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Cited by 412Artificial Intelligence in EducationEducation and Technology IntegrationEducational Technology and Pedagogy

Teachers’ readiness and intention to teach artificial intelligence in schools

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Ayanwale, Musa Adekunle, Sanusi, Ismaila Temitayo, Adelana, Owolabi Paul, Aruleba, Kehinde D., Oyelere, Solomon Sunday·2022·Computers and Education: Artificial Intelligence
DOI 10.1016/j.caeai.2022.100099
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Abstract

The emergence of artificial intelligence (AI) as a subject to be incorporated into K-12 educational levels places new demand on relevant stakeholders, especially teachers that drive the teaching and learning process. It is therefore important to understand how ready teachers are to teach the emerging subject as the success of AI education would probably be closely dependent on the readiness of teachers. As a result, this study presents an insight into factors influencing the behavioural intention and readiness of Nigerian in-service teachers to teach artificial intelligence. A total of 368 teachers, from elementary to high school participated in the study. We utilised quantitative methodology using variance-based structural equation modelling to understand the relationship among the eight variables (AI anxiety, perceived usefulness, AI for social good, Attitude towards using AI, perceived confidence in teaching AI, relevance of AI, AI readiness, and behavioural intention) considered in the study. The result indicated that confidence in teaching AI predicts intention to teach AI while AI relevance strongly predicts readiness to teach AI. While other factors influence the teaching of AI, anxiety and social good could not predict teachers' intention and readiness to implement AI in classrooms respectively. We discussed the implication of our findings in relation to AI implementation in schools and highlight future directions.

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  • Students' attitudes toward GenAI tools are shaped by their level of familiarity and the nature of their experiences: positive engagement tends to foster adoption, while limited exposure or difficulty using the tools may lead to caution or skepticism.

    “Previous research has shown that students' attitudes toward GenAI tools are shaped by their level of familiarity and the nature of their experiences: positive engagement tends to foster adoption, while limited exposure or difficulty using the tools may lead to caution or skepticism (Zhang et al., 2023;Ayanwale et al., 2022;Wang et al., 2021).”

    From Integrating Generative AI into Programming Education: Student Perceptions and the Challenge of Correcting AI Errors (2025) · cites this paper as Ayanwale et al., 2022

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Authors
Ayanwale, M. A., Sanusi, I. T., Adelana, O. P., Aruleba, K. D., & Oyelere, S. S.
Affiliations
  • University of Johannesburg (ZA)
  • University of Eastern Finland (FI)
  • University of Ibadan (NG)
  • University of Leicester (GB)
  • Luleå University of Technology (SE)
Corresponding author
Ayanwale, Musa Adekunle
ORCID
Venue
Computers and Education: Artificial Intelligence
Publisher
Elsevier BV
Published
2022
Volume
3
Pages
100099
ISSN
2666-920X (ISSN-L)
DOI
10.1016/j.caeai.2022.100099
OpenAlex
W4295413191
Cited by
412
References
5
Citations by year
2026: 106 · 2025: 152 · 2024: 110 · 2023: 40 · 2022: 4
FWCI
75.71
Type
journal article
Language
en
Open access
Licence
Locations
  • Computers and Education Artificial Intelligence (publishedVersion, cc-by-nc-nd)
  • KTH Publication Database DiVA (KTH Royal Institute of Technology) (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Education › Education and Technology Integration
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Technology and Pedagogy
Keywords
artificial intelligence in education, teacher readiness, behavioral intention, in-service teachers, K-12 education, AI anxiety, perceived usefulness, perceived confidence, Nigerian teachers

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