Collaborative analysis and reflection on knowledge practices is a central element of the Trialogical Learning Approach as it is supposed to be a driving force in processes of practice transformation and knowledge creation. The exploitation of historical logging data holds promise to provide a great deal of information about group activities without requiring additional efforts for recording of events by the users. Building on the Trialogical Learning Approach as well as related work in the fields of Data Mining and Knowledge Discovery, Computer-Supported Collaborative Learning, and Information Visualization, this paper suggests high-level requirements for analytic tools in support of practice transformation and introduces an application called Timeline-Based Analyzer (TLBA) that was designed and developed in response to these requirements. The usability of this solution has been tested through a first iteration of several practical experiments and case studies. One of them is described in this paper and illustrates how this tool can be used to support collaborative analysis and reflection. The results of these evaluations have been used for continued improvement of the TLBA in order to provide a stable and intuitive tool.
In this paper we propose a classification and systematic description structure based on the pattern paradigm for interaction scripts in Second Life that aim at facilitating knowledge sharing and knowledge integration in groups. We present eight examples of such interactions, a description structure to formalize them, and classify them into four classes according to their design scope and added value. Based on this classification we distinguish among sophisticated 3D collaboration patterns, seamless patterns, decorative patterns, and pseudo patterns.
Adapting E-Learning material allows re-using existing material even in changed usage scenarios. But this adaptation is a complex task. To achieve a perfect result expert knowledge is needed. Often adaptations have to be performed by persons who are not experts in performing these tasks. To enable those persons to achieve a satisfying result they need to be supported. Patterns are one possibility to make expert knowledge on certain tasks available to other persons. In this paper an approach is presented how expert knowledge of performing adaptations of existing E-Learning material can be collected and made available with patterns. This approach can also be used to collect knowledge of other processes, e.g. in companies.
Learning processes using New Media tend to be extremely complex. It is not too surprising then that current research appears rather scattered and dominated by the more tangible issues such as content and learning platform design in a bottom-up approach. While initially this appears practical, we are convinced that advanced learning platforms need to be designed to optimally support the underlying educational process based on learning theories (top-down approach). This paper proposes the Blended Learning Systems Structure (BLESS) model that introduces a layered architecture for decomposing the complexity inherent in the transition from courses to their effective support by learning technologies. In particular, BLESS is intended to act as a reusable framework for decomposing complex blended learning processes into smaller, more tangible and reusable learning activity patterns that may subsequently be used to guide blended course design and effective use of learning technology.