Confusion on the web is a problem connected with web applications. Sometimes apps do not have to be complex to confuse users. Common problems may have newcomers, when accessing the app for the very first time. Ability to identify confusion can help us to give hints to users. These hints can help user to fulfil their needs. Hints can be combined to web application guides.
In our work we identify and predict confusion on web application. We will make a method for this purpose, using logs from the server. Except them we concentrate on user mouse movements, clicks, scrolling and browsing patterns which describe behaviour. We consider usage of eye-tracker data. Next we apply machine learning methods on gathered data. To confirm our method we will establish an experiment, where we will collect feedback from users. At the moment we are workin g on selection of appropriate way to collect these feedback. These will be used as labeled data. Our solution can be combined with production systems providing web application guides .
Personalized Web Research Group
Faculty of Informatics and Information Technologies
Slovak University of Technology in Bratislava