Bridging the Global Teacher Support Gap: A Conceptual Model for AI-Augmented Job-Embedded Professional Development

Introduction
Teacher professional development is widely recognized as a critical driver of instructional improvement and educational reform. However, persistent gaps remain between international policy aspirations and classroom-level implementation, particularly where job-embedded professional development (JEPD) relies heavily on human-intensive coaching. Prior research has identified time constraints, administrative burden, and limited access to sustained support as key barriers to teacher growth and retention. This study introduces the S.C.A.L.E. Framework, a conceptual model designed to support scalable, AI-augmented JEPD by centering educator agency and sustainability.

Methods
This conceptual study synthesizes findings from a prior qualitative case study (N = 7) examining site-based instructional coaching with a targeted review of recent literature on generative artificial intelligence in education published between 2023 and 2025. The framework is theoretically grounded in Knowles’ Adult Learning Theory and Mezirow’s Transformational Learning Theory. Conceptual mapping aligned core principles of job-embedded learning with emerging AI-enabled workflows, aiming to address limitations of personnel-dependent professional development models.

Results
The S.C.A.L.E. Framework (Support, Contextualize, Augment, Literacy, and Evaluate) conceptually addresses sustainability challenges in teacher professional development by positioning AI as a reflective and adaptive partner rather than a standalone tool. The model illustrates how AI-supported processes may offload routine reflective and administrative tasks, allowing human mentors to focus on higher-order instructional dialogue and transformational learning experiences. Conceptual analysis suggests the framework has the potential to enhance continuity, accessibility, and consistency of professional learning across diverse contexts.

Conclusions
The S.C.A.L.E. Framework offers a theoretically grounded, future-oriented approach to reimagining job-embedded professional development. By integrating established adult learning and transformational theories with AI-enabled support structures, the model provides a scalable architecture for sustained teacher development. It contributes to ongoing discussions on leveraging artificial intelligence to support meaningful, equitable, and sustainable professional learning globally.