Drivers of Chatbot Adoption among K–12 Teachers in Saudi Arabia

The aim of the current study was to identify the factors influencing teachers’ acceptance of using chatbots in education. To achieve this, we employed the descriptive method, applying the conceptual framework of the unified theory of acceptance and use of technology (UTAUT2) to a sample of 406 teachers from the Eastern Province in Saudi Arabia. By applying structural equation modelling (SEM), the research results revealed that the most influential factors of chatbot acceptance among Saudi teachers were artificial intelligence literacy, followed by hedonic motivation, and then social influence. Meanwhile, performance expectancy, effort expectancy, and facilitating conditions were not significant indicators of teachers’ acceptance of using chatbots in education. In light of these findings, we recommend the following actions: focusing on artificial intelligence literacy for teachers, holding specialised workshops on chatbot applications in education, enhancing teachers’ motivation to use chatbots, and forming professional communities for teachers to exchange experiences and knowledge.

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Publication Details

Journal
Education Sciences
Published
2024-09-22
DOI
https://doi.org/10.3390/educsci14091034
Citations
12
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
4.17
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article

Drivers of Chatbot Adoption among K–12 Teachers in Saudi Arabia

Ahlam Mohammed Al-Abdullatif, Nada Ali Al-Amri
12 citations
Education Sciences
AI in Service Interactions
4.17
article

Drivers of Chatbot Adoption among K–12 Teachers in Saudi Arabia

Ahlam Mohammed Al-Abdullatif, Nada Ali Al-Amri
article en
12 citations

Abstract

The aim of the current study was to identify the factors influencing teachers’ acceptance of using chatbots in education. To achieve this, we employed the descriptive method, applying the conceptual framework of the unified theory of acceptance and use of technology (UTAUT2) to a sample of 406 teachers from the Eastern Province in Saudi Arabia. By applying structural equation modelling (SEM), the research results revealed that the most influential factors of chatbot acceptance among Saudi teachers were artificial intelligence literacy, followed by hedonic motivation, and then social influence. Meanwhile, performance expectancy, effort expectancy, and facilitating conditions were not significant indicators of teachers’ acceptance of using chatbots in education. In light of these findings, we recommend the following actions: focusing on artificial intelligence literacy for teachers, holding specialised workshops on chatbot applications in education, enhancing teachers’ motivation to use chatbots, and forming professional communities for teachers to exchange experiences and knowledge.

Education SciencesVol. 14(9)
King Faisal University (SA)
Openalex Percentile: Top 5%
AI in Service Interactions
4.17
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