Using Online Learner Trace Data to Understand the Cohesion of Teams in Higher Education

Autor/inn/en	Zamecnik, Andrew; Kovanovíc, Vitomir; Joksimovíc, Srécko; Grossmann, Georg; Ladjal, Djazia; Marshall, Ruth; Pardo, Abelardo
Titel	Using Online Learner Trace Data to Understand the Cohesion of Teams in Higher Education
Quelle	In: Journal of Computer Assisted Learning, 39 (2023) 6, S.1733-1750 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Zamecnik, Andrew) ORCID (Kovanovíc, Vitomir) ORCID (Joksimovíc, Srécko) ORCID (Marshall, Ruth)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0266-4909
DOI	10.1111/jcal.12829
Schlagwörter	Data Use; Group Dynamics; College Students; Cooperative Learning; Experiential Learning; Learning Analytics; Problem Solving; Electronic Learning + Suchen Sie Ihr Suchwort? Gruppendynamik; Collegestudent; Kooperatives Lernen; Experiental learning; Erfahrungsorientiertes Lernen; Problemlösen
Abstract	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. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01