The authors propose AnnoSense, a set of 15 expert-reviewed guidelines for everyday emotion data collection, derived from survey, interview, and focus group insights from 119 stakeholders.
Beyond Experience Sampling: Evaluating Personal Informatics with Technology-Assisted Reconstruction
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Experience Sampling has been considered the golden standard of in-situ measurement, yet, at the expense of high burden to participants. In this paper we propose Technology-Assisted Reconstruction (TAR), a methodological approach that combines passive logging of users' behaviors with use of these data in assisting the reconstruction of behaviors and experiences. Through a number of recent and ongoing projects we will discuss how TAR may be employed for the evaluation of personal informatics systems, but also, conversely, how ideas from the field of personal informatics may contribute towards the development of new methodologies for in-situ evaluation.
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AnnoSense: A Framework for Physiological Emotion Data Collection in Everyday Settings for AI
The authors propose AnnoSense, a set of 15 expert-reviewed guidelines for everyday emotion data collection, derived from survey, interview, and focus group insights from 119 stakeholders.