Community detection with opinion leaders’ identification for promoting collaborative problem‐based learning performance

Abstract

In the 21st century when knowledge‐based economy is emphasized, the cultivation of autonomous learning and problem‐solving abilities presents the importance. With web‐based collaborative problem‐based learning (CPBL), learners could more conveniently cultivate their problem‐solving abilities through autonomous learning. Nevertheless, learners are often guided to solve a target problem by the information announced by teachers during the CPBL processes. Individual learners often could not effectively absorb such standard information, thus ignoring the important information from teachers. In the information communication theory, the two‐step flow of communication through opinion leaders has been proved that it can better change audiences’ attitudes than the one‐step flow of communication through mass media. This study thus employs the modularity Q function as the fitness function of genetic algorithm to optimally detect learning communities and uses PageRank measure to accurately find out community opinion leaders according to the social network interaction data of learners in the CPBL process. Based on quasi‐experimental design, this study examines whether learners in the experimental group using the two‐step flow of communication through opinion leaders to convey information for solving the target CPBL missions could more significantly enhance web‐based CPBL performance, social network interaction and group cohesion than learners in the control group using the one‐step flow of communication through teachers’ information. Analytical results show learners in the experimental group remarkably outperform those in the control group on learning performance and peer interaction under a CPBL environment. Particularly, female learners in the experimental group notably outperform female learners in the control group on learning performance, while there is no significant difference in male learners between both groups. More importantly, learners in the experimental group present significantly higher group cohesion than those in the control group. This study confirms that using the two‐step flow of communication instead of the one‐step flow of communication traditionally used in web‐based learning environments could significantly promote web‐based CPBL performance, social network interaction and group cohesion.

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