Applying Language Technologies to Support Work-Integrated Learning

One key challenge for supporting work-integrated learning (WIL) involves the repurposing of existing knowledge resources (both textual and multimedia) from the organizational memory for automatically creating learning content. Since WIL is highly contextualized to the work tasks as well as to the competences of the knowledge worker in question, manual learning content creation is not feasible here. We present a knowledge artefact lifecycle which starts with the identification of knowledge resources, involves their semantic annotation and contextualized delivery, and concludes with their presentation to users and the consideration of user feedback. We have employed a suite of language and semantic technologies to automate many of the lifecycle steps in order to reduce efforts when instantiating a WIL support environment for a specific application domain. A summative evaluation of the WIL environment has shown that contextualized recommendation of knowledge artefacts can improve task performance and enables learners to advance their competences during work.