Keywords
AI Policy
K-12 education
Stages of Concern
Technology Acceptance Model
How to Cite
Abstract
Purpose: This study aims to examine K-12 administrators’ and educators’ perceptions of the implementation and use of artificial intelligence in educational settings, considering institutional preparedness, ethical use, data security, policy development, and technology adoption practices.
Method: The study adopted a qualitative approach based on semi-structured interviews with K-12 education professionals from different school contexts. Content analysis was guided by the Technology Acceptance Model and the Stages of Concern framework, allowing the study to examine attitudes, concerns, perceived uses, and implementation processes related to AI in educational institutions.
Findings: The findings indicate that student use of AI was the primary concern among participants, particularly regarding academic integrity, privacy, critical evaluation of AI-generated outputs, and exposure to inappropriate content. AI management and policy development also emerged as central themes. The study highlights the importance of clear guidelines, stakeholder participation in policy development, safeguards for responsible use, and professional learning communities to support ongoing AI-related learning.
Contributions: The study contributes by showing that AI implementation in K-12 education requires more than access to technological tools. Clear institutional policies, continuous professional development, alignment among administrators, teachers, students, and families, and ethical and pedagogical criteria are needed to guide responsible AI use.
Originality: The originality of the study lies in integrating administrator and educator perspectives on AI adoption in K-12 education, connecting practical concerns, institutional policy development, and theoretical models of technology acceptance and educational change.
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