Teachers’ readiness and intention to teach artificial intelligence in schools

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 emergin...

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Vydané v:Computers and education. Artificial intelligence Ročník 3; s. 100099
Hlavní autori: Ayanwale, Musa Adekunle, Sanusi, Ismaila Temitayo, Adelana, Owolabi Paul, Aruleba, Kehinde D., Oyelere, Solomon Sunday
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 2022
Elsevier
Predmet:
Behavioural intention
Distribuerade datorsystem
K-12
Nigerian schools
Pervasive Mobile Computing
Teacher readiness
Teaching artificial intelligence
Teacher readiness
K-12
Behavioural intention
Teaching artificial intelligence
Nigerian schools
ISSN:2666-920X, 2666-920X
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Popis
Shrnutí: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.
ISSN:2666-920X
2666-920X
DOI:10.1016/j.caeai.2022.100099