A Narrative Visualization Approach For Massive Open Online Courses Data Analysis

MPhil Thesis Defence


Title: "A Narrative Visualization Approach For Massive Open Online Courses Data 
Analysis"

By

Mr. Zhen LI


Abstract

The practical power of data visualization is currently attracting much 
attention in the e-learning domain, especially now large amounts of 
multivariate MOOC data have become available. A growing number of studies have 
been conducted in recent years to help instructors better analyze learner 
behaviors and reflect on their teaching. However, visual designs can be complex 
in modern data visualization systems, which poses special challenges for 
explaining them to the general audience.

In this work, for introducing complex visualizations of MOOCs data to 
non-experts, we first present a slideshow authoring tool in which we specify a 
data visualization as a hierarchical combination of components, and these 
components are automatically detected and extracted by this tool. The editors 
craft an introduction slideshow through first organizing these components, and 
then explaining them sequentially. In the second part of the thesis, according 
to the decomposition approach which we have proposed in the first part and its 
result on existing MOOC visualizations, we developed 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 way.


Date:			Thursday, 5 July 2018

Time:			4:00pm - 6:00pm

Venue:			Room 5560
 			Lifts 27/18

Committee Members:	Prof. Huamin Qu (Supervisor)
 			Dr. Xiaojuan Ma (Chairperson)
 			Dr. Yangqiu Song


**** ALL are Welcome ****