Along with significant opportunities, Massively Open Online Courses (MOOCs) provide major challenges to students (keeping track of course materials and effectively interacting with teachers and fellow students), teachers (managing thousands of students and supporting their learning progress), researchers (understanding how students interact with materials and each other), and MOOC platform developers (supporting effective course design and delivery in a scalable way). This article demonstrates the use of data analysis and visualization as a means to empower students, teachers, researchers, and platform developers by making large volumes of data easy to understand. First, we introduce the insight needs of different stakeholder groups. Second, we compare the wide variety of data provided by major MOOC platforms. Third, we present a novel framework that distinguishes visualizations by the type of questions they answer. We then review the state of the art MOOC visual analytics using a tabulation of stakeholder needs versus visual analytics workflow types. Finally, we present new data analysis and visualization workflows for statistical, geospatial, and topical insights. The workflows have been optimized and validated in the Information Visualization MOOC (IVMOOC) annually taught at Indiana University since 2013. All workflows, sample data, and visualizations are provided at http://cns.iu.edu/2016-MOOCVis.html.
To have a better understanding of the ecological factors that may contribute to moose Alces alces and vehicle collisions in northern British Columbia, we analyzed Wildlife Accident Reporting System data that were collected between 2000 and 2005 by highway maintenance contractors. We delineated 29 moose-vehicle collision hotspots and 15 control sites at which we assessed environmental and road infrastructure attributes through field surveys and remotely sensed data. A logistic regression model including both coarse- and fine-scale environmental factors suggested that hotspots were more likely to be characterized by the number of roadside mineral licks and bisection of the highway corridor through black spruce forest–sphagnum bog habitat and swamps. The absence of rivers within 1 km and less lake area within 500 m of the highway also better characterized hotspots than controls. At the fine scale, deciduous forest cover along the highway edge and the proportion of browse to nonbrowse vegetation between the road shoulder and forest edge were also related to collision sites. Based on these data, the mitigation of collision hotspots should include decommissioning roadside mineral licks where they occur and cutting roadside brush to improve driver visibility and reduce browse resprouting and attractiveness. Where new road construction or road realignments are being contemplated, we recommend considering routes with more lake area, more rivers, fewer swamps, and fewer black spruce forest–sphagnum bog habitats to help reduce collisions. We discuss the utility of installing novel warning signage in areas where collisions are recurrent.
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