Chris Norval is a postdoctoral researcher at the University of St Andrews on a project to predict when social media users consent to having their data used for health research.
Chris completed his PhD in Human Computer Interaction at the University of Dundee in 2014. His thesis explored reasons why older adults were less likely to use social networking sites than younger adults. Issues (such as privacy and security concerns, a lack of skill, negative preconceptions) were identified from user studies, and recommendations for the designers of such sites were derived to mitigate or avoid these issues. These recommendations were then verified in a user study which compared a prototype replica of a mainstream social networking site to a version which utilised the recommendations.
After completing his PhD, Chris worked in the games industry as a data analyst for two years, where he designed comparative evaluations, conducted exploratory data analysis, and worked with the designers of the games, advocating for a data driven perspective. As a side project, Chris explored how machine learning algorithms could be used to break down complex relationships in the data and predict future events.
His research interests include purposeful social media, the application of machine learning techniques, and the effective use of experimental design and statistical testing within HCI research.
Using a mixed-methods approach, user-centered recommendations were derived to improve SNSs for older adults. A prototype replica of a popular SNS was created, which could load two different UI versions, a control UI and one which was modified by the recommendations. By conducting a comparative evaluation with 25 older adults, results show that the UI version which was modified by the recommendations received a statistically higher usability score, a higher task completion rate and was preferred more often than the control version. The PhD is being supervised by Prof. John Arnott and Prof. Vicki Hanson.