Towards User-Centred Analytics: User-Adaptive Visualizations
In this session, we will watch and discuss one of the keynotes from Learning Analytics and Knowledge Conference 2018 by Professor Cristina Conati, Professor, Department of Computer Science, University of British Columbia. Cristina is interested in integrating research in Artificial Intelligence, Human Computer Interaction and Cognitive Science to create intelligent user interfaces that can effectively and reliably adapt to the needs of each user.
“As digital information continues to accumulate in our lives, information visualizations have become an increasingly relevant tool for discovering trends and shaping stories from this overabundance of data. Education is not an exception, with learner and teacher visualization dashboards being extensively investigated as new means to change pedagogy and learning. Visualizations are typically designed based on the data to be displayed and the tasks to be supported, but they follow a one size-fits-all approach when it comes to users’ individual differences such as expertise, cognitive abilities, states and preferences. There is, however, mounting evidence that these characteristics can significantly influence user experience during information visualization tasks. These findings have triggered research on user-adaptive visualizations, i.e., visualizations that can track and adapt to relevant user characteristics and specific needs. In this talk, I will present results on which user individual differences can impact visualization processing, and on how these differences can be captured using predictive models based on eye-tracking data. I will also discuss how to leverage these models to provide personalized support that can improve the user’s experience with a visualization.”
Here is the link to slides, video and details of this keynote: https://latte-analytics.sydney.edu.au/keynotes/