EyeLikert: Eye-based Interactions for Answering Surveys

Abstract

Surveys are a widely used method for data collection from participants. However, responding to surveys is a time consuming task and requires cognitive and physical efforts of the participants. Eye-based interactions offer the advantage of high speed pointing, low physical effort and implicitness. These advantages are already successfully leveraged in different domains, but so far not investigated in supporting participants in responding to surveys. In this paper, we present EyeLikert, a tool that enables users to answer Likert-scale questions in surveys with their eyes. EyeLikert integrates three different eye-based interactions considering the Midas Touch problem. We hypothesize that enabling eye-based interactions to fill out surveys offers the potential to reduce the physical effort, increase the speed of responding questions, and thereby reduce drop-out rates.