An Evidence-Informed Adaptive Model for Improving University Educators’ Digital Professional Practice

This article proposes an evidence-informed adaptive model for improving university educators’ professional practice in digitally mediated teaching. Drawing on DigCompEdu, TPACK, UNESCO guidance on artificial intelligence and design-based educational inquiry, it defines five competence domains and links them to observable teaching artefacts. The proposed cycle covers diagnosis, contextual interpretation, co-designed professional learning, implementation and reassessment. An engineering-computer-graphics scenario illustrates its practical relevance, while an evaluation protocol specifies how future research could test its validity, feasibility and outcomes. As the available materials lack auditable experimental datasets, no causal or numerical effectiveness claims are advanced. The contribution is an integrated framework for formative development under human oversight and responsible data governance