HCJul 7, 2012

Beyond Experience Sampling: Evaluating Personal Informatics with Technology-Assisted Reconstruction

arXiv:1207.1821v13 citations
Originality Synthesis-oriented
AI Analysis

This addresses the problem of participant burden in evaluation methods for researchers and practitioners in personal informatics, but appears incremental as it builds on existing logging and reconstruction ideas.

The paper tackles the high burden of Experience Sampling in in-situ measurement by proposing Technology-Assisted Reconstruction (TAR), which combines passive logging with data-assisted reconstruction of behaviors and experiences, and discusses its application in evaluating personal informatics systems.

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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