ERIC Number: EJ1422012
Record Type: Journal
Publication Date: 2024
Pages: 22
Abstractor: As Provided
ISBN: N/A
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EISSN: EISSN-2731-5525
Available Date: N/A
Exploring STEAM Teachers' Trust in AI-Based Educational Technologies: A Structural Equation Modelling Approach
Musa Adekunle Ayanwale; Owolabi Paul Adelana; Tolulope Timothy Odufuwa
Discover Education, v3 Article 44 2024
In the rapidly evolving landscape of education, Artificial Intelligence (AI) has emerged as a transformative tool with the potential to revolutionize teaching and learning processes. However, the successful integration of AI in education depends on the trust and acceptance of teachers. This study addresses a significant gap in research by investigating the trust dynamics of 677 in-service Science, Technology, Engineering, Arts, and Mathematics (STEAM) teachers in Nigeria towards AI-based educational technologies. Employing structural equation modelling for data analysis, our findings reveal that anxiety, preferred methods to increase trust, and perceived benefits significantly influence teachers' trust in AI-based edtech. Notably, the lack of human characteristics in AI does not impact trust among STEAM teachers. Additionally, our study reports a significant gender moderation effect on STEAM teachers' trust in AI. These insights are valuable for educational policymakers and stakeholders aiming to create an inclusive, AI-enriched instructional environment. The results underscore the importance of continuous professional development programs for STEAM teachers, emphasizing hands-on experiences to build and sustain confidence in integrating AI tools effectively, thus fostering trust in the transformative potentials of AI in STEAM education.
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Trust (Psychology), STEM Education, Art Education, Teacher Attitudes, Gender Differences, Foreign Countries
Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://bibliotheek.ehb.be:2123/
Publication Type: Journal Articles; Reports - Research
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Language: English
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Identifiers - Location: Nigeria
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Author Affiliations: N/A