Obtaining Self-Reports for Affective System Design

Constructing affect-sensitive intelligent tutoring systems often requires training data in which the learner's true affective or mental states are known. We use students' self reports as ground truth data. We record students during learning then obtain self reports about their mental states during post-recording interviews. We have found a surprising level of consistency in the relationship across different students from different cultures between affective or mental states and unintentional hand gestures during learning. However, in collecting these data, we face some challenges that we outline in this paper. Author