Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale

Şehnaz Baltacı; Abdullah Ragıp Ersöz

doi:10.53850/joltida.1799675

Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale

Abstract

This study aimed to adapt the Artificial Intelligence Self-Efficacy Scale developed by Wang and Chuang (2024) into Turkish and evaluate its validity and reliability. The study was conducted with two independent samples: a group of 291 university students participated in the exploratory factor analysis (EFA), while a separate group of 374 participants was involved in the confirmatory factor analysis (CFA). The 22-item scale, along with demographic questions and one item on AI usage, was administered online. Cronbach’s alpha was used to assess reliability, and correlations with AI usage were examined to evaluate criterion validity. EFA revealed a four-factor structure: assistance, anthropomorphic interaction, comfort with AI, and technological skill, with factor loadings ranging from 0.43 to 0.85. The total variance explained by the factors ranged from 41.23% to 67.47% across the sub-dimensions. A weak negative correlation was found between AI self-efficacy and AI usage levels. The Cronbach’s alpha coefficient was 0.958 for the overall scale, indicating high internal consistency. CFA results confirmed that the Turkish version of the scale is a valid and reliable instrument for measuring AI self-efficacy.

Keywords

artificial intelligence, self-efficacy, level of use, anthropomorphic interaction, comfort with ai

Ethical Statement

Ethical approval for this study was obtained from Publication and Ethics Committee of the Social and Human Sciences at Bursa Uludag University (Session Date: 2024/08, Decision No: 2).

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Details

Primary Language

English

Subjects

Artificial Intelligence (Other)

Journal Section

Research Article

Authors

Şehnaz Baltacı
0000-0001-7826-7301
Türkiye

Abdullah Ragıp Ersöz ^*
0000-0003-3519-8400
Türkiye

Publication Date

April 28, 2026

Submission Date

October 8, 2025

Acceptance Date

March 17, 2026

Published in Issue

Year 2026 Volume: 11 Number: 2

DOI

https://doi.org/10.53850/joltida.1799675

IZ

https://izlik.org/JA98CP96YP

APA

Baltacı, Ş., & Ersöz, A. R. (2026). Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale. Journal of Learning and Teaching in Digital Age, 11(2), 88-97. https://doi.org/10.53850/joltida.1799675

AMA

1.Baltacı Ş, Ersöz AR. Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale. JOLTIDA. 2026;11(2):88-97. doi:10.53850/joltida.1799675

Chicago

Baltacı, Şehnaz, and Abdullah Ragıp Ersöz. 2026. “Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale”. Journal of Learning and Teaching in Digital Age 11 (2): 88-97. https://doi.org/10.53850/joltida.1799675.

EndNote

Baltacı Ş, Ersöz AR (April 1, 2026) Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale. Journal of Learning and Teaching in Digital Age 11 2 88–97.

IEEE

[1]Ş. Baltacı and A. R. Ersöz, “Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale”, JOLTIDA, vol. 11, no. 2, pp. 88–97, Apr. 2026, doi: 10.53850/joltida.1799675.

ISNAD

Baltacı, Şehnaz - Ersöz, Abdullah Ragıp. “Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale”. Journal of Learning and Teaching in Digital Age 11/2 (April 1, 2026): 88-97. https://doi.org/10.53850/joltida.1799675.

JAMA

1.Baltacı Ş, Ersöz AR. Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale. JOLTIDA. 2026;11:88–97.

MLA

Baltacı, Şehnaz, and Abdullah Ragıp Ersöz. “Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale”. Journal of Learning and Teaching in Digital Age, vol. 11, no. 2, Apr. 2026, pp. 88-97, doi:10.53850/joltida.1799675.

Vancouver

1.Şehnaz Baltacı, Abdullah Ragıp Ersöz. Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale. JOLTIDA. 2026 Apr. 1;11(2):88-97. doi:10.53850/joltida.1799675

Journal of Learning and Teaching in Digital Age 2023. This is an Open Access journal distributed under the terms of the Creative Commons Attribution International 4.0 (CC BY 4.0) license.

Journal of Learning and Teaching in Digital Age. Open Access Journal, 2023. ISSN:2458-8350

Adaptation and Validation of the Artificial Intelligence Self-Efficacy Scale

Abstract

Keywords

Ethical Statement

References

Details

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Subjects

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Authors

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Submission Date

Acceptance Date

Published in Issue

DOI

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