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This paper presents work-in-progress on the Social Semantic Server, an open framework providing applications and their users with a growing set of services of different granularity that utilize social and ar-tifact network data. The Social Semantic Server forms a novel approach to store, query and update semantically enriched social data in order to exploit(More)
While several technological advances have been suggested to scale learning at the workplace, none has been successful to scale informal learning. We review three theoretical discourses and suggest an integrated systems model of scaffolding informal workplace learning that has been created to tackle this challenge. We derive research questions that emerge(More)
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Informal learning at the workplace includes a multitude of processes. Respective activities can be categorized into multiple perspectives on informal learning, such as reflection, sensemaking, help seeking and maturing of collective knowledge. Each perspective raises requirements with respect to the technical support, this is why an integrated solution(More)
The co-evolution model of collaborative knowledge building by Cress & Kimmerle (2008) assumes that cognitive and social processes interact when users build knowledge with shared digital artifacts. While these assumptions have been tested in various lab experiments, a test under natural field conditions in educational settings has not been conducted. Here,(More)
This dissertation will elaborate on the understanding of in-tersubjective meaning making by analyzing the traces of collaborative knowledge construction users leave behind in socio-technical systems. Therefore, it will draw upon more theoretical and more formal models of cognitive psychology to describe and explain the underlying process in detail. This is(More)
In this position paper, we argue that the different disciplines in Web Science do not work together in an interdisciplinary way. We attribute this to a fundamental difference in approaching research between social scientists and computer scientists, which we call the patterns vs. model problem. We reason that interdisciplinary teamwork is needed to overcome(More)