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Using wiki for rapid authoring of huge numbers of e-assessments
Ilire Hasani-Mavriqi, Christoph Portsch, Christoph Trattner, Brigita Kacjan, Denis Helić, Hermann A. Maurer, 2010, published scientific conference contribution

Abstract: Nowadays, Question and Test Interoperability (QTI) is a de facto standard for management of so called E-Assessments. It is our experience from numerous technology-supported education projects that QTI supports interoperability andexchange of assessments but completely neglects the authoring process of these assessments. In particular, the task of authoring of a large number of assessments for teachers without technical background is very time and resources consuming one. Therefore, we developed a novel format that focuses on supporting teachers in rapid authoring of huge number of E-Assessments and implemented it as a part of an educational Wiki system. In this paper we present this new format together with its implementation and the first evaluation results of the implemented tool.
Keywords: internet, internet educational tools, wikipedia, assessment
Published: 07.06.2012; Views: 778; Downloads: 19
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Robust clustering of languages across Wikipedia growth
Kristina Ban, Matjaž Perc, Zoran Levnajić, 2017, original scientific article

Abstract: Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.
Keywords: Wikipedia, language, growth dynamics, data analysis, clustering
Published: 13.11.2017; Views: 347; Downloads: 205
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