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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| Published in: | Computers and education. Artificial intelligence Vol. 3; p. 100099 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
2022
Elsevier |
| Subjects: | |
| ISSN: | 2666-920X, 2666-920X |
| Online Access: | Get full text |
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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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| AbstractList | 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. |
| ArticleNumber | 100099 |
| Author | Adelana, Owolabi Paul Ayanwale, Musa Adekunle Sanusi, Ismaila Temitayo Aruleba, Kehinde D. Oyelere, Solomon Sunday |
| Author_xml | – sequence: 1 givenname: Musa Adekunle orcidid: 0000-0001-7640-9898 surname: Ayanwale fullname: Ayanwale, Musa Adekunle email: ayanwalea@uj.ac.za organization: Department of Science and Technology Education, University of Johannesburg, South Africa – sequence: 2 givenname: Ismaila Temitayo orcidid: 0000-0002-5705-6684 surname: Sanusi fullname: Sanusi, Ismaila Temitayo email: ismaila.sanusi@uef.fi organization: School of Computing, University of Eastern Finland, P.O.Box 111, 80101, Joensuu, Finland – sequence: 3 givenname: Owolabi Paul orcidid: 0000-0002-4829-5106 surname: Adelana fullname: Adelana, Owolabi Paul email: paulyetty@gmail.com organization: Department of Science and Technology Education, University of Ibadan, Ibadan, Nigeria – sequence: 4 givenname: Kehinde D. orcidid: 0000-0003-3422-7046 surname: Aruleba fullname: Aruleba, Kehinde D. email: ka388@leicester.ac.uk organization: School of Computing and Mathematical Sciences, University of Leicester, UK – sequence: 5 givenname: Solomon Sunday orcidid: 0000-0001-9895-6796 surname: Oyelere fullname: Oyelere, Solomon Sunday email: solomon.oyelere@ltu.se organization: Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, SE-931 87, Skellefteå, Sweden |
| BackLink | https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-93036$$DView record from Swedish Publication Index |
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| Keywords | Teacher readiness K-12 Behavioural intention Teaching artificial intelligence Nigerian schools |
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