Patterns of action transitions in online collaborative problem solving: A network analysis approach

Abstract

AbstractIn today’s digital society, computer-supported collaborative learning (CSCL) and collaborative problem solving (CPS) have received increasing attention. CPS studies have often emphasized outcomes such as skill levels of CPS, whereas the action transitions in the paths to solve the problems related to these outcomes have been scarcely studied. The patterns within action transitions are able to capture the mutual influence of actions conducted by pairs and demonstrate the productivity of students’ CPS. The purpose of the study presented in this paper is to examine Finnish sixth graders’ (N = 166) patterns of action transitions during CPS in a computer-based assessment environment in which the students worked in pairs. We also investigated the relation between patterns of action transitions and students’ social and cognitive skill levels related to CPS. The actions in the sequential processes of computer-based CPS tasks included using a mouse to drag objects and typing texts in chat windows. Applying social network analysis to the log file data generated from the assessment environment, we created transition networks using weighted directed networks (nodes for those actions conducted by paired students and directed links for the transitions between two actions when the first action is followed by the second action in sequence). To represent various patterns of action transitions in each transition network, we calculated the numbers of nodes (numbers of actions conducted), density (average frequency of transitions among actions), degree centralization (the dispersion of attempts given to different actions), reciprocity (the extent to which pairs revisit the previous one action immediately), and numbers of triadic patterns (numbers of different repeating formats within three actions). The results showed that pairs having at least one member with high social and high cognitive CPS skills conducted more actions and demonstrated a higher average frequency of action transitions with a higher tendency to conduct actions for different number of times, implying that they attempted more paths to solve the problem than the other pairs. This could be interpreted as the pairs having at least one student with high social and high cognitive CPS skills exhibiting more productive CPS than the other pairs. However, we did not find a significant difference across the pairs in terms of alternating sequences of two or three actions. Investigating the patterns of action transitions of the dyads in this study deepens our understanding of the mutual influence between the CPS actions occurring within dyads. Regarding pedagogical implication, our results offer empirical evidence recommending greater awareness of the students’ social and cognitive capacities in CPS when assigning them into pairs for computer-based CPS tasks. Further, this study contributes to the methodological development of process-oriented research in CSCL by integrating an analysis of action transition patterns with a skill-based assessment of CPS.