Social learning analytics (SLA) tools are designed to visually demonstrate online discussions with a goal to foster student engagement. However, empirical studies indicate controversial results of the effect of SLA tools on student engagement. This design-based research designs a student-facing SLA tool to demonstrate discussions from three perspectives and further uses mixed methods to investigate the effects of the tool. Results indicate the tools have positive influences on increasing student social-cognitive engagement. The social network visualization has positive influences on both socially active and inactive students; it particularly increases peripheral students' social engagement. The topic network visualization improves all students' perspective expressions, indicating that demonstrating students' interested topics may increase cognitive engagement. The cognitive network visualization triggers students' information sharing, which is considered as the beginning of online engagement development. Based on the results, this research proposes integrated implications by considering learning theory, pedagogical supports and tool development.
More and more social Q&A platforms are launching new business models to monetize online knowledge. Many users of the traditional free Q&A are gradually adopting the payment‐based Q&A services. Previous studies have focused more on askers' participation behaviors in the free Q&A context, while few of them explored the switching behavior of askers from free‐ to payment‐based Q&A platforms. Based on the push‐pull‐mooring (PPM) model, this paper aims at exploring the influencing factors of askers' switching behavior using the critical incident technique. The classification scheme of the factors that influence the askers' switching behaviors includes 5 categories and 16 subcategories. We also use the entropy‐weight method to calculate the weight of each factor. The findings suggest that the psychological characteristics, cognitive needs, and financial incentives have great impacts on askers' switching behavior in the Q&A context.
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