Analysis and visualisation for inclusive learning analytics
In this talk, Professor Chaoli Wang will present the inclusive learning analytics effort his team has been collaborating with Notre Dame Learning to identify and reduce the academic achievement gaps in college-level introductory courses.
Two visual analytics tools will be introduced:
- CCVis, designed to analyse the course clickstream data and explore student online learning behaviours, and
- PerformanceVis, developed to analyse student admission and course performance data and investigate homework and exam question design.
Professor Wang will also briefly discuss other works and future directions for this research effort.
Presenter
Professor Chaoli Wang, University of Notre Dame
Chaoli Wang is a Professor of Computer Science and Engineering at the University of Notre Dame. He holds a PhD in computer and information science from The Ohio State University. Dr Wang's primary research is visualisation, including scientific visualisation and visual analytics. He has served as a paper co-chair for IEEE VIS, IEEE PacificVis, IEEE LDAV, and ChinaVis, an associate editor of IEEE TVCG, and the international liaison of the IEEE VGTC executive committee. His research has been funded by the U.S. National Science Foundation and the U.S. Department of Energy.
About Learning Analytics and Digital Learning Community of Practice
All UQ staff are invited to attend these sessions aiming to develop a community of practice around learning analytics, evidence-based teaching practice and digital learning.
Each session intends to cater to a variety of presentation and participation formats including presentions, lightning talks, practical data processing tutorials, predictive model building tutorials, learning tool design sessions, recent publication/conference overviews, as well as panel discussions and debates.
For general enquiries please contact learninganalytics@uq.edu.au.