Education, knowledge, attitude, and practices toward artificial intelligence

Abstract

This mixed-methods study investigates the knowledge, attitudes, and implementation perspectives regarding artificial intelligence (AI) in education among key stakeholder groups. Quantitative surveys (n=842) and qualitative interviews (n=48) were conducted with K-12 educators, higher education faculty, educational administrators, students, and parents. Results revealed significant knowledge disparities across stakeholder groups, with higher education faculty demonstrating the highest understanding of AI (M=14.8/20) and parents the lowest (M=9.4/20). Generally positive attitudes toward AI in education were observed (M=3.56/5), though with notable variations; students exhibited the most positive attitudes (M=3.81/5), while parents and K-12 educators reported the lowest (M=3.36/5 and M=3.41/5, respectively). Implementation concerns were highest for privacy protocols (M=4.31/5) and training needs (M=4.14/5). Cluster analysis identified four distinct stakeholder profiles: Enthusiastic Adopters (23.8%), Cautious Implementers (31.5%), Skeptical Observers (18.2%), and Knowledge-Seeking Pragmatists (26.5%). Qualitative findings revealed five themes: Navigating the AI Knowledge Landscape, Balancing Promise and Peril, Resource Realities, Ethical Guardrails, and Evolving Professional Identities. Structural equation modeling demonstrated knowledge as both a direct (β=0.31) and indirect predictor (β=0.18) of implementation perspectives, with attitudes partially mediating this relationship. These findings highlight the need for targeted interventions that address knowledge gaps, ethical concerns, and resource limitations while acknowledging the diverse perspectives of educational stakeholders. The study contributes to theoretical understanding of educational AI adoption by revealing complex interrelationships between knowledge, attitudes, and implementation perspectives that challenge linear models of technological integration.