What Explains Teachers' Trust of AI in Education across Six Countries?

TL;DR

The paper investigates what explains K-12 teachers' trust in AI-EdTech across six countries, treating trust as willingness to be vulnerable to AI-EdTech based on anticipated benefits and concerns. It employs a cross-national survey of 508 teachers and analyzes how demographic, professional, cognitive, and cultural factors—measured via AI self-efficacy, AI understanding, and CVSCALE Hofstede-based values—predict perceived benefits, concerns, and trust, using country-fixed effects and multiple imputations. The results show that AI self-efficacy and AI understanding shape benefits and concerns, which in turn drive trust, while cultural values and geographic location also play independent roles; demographic traits show limited effects. The findings highlight the need for culture-sensitive AI literacy and professional development to foster trustworthy adoption of AI-EdTech in classrooms, with implications for educators, policymakers, and EdTech designers.

Abstract

With growing expectations to use AI-based educational technology (AI-EdTech) to improve students' learning outcomes and enrich teaching practice, teachers play a central role in the adoption of AI-EdTech in classrooms. Teachers' willingness to accept vulnerability by integrating technology into their everyday teaching practice, that is, their trust in AI-EdTech, will depend on how much they expect it to benefit them versus how many concerns it raises for them. In this study, we surveyed 508 K-12 teachers across six countries on four continents to understand which teacher characteristics shape teachers' trust in AI-EdTech, and its proposed antecedents, perceived benefits and concerns about AI-EdTech. We examined a comprehensive set of characteristics including demographic and professional characteristics (age, gender, subject, years of experience, etc.), cultural values (Hofstede's cultural dimensions), geographic locations (Brazil, Israel, Japan, Norway, Sweden, USA), and psychological factors (self-efficacy and understanding). Using multiple regression analysis, we found that teachers with higher AI-EdTech self-efficacy and AI understanding perceive more benefits, fewer concerns, and report more trust in AI-EdTech. We also found geographic and cultural differences in teachers' trust in AI-EdTech, but no demographic differences emerged based on their age, gender, or level of education. The findings provide a comprehensive, international account of factors associated with teachers' trust in AI-EdTech. Efforts to raise teachers' understanding of, and trust in AI-EdTech, while considering their cultural values are encouraged to support its adoption in K-12 education.

Figures (2)

• Figure 1: Overview of the relationships that are investigated in this study.
• Figure 2: Variation in perceived benefits, concerns, and trust in AI-EdTech by teacher sample (n=508).