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

• DOI: 10.1080/10494820.2023.2266523
• Publication Date: 2023-10-09T12:06:06Z
• Authors: Cixiao Wang; Jianjun Xiao
• Keywords: Reciprocity; Thematic Analysis; Social Network Analysis

ABSTRACTCommunity-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 potential collaborators before they engage in CPS. This analyzed community-based course, cMOOC total 145 participated thematic stage and 52 chose participate interaction pattern indirect effects individual attribute-based (exogenous) network structure-based (endogenous) on were examined using quadratic assignment procedure (QAP) stochastic actor-oriented model (SAOM). Results suggest substantial activeness attractiveness are key patterns collaborators’ interactions CPS, there some homogeneity among collaborators. Some effects, such as age, gender, occupation, will reduce early reciprocity, transitivity, cumulative advantages gradually increase attractiveness; contrast, simultaneously limit activeness. provides theoretical foundation practical experience regarding encouraging learners’ deep collaboration courses.KEYWORDS: Massive Open Online Courseconnectivismcollaborative solvinggroup formationSAOMQAP Disclosure statementNo conflict interest was reported author(s).Data availability statementThe data support findings available from corresponding author upon reasonable request.Additional informationFundingThis work supported National Natural Science Foundation China [grant number 62207003]; Research Project Huiyan International College, Faculty Education, Beijing Normal University 2023HICR0004].Notes contributorsCixiao WangCixiao Wang lecture at Center Distance Education University. Her research interests include online learning, CSCL, embodied learning.Jianjun XiaoJianjun Xiao postgraduate student His e-learning, interaction, network.