A Comparative Study of AI Integration Barriers in K–12 Education in South Korea, Taiwan, and the United States
Year: 2025
Type: conference-paper
Abstract: This comparative study investigated barriers to AI integration in K-12 education across South Korea, Taiwan, and the United States, addressing a gap in understanding educators' perspectives (Casal-Otero et al., 2023). Semi-structured interviews with 45 educators were conducted and analyzed using Ertmer's first-and-second-order barriers to change framework (1999), revealing first-order and second-order barriers. Despite challenges, participants expressed positive views toward AI integration. The study identified four themes and highlighted differences between countries with and without clear AI integration policies. This contributes to a comprehensive understanding of AI integration in K-12 education across different national contexts.
Authors: Seoljoo Kang, Wanju Huang, Sunnie Watson, Chi-Jia Hsieh, William Watson, Wonjin Yu
Institution: Purdue University West Lafayette
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4412480072