This evidence was extracted from a paper coming from the 15th International Conference on Knowledge Technologies and Data-driven Business (i-KNOW 2015), held in Graz (Austria) last 21st – 22nd October 2015.
In this paper, authors describe a framework, named Social Semantic Server (SSS), that can constitute a flexible tool for the support of informal learning in different workplace scenarios.
The development of this tool is based on the assumption that “individual knowledge is constructed through collaborative knowledge building […][and that] a knowledge base is co-constructed by a community of learners as a result of their activities mediated by shared artefacts”. This implies that learners community can be considered as a Distributed Cognitive System, and that the process of meaning construction in this environment can be defined as “Meaning Making”.
SSS was developed considering several Design Principles, and among them several learning KPIs can be found, such as tracking of physical, time, social and semantic context of user-artefact and user-user interactions or tracking of history of network interactions. This network, thanks to Learning Analytics, can represent a good source of understanding what kind of information the users are searching for and new trends in the Meaning Making process.
In the second part of the conference paper, several services of SSS were described, namely metadata degrees of formality, tracking of users interaction, search engine, recommendations tool, knowledge structures, Q&A environment, access restrictions and collections and aggregation of learning inputs inside the framework.
The last part of the paper was dedicated to three case studies, which depict how SSS can represent a flexible tool for the generation of informal learning environments at the workplace. Three different IT tool were generated based on some of the SSS services described above, for the informal learning of healthcare professionals (Bits & Pieces), academic researchers (KnowBrain, currently under development) and future teachers training (Attacher). During these case studies, the context of the collected, generated or modified resources were tracked and analysed through dedicated KPIs, which were author, time of collection and the set of attached tags for Attacher, while for B&P and KnowBrain also categories, ratings and discussions were available. As indicated in the paper, “This contextual characteristics can be exploited to create networks of actors and artefacts, as well as to make Learning Analytics”.