A DARIAH Working Group on combining language learning with crowdsourcing techniques
The DARIAH Working Group Combining Language Learning with Crowdsourcing Techniques (D4COLLECT) is aimed at exploring research and innovation trends in the use of crowdsourcing techniques in the domain of language learning, while at the same time opening paths to crowdsource NLP datasets from language learning activities. This means that on the production side, R&I players who are working on language-related topics and have laborious and complex tasks that can be approached by crowdsourcing are prospective members of D4COLLECT no matter if they are directly interested in language learning or rather in the crowdsourcing workforce it can unleash through its learners and teachers.
D4COLLECT is meant to sustain and move forward the outcomes of the COST Action enetCollect and to serve as a flexible and dynamic bottom-up institutional framework for knowledge exchange, research coordination and capacity building beyond the end of the COST Action.
D4COLLECT aims to bring together language teachers and experts in linguistics, computational linguistics, educational sciences, software engineering and digital humanities to explore digital workflows, tools, and solutions for deploying implicit and explicit crowdsourcing methods in the creation of language-learning materials and the collection of language datasets.