Collaborative learning in management subjects to university students: A multi-level research to identify group profile, engagement and academic performance
Our research has consisted of a multilevel analysis of work groups within the framework of collaborative learning methodology through the Computer-Supported Collaborative Learning (CSCL) approach with respect to students who operate through a non-CSCL approach as a group of students control. The obj...
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Veröffentlicht in: | The international journal of management education 2023-03, Vol.21 (1), p.100762, Article 100762 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Our research has consisted of a multilevel analysis of work groups within the framework of collaborative learning methodology through the Computer-Supported Collaborative Learning (CSCL) approach with respect to students who operate through a non-CSCL approach as a group of students control. The objective, in addition to examining to what extent the CSCL approach is more beneficial for academic performance, has been to identify the individual and group characteristics associated with work groups through the behavior of a set of variables. The research uses academic results obtained from a sample of 367 university students. The factors that most strongly contribute to reactive-positive behavior within the analyzed group profiles are the use of the CSCL approach, a higher average age of the group, a higher level of university experience, and a high level of qualification to access the degree required by the university.
•Collaborative learning contributes significantly to proactive group learning.•The profile and individual and group characteristics within the framework of the collaborative learning methodology represents an important nucleus of research.•The profile and motivation of the working groups within the framework of the methodology contributes positively and negatively to the results achieved by the working groups.•Collaborative learning can significantly contribute to improving academic performance. |
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ISSN: | 1472-8117 |
DOI: | 10.1016/j.ijme.2022.100762 |