Collaborative learning in economics: Do group characteristics matter?
Lenis Saweda O. Liverpool-Tasie,
Guigonan Serge Adjognon and
Aaron J. McKim
International Review of Economics Education, 2019, vol. 31, issue C, -
Abstract:
While the positive impacts of collaborative learning are well recognized, relatively little is known about how group characteristics (e.g., group size and composition) affect learning outcomes. Consequently, this article explores how group characteristics affect learning. We leverage a random assignment of students into groups of predetermined sizes to explore the effect of group size on learning outcomes in an undergraduate economics class. Though confirming the benefits of collaborative learning, our results indicate smaller group sizes (i.e., groups of about 5 or 6 members) are preferred to enhance learning, in our study context. We also find group learning effects tend to be limited for students with cultural and/or language barriers that limit participation. This is an important consideration for many US institutions with increasing enrollments of international students, particularly from Asian countries.
Keywords: Undergraduate teaching; Experiments; Cooperative learning; Group size (search for similar items in EconPapers)
JEL-codes: A22 C13 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1477388018301038
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ireced:v:31:y:2019:i:c:5
DOI: 10.1016/j.iree.2019.100159
Access Statistics for this article
International Review of Economics Education is currently edited by Guest, Ross
More articles in International Review of Economics Education from Elsevier
Bibliographic data for series maintained by Catherine Liu ().