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

Background: Maintaining 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. Objectives: The primary aim of this study is to examine the cohesion of teams in learning environments using a learning analytics approach. Method: This 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 Conclusions: We 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. Implications: Applying 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. Lay Description: What is already known about this topic?: The development of team cohesion has been widely studied for decades in face‐to‐face educational contexts but remains underexplored in online environmentsObtrusive tools, such as questionnaire instruments are still the primary method used to examine team cohesionTeam cohesion is an emergent state that changes over time, representing the synchrony of different behavioural interactionsResearch that explores and examines the temporality of cohesion as it unfolds in team learning is limited What this paper adds?: Underlines how emerging team behaviours are characterised by their engagement, performance and cohesion development using temporal network motifsPresents an analytics‐based measure to examine cohesion using temporal network motifs as a proxyProvides a learning analytics approach for researchers and instructors to evaluate cohesion in online learning environments through online learner trace data The implications of study findings for practitioners: The paper provides insights into distinct teams with emerging learning behaviours, performance associations and cohesion in an online learning platform.The paper provides instructors with a way to monitor and support a team's cohesion over time by examining the way temporal motifs occur.The paper offers a new avenue to understanding learner engagement beyond summarisations [ABSTRACT FROM AUTHOR]