Who will participate in online collaborative problem solving? A longitudinal network analysis

ABSTRACT

Community-based courses, driven by connectivist learning theory, provide learners with a social environment that supports collaborative problem solving (CPS). The purpose of this study is to investigate the characteristics of potential collaborators before they engage in CPS. This study analyzed a community-based course, a cMOOC with a total of 145 learners participated in the thematic learning stage and 52 of the 145 chose to participate in the CPS. The interaction pattern of the collaborators and the indirect effects of individual attribute-based (exogenous) effects and network structure-based (endogenous) effects on the interaction pattern were examined using the quadratic assignment procedure (QAP) and the stochastic actor-oriented model (SAOM). Results suggest that substantial interaction activeness and interaction attractiveness are key patterns of the collaborators’ social interactions before CPS, and there is some interaction homogeneity among the collaborators. Some individual attribute-based effects, such as age, gender, and occupation, will reduce the early interaction attractiveness of the collaborators. The reciprocity, transitivity, and cumulative advantages of the network structure-based effects will gradually increase collaborators’ interaction attractiveness; in contrast, the network structure-based effects simultaneously limit collaborators’ interaction activeness. This study provides a theoretical foundation and practical experience regarding encouraging learners’ deep collaboration in community-based courses.

KEYWORDS:

• Massive Open Online Course
• connectivism
• collaborative problem solving
• group formation
• SAOM
• QAP

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number 62207003]; Research Project of Huiyan International College, Faculty of Education, Beijing Normal University [grant number 2023HICR0004].

Notes on contributors

Cixiao Wang

Cixiao Wang is a lecture at the Research Center of Distance Education in Beijing Normal University. Her research interests include online learning, CSCL, and embodied learning.

Jianjun Xiao

Jianjun Xiao is a postgraduate student at the Research Center of Distance Education at Beijing Normal University. His research interests include e-learning, interaction, and social network.