Empowering STEAM Educators through AI: A Conceptual Framework for Adaptive, Inclusive Professional Development - Radvila, Vytis; Bredelytė, Aelita; Lekutienė, Kristina (Social Welfare: Interdisciplinary Approach, 2025)
The growing demand for interdisciplinary Science, Technology, Engineering, Arts, and Mathematics (STEAM) education has placed increasing pressure on secondary education teachers to develop integrative, technology-enhanced pedagogical competencies. However, conventional models of professional development (PD) often fall short in addressing the complex, practice-based learning needs required for effective STEAM instruction. This conceptual study explores the potential of Artificial Intelligence (AI) to transform teacher PD by synthesizing recent high-impact literature (2018–2025) across the fields of educational technology, learning sciences, and AI ethics. Four thematic strands are identified: personalization of learning, enhancement of Technological Pedagogical Content Knowledge (TPACK), support for collaboration and reflection, and challenges related to ethics, equity, and teacher readiness. In response, the paper proposes the Adaptive AI-STEAM PD Cycle (A²SPDC) – a six-phase framework that integrates AI-driven assessment, personalized pathways, practice environments, feedback, peer collaboration, and reflective analytics. The framework aims to promote context-sensitive, teacher-centered, and ethically responsible professional learning. While conceptual in nature, this work contributes a theoretically grounded model to guiding future empirical research and policy design, with the broader goal of supporting equitable, innovative, and socially responsive teacher development in STEAM education.
Keywords: Artificial intelligence; Teacher professional development; STEAM education; TPACK; Educational equity; Design-based research