Teachers' trust in AI‐powered educational technology and a professional development program to improve it

Tanya Nazaretsky, Moriah Ariely, Mutlu Cukurova, Giora Alexandron

Research output: Contribution to journalArticlepeer-review


Evidence from various domains underlines the critical role that human factors, and especially trust, play in adopting technology by practitioners. In the case of Artificial Intelligence (AI) powered tools, the issue is even more complex due to practitioners' AI-specific misconceptions, myths and fears (e.g., mass unemployment and privacy violations). In recent years, AI has been incorporated increasingly into K-12 education. However, little research has been conducted on the trust and attitudes of K-12 teachers towards the use and adoption of AI-powered Educational Technology (AI-EdTech). This paper sheds light on teachers' trust in AI-EdTech and presents effective professional development strategies to increase teachers' trust and willingness to apply AI-EdTech in their classrooms. Our experiments with K-12 science teachers were conducted around their interactions with a specific AI-powered assessment tool (termed AI-Grader) using both synthetic and real data. The results indicate that presenting teachers with some explanations of (i) how AI makes decisions, particularly compared to the human experts, and (ii) how AI can complement and give additional strengths to teachers, rather than replacing them, can reduce teachers' concerns and improve their trust in AI-EdTech. The contribution of this research is threefold. First, it emphasizes the importance of increasing teachers' theoretical and practical knowledge about AI in educational settings to gain their trust in AI-EdTech in K-12 education. Second, it presents a teacher professional development program (PDP), as well as the discourse analysis of teachers who completed it. Third, based on the results observed, it presents clear suggestions for future PDPs aiming to improve teachers' trust in AI-EdTech.
Original languageEnglish
Pages (from-to)914-931
Number of pages18
JournalBritish Journal of Educational Technology
Issue number4
StatePublished - Jul 2022


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