Digital Profiling for Assessing Implicit Competencies in Holistic Pre-service Teacher Education

Abstract

Global changes in education call for a shift from mechanistic knowledge transmission to a more holistic model of teacher development. However, a persistent gap remains in traditional pre-service teacher (PST) education, which often emphasizes explicit pedagogical skills while paying insufficient attention to essential implicit competencies. This study addresses this issue by examining the application of digital profiling technology in PST education. Through a structured interdisciplinary literature review and framework synthesis, it explores how multi-modal data collection, emotion recognition, and behavioral analytics can be used to identify and assess non-cognitive dimensions such as emotional intelligence, empathy, and professional ethics. The analysis indicates that digital profiling can support personalized development pathways, targeted cultivation of emotional competencies, and evidence-based reflective feedback in diverse pedagogical contexts. Overall, the study argues that digital profiling offers a feasible pathway for strengthening holistic teacher preparation and supporting the development of implicit competencies in contemporary pre-service teacher education.