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hansdezwart

Scraping for Journalism: A Guide for Collecting Data - ProPublica - 0 views

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    We've written a series of how-to guides explaining how we collected the data. Most of the techniques are within the ability of the moderately experienced programmer.
hansdezwart

http://www.ifets.info/journals/11_3/16.pdf - 0 views

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    As the integration of community-centred teaching practices intensifies, an understanding of the types of relationships that manifest in this network and the associated impact on student learning is required. This paper explores the relationship between a student's position in a classroom social network and their reported level of sense of community. Quantitative methods, such as Rovai's (2002b) Classroom Community Scale and social network centrality measures, were incorporated to evaluate an individual's level of sense of community and their position within the classroom social network. Qualitative methods such as discussion forum content analysis and student interviews were adopted to clarify and further inform this relationship. The results demonstrate that the centrality measures of  closeness and  degrees are positive predictors of an individual's reported sense of community whereas,  betweenness indicates a negative correlation. Qualitative analyses indicate that an individual's pre-existing external social network influences the type of support and information exchanges an individual requires and therefore, the degree of sense of community ultimately experienced. The paper concludes by discussing future recommendations for teaching practices incorporating computer-mediated communications. 
Phillip Long

http://www.ifets.info/journals/17_4/4.pdf - 0 views

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    Papamitsiou, Z., & Economides, A. (2014). Learning Analytics and Educational Data Mining in Practice: A Systematic Literature Review of Empirical Evidence. Educational Technology & Society, 17 (4), 49-64. This paper aims to provide the reader with a comprehensive background for understanding current knowledge on Learning Analytics (LA) and Educational Data Mining (EDM) and its impact on adaptive learning. It constitutes an overview of empirical evidence behind key objectives of the potential adoption of LA/EDM in generic educational strategic planning. We examined the literature on experimental case studies conducted in the domain during the past six years (2008-2013). Search terms identified 209 mature pieces of research work, but inclusion criteria limited the key studies to 40. We analyzed the research questions, methodology and findings of these published papers and categorized them accordingly. We used non-statistical methods to evaluate and interpret findings of the collected studies. The results have highlighted four distinct major directions of the LA/EDM empirical research. We discuss on the emerged added value of LA/EDM research and highlight the significance of further implications. Finally, we set our thoughts on possible uncharted key questions to investigate both from pedagogical and technical considerations.
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