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Teachers’ readiness and intention to teach artificial intelligence in schools

Authors :
Ayanwale, Musa Adekunle
Sanusi, Ismaila Temitayo
Adelana, Owolabi Paul
Aruleba, Kehinde D.
Oyelere, Solomon Sunday
Ayanwale, Musa Adekunle
Sanusi, Ismaila Temitayo
Adelana, Owolabi Paul
Aruleba, Kehinde D.
Oyelere, Solomon Sunday
Publication Year :
2022

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.<br />Validerad;2022;Nivå 1;2022-09-15 (hanlid)

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1348929451
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1016.j.caeai.2022.100099