Crowdlearning: An incentive-based learning platform for crowd

Abstract

Crowdlearning is an incentive-based learning platform for crowd, denoted as iCL, to inspire experts for knowledge sharing and to incentivize them for their contributions in crowd. In iCL, collaborators provide learning platform to the crowd of interested learners. The relativeness of interest of contributors and learners is compared by match-making process. The core objective of iCL is to motivate learners to join common-interest crowd and to collaboratively perform Crowdlearning activities. Moreover, incentivization motivates learners to grow crowd. The main contributions of iCL are three-fold. First, it presents the architecture of iCL with the crowd formation process that includes the processes of initialization and collaboration. Second, it proposes three incentive-based fees distribution schemes defined as Equally Distributed Incentive (EDI), Level-based EDI (LEDI) and Commission-oriented LEDI (CLEDI). Third, our performance evaluation shows that our schemes are indeed effective to motivate learners for participation and to inspire experts for their contribution through incentivization in crowdlearning.