EMotion: Retrospective in-car user experience evaluation
Well-established self-reporting methods in HCI such as the Experience Sampling Method (ESM) prove rather limited for sampling in-car experiences, as they distract the driver from the primary task of driving. In this work we present eMotion, a mobile application that provides a lightweight alternative to Experience Sampling. eMotion uses the front and back facing cameras of a mobile device with the goal of unobtrusively capturing drivers' facial expressions along with 10-sec videos of the outside landscape, the location, and the speed of the car at the moment of sampling. All these logs are later presented to the user with the goal of helping her recall her experience (e.g. experienced stress) at that moment. We report on the design of eMotion as well as a study design, with which we will try to assess the validity of the elicited data.