Preparing K-12 Teachers for Artificial Intelligence: Teacher Readiness, Professional Development Needs, and AI Integration in American Classrooms
DOI:
https://doi.org/10.63084/cognexus.v1i04.286Keywords:
artificial intelligence, teacher readiness, professional development, AI integration, K-12 education, teacher educationAbstract
The rapid expansion of artificial intelligence in education has increased expectations for teachers to integrate AI into instructional practice while addressing concerns related to accuracy, ethics, privacy, academic integrity, and student learning. This study examined AI readiness, professional development needs, institutional support, and classroom AI integration among K-12 teachers in the United States. Data were collected through a cross-sectional survey of 526 practicing teachers representing elementary, middle, and high school settings across U.S. geographic regions. Teacher AI readiness was examined across cognition, ability, vision, and ethics, alongside measures of professional development, institutional support, perceived barriers, and teacher-facing and student-facing AI use. Teachers reported moderate overall AI readiness, with ethical readiness receiving the highest ratings and practical ability the lowest. Although 68.6% of participants reported using AI for professional or instructional purposes, only 41.8% had received formal AI-related professional development. Teachers identified substantial professional development needs, particularly in evaluating AI-generated information, protecting student privacy, identifying bias, assessing AI-generated student work, and establishing appropriate expectations for student AI use. AI readiness was positively associated with classroom AI integration, and readiness emerged as the strongest predictor of integration after accounting for professional development, institutional support, barriers, teaching experience, and instructional level. Institutional support and previous AI-related professional development were also positively associated with classroom integration. The findings suggest that effective AI integration depends not only on access to emerging technologies but also on teachers' practical competence, sustained professional learning, and supportive institutional conditions. Schools, districts, and teacher preparation programs should therefore prioritize comprehensive AI professional development that integrates technological knowledge, pedagogy, ethical judgment, and responsible classroom application.
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