptions of AI’s role in academia and individual teacher characteristics affect teacher trust and acceptance. This study was conducted on a sample of 210 higher education teachers from the social sciences and humanities in the Republic of Croatia. Data for this work were collected using adapted versions of the Teacher Trust Scale (Nazaretsky, Cukurova and Alexandron 2022) and the Attitudes Towards AI Scale (Stein et al. 2024), along with additional relevant constructs. Factor analysis confirmed that teachers’ trust in AI is a multidimensional construct comprising three key dimensions: (1) perceived pedagogical values of AI, (2) familiarityand usefulness-based trust (experience-based reliance on AI) and (3) concerns and reasons for distrust in AI. The findings provide valuable insights into educators’ perceptions of AI, which are essential for understanding and shaping contemporary higher education teaching and for developing effective AI-supported teaching strategies. |
|---|
| Keywords: | artificial intelligence, higher education teaching, social sciences, higher education didactics |
|---|
| Publication status: | Published |
|---|
| Publication version: | Version of Record |
|---|
| Publication date: | 30.03.2026 |
|---|
| Year of publishing: | 2026 |
|---|
| Number of pages: | str. 70-90 |
|---|
| Numbering: | Letn. 77 = 143, št. 1 |
|---|
| PID: | 20.500.12556/DiRROS-29446  |
|---|
| UDC: | 378 |
|---|
| ISSN on article: | 0038-0474 |
|---|
| DOI: | 10.63384/spB61z867a |
|---|
| COBISS.SI-ID: | 276610307 |
|---|
| Publication date in DiRROS: | 20.05.2026 |
|---|
| Views: | 71 |
|---|
| Downloads: | 54 |
|---|
| Metadata: |    |
|---|
|
:
|
Copy citation |
|---|
| | | | Share: |  |
|---|
Hover the mouse pointer over a document title to show the abstract or click
on the title to get all document metadata. |
