The main goal of this study was to investigate the factors that shape K-12 teachers' trust in AI-based educational technology (AI-EdTech) across six countries, focusing on perceived benefits, concerns, and cultural influences.

 

Methods: The study surveyed 508 K-12 teachers from Brazil, Israel, Japan, Norway, Sweden, and the USA. It used multiple regression analysis to examine the relationship between teachers' trust in AI-EdTech and various factors, including demographic and professional characteristics, cultural values, AI self-efficacy, and understanding.

 

Key Findings:

• Teachers with higher AI-EdTech self-efficacy and understanding perceived more benefits and fewer concerns, leading to greater trust in AI-EdTech.
• Cultural values significantly influenced trust, with higher uncertainty avoidance and long-term orientation predicting more trust.
• Geographic differences were observed, with teachers in Brazil, Israel, and Japan showing higher trust compared to those in Norway, Sweden, and the USA.

Implications: The findings highlight the importance of enhancing teachers' understanding of AI and considering cultural values to support the adoption of AI-EdTech in education. This can inform professional development programs and policy-making to foster trust and effective use of AI in classrooms.Limitations: The study's limitations include the use of convenience samples, which may not be nationally representative, and the dynamic nature of AI and its public perception, which can change over time. Additionally, the translated survey instruments did not undergo formal psychometric evaluation.Future Directions: Future research should explore teachers' trust in AI-EdTech across different educational levels and contexts, examine the impact of professional development programs, and consider qualitative studies to understand cultural influences more deeply.

 

Title and Authors: "What Explains Teachers' Trust of AI in Education across Six Countries?" by Olga Viberg, Mutlu Cukurova, Yael Feldman-Maggor, Giora Alexandron, Shizuka Shirai, Susumu Kanemune, Barbara Wasson, Cathrine Tømte, Daniel Spikol, Marcelo Milrad, Raquel Coelho, and René F. Kizilcec.

 

Published On: December, 2023

 

Published By: Computers and Society