CrowdLearn: Crowd-sourcing the Creation of Highly-structured E-Learning Content

Darya Tarasowa, Ali Khalili, Soeren Auer


While nowadays there is a plethora of Learning Content Management Systems, the collaborative, community-based creation of rich e-learning content is still not sufficiently well supported. Few attempts have been made to apply crowd-sourcing and wiki-approaches for the creation of e-learning content. However, the paradigm is only applied to unstructured, textual content and cannot be used in SCORM-compliant systems. To address this issue we developed the CrowdLearn concept to exploit the wisdom, creativity and productivity of the crowd for the creation of rich, deep-semantically structured e-learning content. The CrowdLearn concept combines the wiki style for collaborative content authoring with SCORM requirements for re-usability. Therefore, it enables splitting the learning material into Learning Objects (LOs) with an adjustable level of granularity. In order to realize the CrowdLearn concept, a novel data model called WikiApp is devised. The WikiApp data model is a refinement of the traditional entity-relationship data model with further emphasis on collaborative social activities and structured content authoring. We implement and evaluate the CrowdLearn approach with SlideWiki – an educational platform dealing with presentations and assessment tests. The article also comprises results of a usability evaluation with real students.


e-learning; LMS; crowdsourcing; (semi-)structured learning objects; SCORM

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International Journal of Engineering Pedagogy (iJEP) – eISSN: 2192-4880
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