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

TL;DR

This paper introduces Technology-Assisted Reconstruction (TAR), a new methodology that reduces participant burden by combining passive data logging with behavior reconstruction to evaluate personal informatics systems.

Contribution

It proposes TAR as an alternative to Experience Sampling, integrating passive data collection with reconstruction techniques for in-situ evaluation of personal informatics.

Findings

TAR reduces participant burden compared to traditional methods.

TAR effectively evaluates personal informatics systems.

Potential for TAR to inspire new evaluation methodologies.

Abstract

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.