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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.
Christian D

Academic Analytics: The Uses of Management Information and Technology in Higher Educati... - 0 views

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    "This study analyzes the outcomes at more than 380 higher education institutions. It looks at what the chosen strategies have accomplished, in what ways institutions use the data they collect, whether institutions are investing more resources in tools that enable them to collect and manipulate management information, and the degree to which information and analysis are being used to support institutional decision making."
Tony Searl

Conor Williams: Educational Productivity and the Reform Wars - 0 views

  • data difficulties in "some" cases hardly eviscerate a study of "more than 9,000 districts that enroll more than 85 percent of all U.S. students."
  • Poverty does not make productive, efficient education impossible.
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    data was hard to come by in some districts, it was untrustworthy in others and controlling for all relevant variables when comparing school districts is really, really difficult.
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