Factors Affecting Teachers' Acceptance of Artificial Intelligence Technologies: Analyzing Teacher Perspectives with Structural Equation Modeling

Özlem Gökçe Tekin

doi:10.52911/itall.1532218

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Factors Affecting Teachers' Acceptance of Artificial Intelligence Technologies: Analyzing Teacher Perspectives with Structural Equation Modeling

Abstract

Recent advances in artificial intelligence (AI) technologies have brought to the agenda how to encourage the use of these technologies in education. Teachers' acceptance of AI technologies has an important place. This study, based on the Technology Acceptance Model (TAM), investigates the factors affecting teachers' acceptance of AI technologies. A five-structure structural model for AI technology was proposed by adding Self-Efficacy and Anxiety to TAM. A trial form consisting of 21 items was prepared and 18 items were confirmed. Structural Equation Modeling (SEM) was used to analyze the data. In the proposed model, 7 hypotheses related to Self-Efficacy (SE), Artificial Intelligence Anxiety (AIA), Perceived Ease of Use (PEU), Perceived Utility (PU) and Behavioral Intention (BI) were tested. A significant negative effect was obtained with H1, H2 and H7; a significant positive effect was obtained with H3, H4 and H6, while H5 was not confirmed. The effect of teachers' perceived ease of use on perceived usefulness (H3) and the effect of perceived usefulness on behavioral intention (H6) were the strongest positive effects in the model. The effect of AI anxiety on perceived ease of use (H2) was the strongest negative effect. It was found that teachers' acceptance of using AI technologies in teaching is predictable by teachers' self-efficacy towards AI, AI anxiety and perceived usefulness. The results of this study contributed to the extension of TAM. This study presents a TAM study on AI technologies. In addition, the results can help future educational planning in the use of educational technologies.

Keywords

Artificial intelligence anxiety , Self-efficacy , Technology acceptance model , Structural equation model , Teachers

Öğretmenlerin Yapay Zekâ Teknolojilerini Kabulünü Etkileyen Faktörler: Yapısal Eşitlik Modeli ile Öğretmen Bakış Açılarının Analizi

Öz

Yapay zekâ teknolojilerindeki hızlı ilerlemeler, eğitimde bu teknolojilerin kullanımının nasıl teşvik edileceğini gündeme getirmiştir. Öğretmenlerin yapay zekâ teknolojilerini kabulü bu bakımdan önemli bir yere sahiptir. Teknoloji Kabul Modeli'ne (TKM) dayanan bu çalışma, öğretmenlerin yapay zekâ teknolojilerini kabulünü etkileyen faktörleri araştırmaktadır. Bu amaçla TKM’ye Öz-yeterlik ve Kaygı eklenerek yapay zekâ teknolojisine yönelik beş yapılı bir yapısal model önerilmiştir. Verilerin toplanması için 21 maddeden oluşan bir ölçek hazırlanmıştır. 18 madde Doğrulayıcı Faktör Analizi ile doğrulanmıştır. Verilerin analizinde Yapısal Eşitlik Modeli kullanılmıştır. Önerilen modelde, Öz-yeterlik (ÖY), Yapay Zekâ Kaygısı (YZK), Algılanan Kullanım Kolaylığı (AKK), Algılanan Fayda (AF) ve Davranışsal Niyet (DN) ile ilgili 7 hipotez test edilmiştir. Hipotezlerden H1, H2 ve H7 ile anlamlı bir negatif etki; H3, H4 ve H6 ile ise anlamlı bir pozitif etki elde edilirken H5 doğrulanmamıştır. Öğretmenlerin Algılanan kullanım kolaylığının Algılanan faydası üzerindeki etkisinin (H3) ve Algılanan Faydasının Davranışsal niyeti üzerindeki etkisinin (H6) sırasıyla modeldeki en güçlü olumlu etkiler olduğu tespit edilmiştir. Yapay zekâ kaygısının Algılanan kullanım kolaylığının üzerindeki etkisinin (H2) ise en güçlü negatif etki oldğu tespit edilmiştir. Çalışmada öğretmenlerin öğretimde yapay zekâ teknolojilerini kullanmayı kabullerinin, öğretmenlerin yapay zekâya yönelik öz-yeterliği, yapay zekâ kaygısı ve algılanan faydası tarafından tahmin edilebilir olduğu tespit edilmiştir. Bu çalışmanın sonuçları TKM’nin genişletilmesine katkıda bulunmuştur. Bu çalışma Türkiye’de alanyazındaki önemli bir boşluğu doldurarak yapay zekâ teknolojilerini konu alan bir TKM çalışması sunmaktadır. Ayrıca çalışmanın sonuçları, eğitim teknolojilerinin kullanılmasında gelecekteki eğitim planlamalarına yardımcı olabilecek niteliktedir.

Anahtar Kelimeler

Yapay zekâ kaygısı , Öz-yeterlik , Teknoloji kabul modeli , Yapısal eşitlik modeli , Öğretmenler

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Details

Primary Language

English

Subjects

Other Fields of Education (Other)

Journal Section

Research Article

Authors

Özlem Gökçe Tekin ^*
0000-0002-4436-3060
Türkiye

Early Pub Date

December 31, 2024

Publication Date

December 31, 2024

Submission Date

August 12, 2024

Acceptance Date

December 26, 2024

Published in Issue

Year 2024 Volume: 5 Number: 2

DOI

https://doi.org/10.52911/itall.1532218

IZ

https://izlik.org/JA95WJ52FP

APA

Gökçe Tekin, Ö. (2024). Factors Affecting Teachers’ Acceptance of Artificial Intelligence Technologies: Analyzing Teacher Perspectives with Structural Equation Modeling. Instructional Technology and Lifelong Learning, 5(2), 399-420. https://doi.org/10.52911/itall.1532218