EnetCollect was organised around five WGS:
Whereas WG1 and WG2 focused on the combination of Language Learning with explicit and implicit Crowdsourcing techniques, WG3 focused on the user-orientation of an online language learning solution to ensure its capacity to attract and retain a crowd, WG4 focused on technical specifications to support the functional demands of Language Learning and Crowdsourcing approaches and WG5 focused on ethical questions, legal regulations and business opportunities that such a combination between Language Learning and Crowdsourcing can imply.
WG1 and WG2 thus tackled the main research subject of the action, the combination of Language Learning and Crowdsourcing, whereas WG3, WG4 and WG5 support them by researching the context necessary for such combination to be implemented in practice. Even though, the efforts of WG3, WG4 and WG5 would first and foremost target the objectives the Action, It was also expected that their findings would be of interest beyond the scope of enetCollect. For example, researching what makes a Language Learning platform attractive was a task tackled by WG3 and the resulting findings would be of interest for any Language Learning platform, including the one that have no interest in Crowdsourcing.
For an explanation about what was intended between Implicit and Explicit Crowdsourcing, click here.