The SSN is thereby instantiated from the Social Semantic Server (SSS). The main objective of WP5 is to develop a Social Semantic Network (SSN) that enables situated and contextualized learning to support scaling of informal workplace learning and meaning making, as well as scaffolding and peer production.
This report provides a summary of the work done in Year 3 in the Learning Layers project from the perspective of Work Package 5 (WP5). The evaluation results indicate that the SSS satisfactorily supports decision making in diverse workplace learning situations and allow us to reflect on the importance of knowledge creation theories for this analysis. We also show evidence for the usefulness of the SSS extracted from 4 authentic workplace learning situations involving 57 participants. This paper contributes by systematically deriving requirements for the SSS according to knowledge creation theories, and by offering support across a number of different learning tools and LA applications integrated into the SSS. Further, the SSS design’s flexibility enables it to be adapted to different workplace learning situations. The SSS collects data from workplace learning tools, integrates it into a common data model based on a semantically enriched artifact-actor network, and offers it back for LA applications to exploit the data. The design and development of the SSS have evolved over eight years, starting with an analysis of workplace learning inspired by knowledge creation theories and their application in different contexts. In this paper, we propose the Social Semantic Server (SSS) as a service-based infrastructure for workplace and professional learning analytics (LA). The focus on theory is generally a positive feature in WPLA, but we encourage a stronger focus on assessing the impact of WPLA in realistic settings. We found that WPLA is gaining momentum, especially in some fields, like healthcare and education. We also discuss the characteristics of workplace learning that make WPLA proposals different from LA in formal education contexts and the challenges resulting from this. Our in-depth analysis of 52 existing proposals not only provides a descriptive view of the field, but also reflects on researcher conceptions of learning and their influence on the design, analytics and technology choices made in this area. This paper summarizes the state of the art of Workplace Learning Analytics (WPLA), extracted from a two-iteration systematic literature review. This may be due to the focus on researching formal learning, as workplace learning is often informal, hard to grasp and not unequivocally defined. Despite the ubiquity of learning in workplace and professional settings, the learning analytics (LA) community has paid significant attention to such settings only recently.
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