ShareMe: Running A Distributed Systems Lab For 600 Students With 3 Faculty Members

The goal of the Distributed Systems (DS) lab is to provide an attractive environment in which students learn about network programming and apply some fundamental concepts of distributed systems. In the last two years, students had to implement a fully functional peer-to-peer file sharing system called ShareMe. This paper presents the approach the authors used to provide the best possible support and guidance for the students whilst keeping up with ever-rising participant numbers in the lab course (approximately 600 last year) as well as managing budget and personnel constraints. The learning environment is based on Web- and Internet technologies and not only offers the description of the lab tasks, but also covers electronic submission, a discussion forum, automatic grading and online access to grading and test results. The authors report their experiences of using the automated grading system, the amount of work required to prepare and run the lab, and how they deal with students who submit plagiarized solutions. Furthermore, the results of student feedback and evaluation forms are presented and the overall student course satisfaction is discussed. Detailed information about the DS lab is available at www.dslab.tuwien.ac.at

KP-LAB Knowledge Practices Laboratory -- Specifications for the Knowledge Matchmaker (V.2.0), the Knowledge Synthesizer (V.1.0) and the Analytical and Knowledge Mining Services (V.1.0)

deliverablesThis deliverable presents specifications of three components responsible for advanced manipulation with the knowledge stored in the KP-Lab Semantic Web Knowledge Middleware (SWKM). It starts with motivating scenarios defined within various Working Knots (WKs), extracting relevant functional requirements and mapping them on the high-level requirements, of particular driving objectives and user tasks (described in deliverable [D2.4]). The first component is Knowledge Matchmaker (V2.0), which utilizes various text mining, information extraction, and heuristic methods for advanced access to and manipulation with shared knowledge artefacts according to the explicit meaning of artefacts expressed by their textual content, as well as metadata, including semantic tagging. This second version presents a set of completely new services supporting miscellaneous functionalities such as support for semantic tagging process, search for similar artefacts, information extraction capabilities, as well as recommendation services. Next two components are completely new. The Knowledge Synthesizer (V1.0) can be used to combine information found in multiple sources; this feature is necessary to allow automated merging of the conceptualizations modeled in independently edited conceptualizations. The Analytical and Knowledge Mining Services (V1.0) provide means for analyzing participation and activities within past or running knowledge creation processes, as well as for support of knowledge evolution analysis (e.g. via identification of critical patterns in selected knowledge creation processes)