From entry to transformation: exploring AI integration in teachers’ K–12 assessment practices
Katia Ciampa, Zora M. Wolfe, Meagan Hensley
Abstract
This study explores the role of artificial intelligence (AI) in K–12 student assessment practices, focusing on educators’ use of AI tools. Through content analysis of active Facebook groups dedicated to AI in education, the authors examined how educators integrate AI into assessment across various grade levels and subjects. Using the Technology Integration Model, they analysed posts to evaluate the use of AI across subjects and grade levels. The findings revealed a progression from initial interest and experimentation with AI to more advanced, adaptive uses in assessment creation and grading. Educators reported positive experiences with AI-driven tools, especially in automating tasks and gamifying assessments. However, challenges such as ensuring reliable, context-specific feedback persist. Overall, the research highlights AI’s potential to enhance student-centred assessment practices and provides insights for educators, administrators and policymakers on AI’s evolving role in education.