Artificial Intelligence Anxiety Among University Students and Academics: The Case of Batman University

This study examines the levels of artificial intelligence (AI) anxiety among academic staff and students at Batman University. Data were collected from 500 academic personnel and 500 students using the Artificial Intelligence Anxiety Scale (AIAS) and analyzed through descriptive statistical methods, including t-tests and ANOVA. The study focused on demographic variables such as gender, age, academic field, and years of experience. The findings indicate that male academic staff experienced higher levels of AI anxiety, particularly in job change, sociotechnical blindness, and AI structuring. Less experienced academics also reported elevated anxiety. In the student group, females and those studying in social sciences showed higher anxiety, with the highest job change anxiety detected among the 17–25 age group. These results suggest that AI anxiety varies significantly across demographic categories. The study emphasizes the need for targeted awareness and training programs within academic institutions to support adaptation to AI technologies.

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Publication Details

Journal
Balkan Journal of Electrical and Computer Engineering
Published
2025-12-31
DOI
https://doi.org/10.17694/bajece.1649753
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial Intelligence Anxiety Among University Students and Academics: The Case of Batman University

Murat Sinan Özdaş, Hafzullah İş, Suat Gök
Balkan Journal of Electrical and Computer Engineering
AI in Service Interactions
article

Artificial Intelligence Anxiety Among University Students and Academics: The Case of Batman University

Murat Sinan Özdaş, Hafzullah İş, Suat Gök
article en

Abstract

This study examines the levels of artificial intelligence (AI) anxiety among academic staff and students at Batman University. Data were collected from 500 academic personnel and 500 students using the Artificial Intelligence Anxiety Scale (AIAS) and analyzed through descriptive statistical methods, including t-tests and ANOVA. The study focused on demographic variables such as gender, age, academic field, and years of experience. The findings indicate that male academic staff experienced higher levels of AI anxiety, particularly in job change, sociotechnical blindness, and AI structuring. Less experienced academics also reported elevated anxiety. In the student group, females and those studying in social sciences showed higher anxiety, with the highest job change anxiety detected among the 17–25 age group. These results suggest that AI anxiety varies significantly across demographic categories. The study emphasizes the need for targeted awareness and training programs within academic institutions to support adaptation to AI technologies.

Balkan Journal of Electrical and Computer EngineeringVol. 13(4)
Batman University (TR)
Gender equality
Openalex Percentile: Top 13%
AI in Service Interactions
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Artificial Intelligence Anxiety Among University Students and Academics: The Case of Batman University — Murat Sinan Özdaş, Hafzullah İş, et al. · Balkan Journal of Electrical and Computer Engineering (2025) | TGRS Research Map | TGRS