KNOWLEDGE STOCK EXCHANGES: A CO-OPETITIVE CROWDSOURCING MECHANISM FOR E-LEARNING
作者： Martin Spann , Andreas Heusler
DOI:
关键词: Computer science 、 Competitive learning 、 Crowdsourcing 、 Knowledge community 、 Collective intelligence 、 Higher education 、 Stock exchange 、 Interactivity 、 Information and Communications Technology 、 Knowledge management
摘要: Modern information and communication technologies (ICT) provide numerous opportunities to support e-learning in higher education. Recent devlopments such as Massive Open Online Courses (MOOCs) utilize the scalabiltiy interactivity of ICT broaden accessibility university However, potential enhancing students’ learning experience success is far from being fully utilized. One area for development new mechanisms at intersection collective intellegence crowdsourcing mechanisms: The knowledge-disseminating ability a intelligence platform combined with participative nature knowledge fellow students may enhance motiviation acceptance learning. Following crowd-based approach we present prototype that offers highly collaborative competitive environment improve mutual exchange well encourage community. Our draws upon principle virtual stock markets (also “prediction markets”), well-known mechanism which enhanced elements. We describe proposed system architecture, evaluate practical feasibility our field implications future research.
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