Visualising and examining sequential actions as behavioural paths that can be interpreted as markers of complex behavioursComputers in Human Behavior (2017)
Visualisation of pathways taken by students through problem solving environments provides the potential to identify patterns of exploratory behaviour that may relate to different levels of proficiency or different cognitive approaches. This is particularly the case when problems are situated in complex online environments and are programmed to generate large scale data for analysis.
Using process data from an online collaborative problem solving task, we visualised behavioural paths of 607 pairs of students as directed graphs. The empirical paths were then examined using exploratory network analysis based on four main aspects of exploration (prominence, branches, clusters, and shortest paths).
The primary purpose of such analysis is to detect sequences that are potentially relevant for establishing particular paths as meaningful markers of complex behaviours. This visualisation approach enabled us to capture all actual (as opposed to possible) pathways from the data. Although there may be an optimal pathway through a complex task according to criteria such as efficiency or correct solution, the added human factors bring a dynamic to the activity that provides a richer environment for understanding students’ collaborative processes, both cognitive and social. The method adopted in this study provides a prototype for exploration of other complex skillsets.
- Problem solving,
- Data analysis,
- Online assessment
Citation InformationAlvin Vista, Esther Care and Nafisa Awwal. "Visualising and examining sequential actions as behavioural paths that can be interpreted as markers of complex behaviours" Computers in Human Behavior (2017) ISSN: 0747-5632
Available at: http://works.bepress.com/alvin-vista/14/