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• W2223014329 abstract "Author Co-Citation Analysis (ACA) provides a principled way of analyzing research communities, based on how often authors are cited together in scientific publications. In this paper, we present preliminary results based on ACA to analyze and visualize research communities in the area of technology-enhanced learning, focusing on publicly available citation and conference information provided through CiteseerX and DBLP. We describe our approach to collecting, organizing and analyzing appropriate data, as well as the problems which have to be solved in this process. We also provide a thorough interpretation of the TEL research clusters obtained, which provide insights into these research communities. The results are promising, and show the method’s potential as regards mapping and visualizing TEL research communities, making researchers aware of the different research communities relevant for technology enhanced learning, and thus better able to bridge communities wherever needed. Introduction and Motivation Technology Enhanced Learning (TEL) is a fascinating field, with lots of different research questions and aspects to focus on. Researchers in TEL can focus on learning infrastructure to support the re-use of learning objects or personalization, on intelligent tutoring systems, on mobile learning, or on collaborative learning in teams. They can also focus on professional learning and knowledge management infrastructures, learning in universities (computer science, engineering or other disciplines) and on learning in schools, with a lot of interesting research questions and results. Many different conferences and journals are devoted to different aspects of technology enhanced learning, providing a variety of forums through which to publish TEL research results. The downside of this variety is, however, that TEL is a much more fragmented area than most other research areas, making it difficult to gain an overview of recent advances in the field. Even for experienced TEL researchers answering the questions: “What communities and sub-communities can be identified in TEL”, “what research topics/specialties can be identified in a field of studies” and “what conferences are the most relevant for what topic and for which community” is a difficult task, and for beginners it is obviously an impossible one. Being aware of this fragmentation and of the various sub-communities which make up the TEL area is an important pre-requisite towards overcoming this fragmentation, increasing synergies between different sub-areas and researchers, and, last but not least, providing funding agencies with evidence of new research results, innovative applications and promising new approaches for technology enhanced learning. This paper provides a first step towards this goal, by employing the technique of Author Co-citation Analysis (ACA) on the large subset of TEL conferences related to computer science as indexed by DBLP and CiteseerX the latter provides citation information for each indexed paper. ACA relies on the insight, that if two authors are cited together very often in scientific articles, their work must be related to the same research field. We will describe our methodology for data collection, solutions for problems that we encountered, and the techniques of author-co-citation and factor analysis for detecting communities in a given research area. We will 1 http://www.informatik.uni-trier.de/~ley/db/ 2 http://citeseerx.ist.psu.edu/ further describe and discuss our results, which provide an interesting insight into some important TEL research clusters, and close with a summary and discussion of next steps and future work." @default.
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• W2223014329 date "2010-06-29" @default.
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• W2223014329 title "Who are you working with? Visualizing TEL Research Communities" @default.
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