Using online learner trace data to understand the cohesion of teams in higher education

Abstract

BackgroundMaintaining cohesion is critical for teams to achieve shared goals and performance outcomes within a work‐integrated learning (WIL) environment. Cohesion is an emergent state that develops over time, representing the synchrony of different behavioural interactions. Cohesive teams will exhibit such phenomena by their temporal coordination of micro‐level relations.ObjectivesThe primary aim of this study is to examine the cohesion of teams in learning environments using a learning analytics approach.MethodThis study examines teams from higher education who participate in a WIL environment platform working in teams to develop their collaborative problem‐solving skills. Here we show that temporal network motifs can be used as a proxy to measure cohesion.Results and ConclusionsWe illustrate three clusters represented by team learning behaviours and found that each cluster has distinctive interactions with learning resources, performance outcomes, temporal network motif group characteristics and emergence over time using learning analytics.ImplicationsApplying temporal motifs as an analytics‐based measure of cohesion is a starting point for understanding how cohesion develops over time without relying on surveys. We anticipate that the same approaches can be applied in most learning management systems containing trace data of teams and their interactions with learning resources to understand cohesion.