Measuring students’ self-regulated learning in professional education: bridging the gap between event and aptitude measurements

Self-regulated learning has benefits for students’ academic performance in school, but also for expertise development during their professional career. This study examined the validity of an instrument to measure student teachers’ regulation of their learning to teach across multiple and different kinds of learning events in the context of a postgraduate professional teacher education programme. Based on an analysis of the literature, we developed a log with structured questions that could be used as a multiple-event instrument to determine the quality of student teachers’ regulation of learning by combining data from multiple learning experiences. The findings showed that this structured version of the instrument measured student teachers’ regulation of their learning in a valid and reliable way. Furthermore, with the aid of the Structured Learning Report individual differences in student teachers’ regulation of learning could be discerned. Together the findings indicate that a multiple-event instrument can be used to measure regulation of learning in multiple contexts for various learning experiences at the same time, without the necessity of relying on students’ ability to rate themselves across all these different experiences. In this way, this instrument can make an important contribution to bridging the gap between two dominant approaches to measure SRL, the traditional aptitude and event measurement approach

Using sensor technology to capture the structure and content of team interactions in medical emergency teams during stressful moments

In healthcare, action teams are carrying out complex medical procedures in intense and unpredictable situations to save lives. Previous research has shown that efficient communication, high-quality coordination, and coping with stress are particularly essential for high performance. However, precisely and objectively capturing these team interactions during stressful moments remains a challenge. In this study, we used a multimodal design to capture the structure and content of team interactions of medical teams at moments of high arousal during a simulated crisis situation. Sociometric badges were used to measure the structure of team interactions, including speaking time, overlapping speech and conversational imbalance. Video coding was used to reveal the content of the team interactions. Furthermore, the Empatica E4 was used to unobtrusively measure the team leader’s skin conductance to identify moments of high arousal. In total, 21 four-person teamsof technical medicine students in the Netherlands were monitored in a simulation environment while they diagnosed and managed a patient with cardiac arrest. Outcomes of this exploratory study revealed that more effective teams showed greater conversational imbalance than less effective teams, but during moments of high arousal the opposite was found. Also, a number of differences were found for the content of team interaction. Combining sensor technology with traditional measures can enhance our understanding of the complex interaction processes underlying effective team performance, but technological advances together with more knowledge about the simultaneous application of these methods are needed to tap into the full potential of wearable sensor technology in team research