THESIS
2018
xi, 53 pages : illustrations ; 30 cm
Abstract
The practical power of data visualization is currently attracting significant attention in
the e-learning domain, especially now that large amounts of multivariate massive open
online course (MOOC) data have become available. A growing number of studies has
recently been conducted to help instructors analyze learner behaviors well and reflect on
their teaching methods. However, visual designs can be complex in modern data visualization
systems, thereby rendering their explanation to the general audience challenging.
In this thesis, for introducing complex visualizations of MOOC data to non-experts,
we first present a slideshow authoring tool in which we specify data visualization as a
hierarchical combination of components, which are automatically detected and extracted
by this...[
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The practical power of data visualization is currently attracting significant attention in
the e-learning domain, especially now that large amounts of multivariate massive open
online course (MOOC) data have become available. A growing number of studies has
recently been conducted to help instructors analyze learner behaviors well and reflect on
their teaching methods. However, visual designs can be complex in modern data visualization
systems, thereby rendering their explanation to the general audience challenging.
In this thesis, for introducing complex visualizations of MOOC data to non-experts,
we first present a slideshow authoring tool in which we specify data visualization as a
hierarchical combination of components, which are automatically detected and extracted
by this tool. The editors craft an introduction slideshow by organizing these components
and explaining them sequentially. In the second part of the thesis, according to the decomposition
approach we propose in the first part and its result on existing MOOC visualizations,
we develop a narrative visualization system with an interactive slideshow that
helps instructors and education experts explore potential learning patterns and convey data stories in an understandable and efficient manner.
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