From individual digital skills to collective governance capability: A systemic team-based learning model in local government

This study develops and empirically examines a systemic team-based learning (TBL) model for strengthening digital competence among civil servants and supporting smart governance implementation in local government organizations. Grounded in soft systems methodology (SSM) (Checkland, 1981) as a framework for managing unstructured public-sector problems, a mixed-methods design was applied to 500 civil servants from three Indonesian local governments, using pre- and post-intervention DigComp 2.2-based assessments alongside qualitative interviews. The intervention produced statistically significant improvements across all digital competence domains (p < 0.001) with large effect sizes, particularly in communication, collaboration, and problem-solving. This study provides a distinct theoretical contribution by operating at the intersection of digital government literature (Dunleavy et al., 2006) and organizational learning theory (Senge, 2006). It explicitly demonstrates a conceptual shift from individual digital skills to a collective, relational governance capability. By utilizing Michaelsen’s TBL principles as an active-learning mechanism within a systemic smart governance framework (Gil-Garcia et al., 2016), the study reveals how structured, team-level dynamics bridge personal proficiency and organizational capacity, offering a scalable framework to overcome human capital bottlenecks in public sector digital transformation.