Cukurova, M;
Miao, X;
Brooker, R;
(2023)
Adoption of Artificial Intelligence in Schools: Unveiling Factors Influencing Teachers’ Engagement.
In:
AIED 2023: Artificial Intelligence in Education.
(pp. pp. 151-163).
Springer Nature
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Abstract
Albeit existing evidence about the impact of AI-based adaptive learning platforms, their scaled adoption in schools is slow at best. In addition, AI tools adopted in schools may not always be the considered and studied products of the research community. Therefore, there have been increasing concerns about identifying factors influencing adoption, and studying the extent to which these factors can be used to predict teachers’ engagement with adaptive learning platforms. To address this, we developed a reliable instrument to measure more holistic factors influencing teachers’ adoption of adaptive learning platforms in schools. In addition, we present the results of its implementation with school teachers (n = 792) sampled from a large country-level population and use this data to predict teachers’ real-world engagement with the adaptive learning platform in schools. Our results show that although teachers’ knowledge, confidence and product quality are all important factors, they are not necessarily the only, may not even be the most important factors influencing the teachers’ engagement with AI platforms in schools. Not generating any additional workload, increasing teacher ownership and trust, generating support mechanisms for help, and assuring that ethical issues are minimised, are also essential for the adoption of AI in schools and may predict teachers’ engagement with the platform better. We conclude the paper with a discussion on the value of factors identified to increase the real-world adoption and effectiveness of adaptive learning platforms by increasing the dimensions of variability in prediction models and decreasing the implementation variability in practice.
| Type: | Proceedings paper |
|---|---|
| Title: | Adoption of Artificial Intelligence in Schools: Unveiling Factors Influencing Teachers’ Engagement |
| Event: | International Conference on Artificial Intelligence in Education (AIED 2023) |
| ISBN-13: | 978-3-031-36271-2 |
| DOI: | 10.1007/978-3-031-36272-9_13 |
| Publisher version: | https://doi.org/10.1007/978-3-031-36272-9_13 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Artificial Intelligence, Adoption, Adaptive Learning Platforms, Factor Analysis, Predictive Models, Human Factors |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education UCL > Provost and Vice Provost Offices > School of Education > UCL Institute of Education > IOE - Culture, Communication and Media |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10175451 |
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