Logo image
Productive disciplinary engagement in high- and low-outcome student groups: Observations from three collaborative science learning contexts
Journal article   Open access   Peer reviewed

Productive disciplinary engagement in high- and low-outcome student groups: Observations from three collaborative science learning contexts

M.D. Koretsky, M. Vauras, C. Jones, T. Iiskala and S. Volet
Research in Science Education, Vol.51, pp.159-182
2019
pdf
Learning Contexts.pdfDownloadView
CC BY V4.0 Open Access
url
Free to Read *No subscription requiredView

Abstract

This study explored how productive disciplinary engagement (PDE) is associated with the level of cognitive activity and collective group outcome in collaborative learning across multiple contexts. Traditionally, PDE has been studied in a single collaborative learning environment, without analysis of how these environments fulfill the supporting conditions for PDE. In addition, research on the quality of a collective learning outcome and product in relation to the extent of the group’s PDE during actual collaborative learning processes is scarce. In this study, the learning processes of low- and high-outcome small groups were compared within three collaborative learning contexts: high school general science, second year university veterinary science, and fourth year university engineering. Two meaningful and self-contained phases from each context were selected for analysis. The same theory-based analytical methods were used across contexts. The findings revealed similar patterns in the high school science and second year university veterinary science data sets, where high-outcome groups displayed a greater proportion of high-level cognitive activity while working on the task. Thus, they could be distinctively perceived as high- and low-performing groups. These high-performing groups’ interactions also reflected more of the supporting conditions associated with PDE than the low-performing groups. An opposite pattern was found in the fourth year university engineering data set, calling for interpretation grounded in the literature on the nature and development of expertise. This study reveals the criticality of using comparable analytical methods across different contexts to enable discrepancies to emerge, thus refining our contextualized understanding of PDE in collaborative science learning

Details

UN Sustainable Development Goals (SDGs)

This output has contributed to the advancement of the following goals:

#4 Quality Education

Source: InCites

Metrics

64 File views/ downloads
62 Record Views

InCites Highlights

These are selected metrics from InCites Benchmarking & Analytics tool, related to this output

Collaboration types
Domestic collaboration
International collaboration
Citation topics
6 Social Sciences
6.11 Education & Educational Research
6.11.295 Science Education
Web Of Science research areas
Education & Educational Research
ESI research areas
Social Sciences, general
Logo image