Information Exchange in a Group Mapping Activity: A Comparative Mixed Methods Case Study of Jigsaw and Traditional Learning
Restricted (Penn State Only)
- Author:
- Yu, Junxiu
- Graduate Program:
- Learning, Design, and Technology (PHD)
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- February 21, 2023
- Committee Members:
- Gabriela Richard, Major Field Member
Craig Campbell, Outside Field Member
Ravinder Koul, Outside Unit Member
Roy Clariana, Chair & Dissertation Advisor
Susan Land, Program Head/Chair - Keywords:
- group learning
jigsaw learning
information exchange
concept map - Abstract:
- Designing and implementing group learning has been challenging in different educational contexts. For example, past literature has reported that group members usually do not effectively exchange information, especially in jigsaw learning activities. To deepen our understanding of this phenomenon, the current study implemented a concept map-enhanced jigsaw activity to investigate the information exchange processes and its learning outcomes. A concept map is a diagram that visually represents relationships between concepts. Each concept is represented as a node, and a link connects two concepts. A comparative mixed methods case study was adopted to compare jigsaw groups and control groups. In the jigsaw condition, a chapter was divided into several parts and each participant was assigned to read a different part. In the traditional condition, each participant read the full chapter. Each participant then was asked to create a pre-map of their assigned part. Two weeks later, each group met online and created a group concept map together using the CmapTools software to represent the whole chapter. Finally, each participant responded to a survey to list the key concepts of the whole chapter. To compare group performance, a t-test of NodeXL elicited metrics was conducted between the traditional group maps (n = 6) and the jigsaw group maps (n = 9). To compare individual performance, a MANOVA test was conducted between participants’ survey responses from the traditional groups (n = 18) and the jigsaw groups (n = 17). Regarding the information exchange processes, 19.63 hours of video recordings of the group mapping activities were transcribed and analyzed using thematic analysis in NVivo. The results showed that there were striking differences between the two conditions in group performance. Compared to the traditional groups (m = 29.50 minutes), the jigsaw groups spent more time (m = 58.56 minutes) on map-making. Their maps were larger (i.e., more nodes and links) but relatively more sparse networks. Jigsaw group maps on average have 78.56 nodes and 82.78 links. Traditional group maps on average have 47.50 nodes and 49.67 links. Regarding individual performance, there were no significant differences in individuals’ recalled nodes between the traditional and jigsaw groups. Examining the group mapping processes showed that the jigsaw groups did not frequently exchange information. Furthermore, the information exchange episodes were not in-depth. Additionally, the groups were found to use the pre-maps, the textbook, and the CmapTools software to assist their information exchange. Besides, time and task requirement were found to have impacts on information exchange as well. The findings are in alignment with existing jigsaw group studies and information exchange studies. The current investigation also proposed intellectual authority as another possible explanation for the results. Lastly, the current investigation pointed out several areas to improve the concept mapping activity, including an advanced CmapTools training, a technical issue-free collaboration environment, and more-guided instructions. Some future directions to investigate concept map-enhanced hidden profile settings were provided as well, such as the impact of directions regarding the number of nodes of a concept map, the role that map-controller plays in the information exchange processes, the influences of text types on jigsaw learning outcomes, and using graph centrality to measure group maps.