Artificial Intelligence Awareness Scale Development Study

Şükrü Mustafa Kaya; Vildan Bayram

doi:10.26466/opusjsr.1680531

EN TR

Artificial Intelligence Awareness Scale Development Study

Abstract

The aim of the study is to develop a valid and reliable measurement tool to measure employees' perceptions of artificial intelligence awareness. In the first stage of the three-stage scale development study, in-depth interviews were conducted. As a result of the content analysis of the data obtained from the interviews, a 41-item proposition pool was created. In the second stage, a draft of the items was created and the scale was structured by consulting expert opinions in order to ensure meaning, face and scope validity. In the last stage, the scale was evaluated and a 14-item draft scale was created. As a result of the pilot application conducted on 132 employees working in the healthcare sector using the draft scale, it was decided to remove one item from the scale. Then, the final scale consisting of 13 items was reached: 139 employees in the automotive sector and 152 employees in the logistics sector. As a result of the analysis, a 13-item one-dimensional scale emerged. The CFA server determined that the scale provided an acceptable level of fit. Cronbach's Alpha values were 0.834 in the healthcare sector; It was calculated as 0.810 in the automotive sector and 0.867 in the logistics sector, and the scale was found to be valid and reliable. The scale is an important measurement tool to be used to analyze individuals' awareness of AI in measuring the level of individual awareness, determining educational needs, conducting attitude analysis, developing policies and strategies, and academic research.

Keywords

Artificial Intelligence , Artificial Intelligence Perception , Artificial Intelligence Aware-ness , Scale Development , Scale

Yapay Zekâ Farkındalık Ölçeği Geliştirme Çalışması

Öz

Bu çalışmada, çalışanların yapay zekâ farkındalığına ilişkin algılarını ölçmek üzere geçerli ve güvenilir bir ölçüm aracı geliştirmek amaçlanmıştır. Üç aşamalı ölçek geliştirme çalışmasının ilk aşamasında derinlemesine görüşmeler yapılmıştır. Bu görüşmelerden elde edilen verilerin içerik analizi sonucunda 41 maddelik önerme havuzu oluşturulmuştur. İkinci aşamada maddelerin taslağı oluşturulmuş ve anlam, görünüş ve kapsam geçerliliğini sağlamak amacıyla uzman görüşlerine başvurularak ölçek yapılandırılmıştır. Son aşamada ölçek değerlendirilmiş ve 14 maddelik taslak ölçek oluşturulmuştur. Taslak ölçek kullanılarak sağlık sektöründe çalışan 132 çalışan üzerinde yapılan pilot uygulama sonucunda ölçekten bir maddenin çıkarılmasına karar verilmiştir. Daha sonra 13 maddeden oluşan nihai ölçeğe ulaşılmıştır: Otomotiv sektöründe 139 çalışan ve lojistik sektöründe 152 çalışan. Yapılan analizler sonucunda 13 maddelik tek boyutlu bir ölçek ortaya çıkmıştır. CFA sunucusu ölçeğin kabul edilebilir düzeyde uyum sağladığını belirlemiştir. Cronbach's Alpha değerleri sağlık sektöründe 0,834; otomotiv sektöründe 0,810 ve lojistik sektöründe 0,867 olarak hesaplanmış olup ölçeğin geçerli ve güvenilir olduğu bulunmuştur. Ölçek, bireysel farkındalık düzeyinin ölçülmesinde, eğitim ihtiyaçlarının belirlenmesinde, tutum analizlerinin yapılmasında, politika ve stratejiler geliştirilmesinde, akademik araştırmalarda bireylerin yapay zekaya ilişkin farkındalıklarının analiz edilmesinde kullanılabilecek önemli bir ölçüm aracıdır.

Anahtar Kelimeler

Yapay Zekâ , Yapay Zekâ Algısı , Yapay Zekâ Farkındalığı Ölçek Geliştirme , Ölçek

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Ampirik Yazılım Mühendisliği

Bölüm

Araştırma Makalesi

Yazarlar

Şükrü Mustafa Kaya ^*
0000-0003-2710-0063
Türkiye

Vildan Bayram
0000-0001-7526-6485
Türkiye

Erken Görünüm Tarihi

27 Temmuz 2025

Yayımlanma Tarihi

4 Ağustos 2025

Gönderilme Tarihi

20 Nisan 2025

Kabul Tarihi

23 Haziran 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 22 Sayı: 4

DOI

https://doi.org/10.26466/opusjsr.1680531

IZ

https://izlik.org/JA23XK78NN

APA

Kaya, Ş. M., & Bayram, V. (2025). Artificial Intelligence Awareness Scale Development Study. OPUS Journal of Society Research, 22(4), 657-672. https://doi.org/10.26466/opusjsr.1680531

Cited By

Data Pre-processing Approach with ML Algorithms for Accuracy and Authenticity Detection of Big Data Sourced from the Social Internet of Things and a Case Study

Balkan Journal of Electrical and Computer Engineering

https://doi.org/10.17694/bajece.1712376

Artificial Intelligence Awareness Scale Development Study

Abstract

Keywords

Yapay Zekâ Farkındalık Ölçeği Geliştirme Çalışması

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Erken Görünüm Tarihi

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster

Cited By

Data Pre-processing Approach with ML Algorithms for Accuracy and Authenticity Detection of Big Data Sourced from the Social Internet of Things and a Case Study