Predicting interaction effort in web interface widgets

Abstract

The product of good design should render a tool invisible for a user who is executing a task. Unfortunately, web applications are often far from invisible to users, who struggle with poor design of websites and processes in them. We are particularly interested in web processes that involve form filling, so we have been studying how people interact with web forms. Besides cataloguing user interaction problems that are common in web forms, we have noticed that, in many cases, there is a single form element or widget to blame for a certain interaction problem, because such widget is not the most appropriate one for the required input in that particular context. This unfitness of the widget causes an extra burden to the user, which we call interaction effort. In this work we propose measuring the interaction effort of a widget with a unified score based on micro-measures automatically captured from interaction logs. We present the micro-measures that were found relevant to predict the interaction effort in 6 different types of web forms widgets. We describe a large data collection process and prediction models, showing that it is indeed possible to automatically predict a widget interaction effort score by learning from expert human ratings. We consequently believe that the interaction effort could be used as an effective metric to compare small variations in a design in terms of user experience.