Described herein are various technologies pertaining to estimating affective states of a user by way of monitoring data streams output by sensors and user activity on a computing device. Models of valence, arousal, and engagement can be learned during a training phase, and such models can be employed to compute values that are indicative of valence, arousal, and engagement of a user in near-real time. A visualization that represents estimated affective states of a user over time is generated to facilitate user reflection.