This study aims to unpack reflective inquiry in professional learning networks (PLNs) by exploring how its three dimensions – collective dialogue, integrating multiple data sources, and reflection with internal attribution – occur and interrelate, and by examining which factors influence reflective inquiry in PLNs.
Data were collected through recording 19 PLN sessions across three networks. A total of 30 h of interactions between educators from different schools were selected (N = 5,579 speaker turns). Contributions were coded for collective dialogue (C), use of data sources (D), and depth of reflection (R), each along three levels. Statistical associations between C, D, and R were analyzed using chi-square tests and a multilevel logistic regression model. Occurrence and conversational sequences were examined through Markov chain analysis. To gain deeper insight into the influencing factors of high-level reflective inquiry contributions, thematic coding was used.
The analysis showed that collective dialogue, data use, and depth of reflection were significantly interconnected, with higher levels of data use strongly associated with deeper levels of reflection. Role-adjusted analyses showed that facilitators had higher odds of higher-level reflection than participants. Higher-level reflective inquiry rarely emerged spontaneously among participants and was difficult to sustain across conversational turns, with discussions often shifting back toward lower-level reflective patterns. The findings underscore the need to build trust, develop individual capacity, and use structured protocols that prompt data use and critical challenge.
This study contributes to conceptual clarity by showing how the dimensions of reflective inquiry unfold and interact in practice within professional learning networks. It also provides insight into the conversational dynamics of reflective inquiry by demonstrating the central role of facilitators in modeling higher-level reflection and the difficulty of sustaining higher-level reflective inquiry across conversational turns.
