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Research at St Andrews

Self-reflection and personal physicalization construction

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Alice Thudt, Uta Hinrichs, Samuel Huron, Sheelagh Carpendale

School/Research organisations

Abstract

Self-reflection is a central goal of personal informatics systems, and constructing visualizations from physical tokens has been found to help people reflect on data. However, so far, constructive physicalization has only been studied in lab environments with provided datasets. Our qualitative study investigates the construction of personal physicalizations in people's domestic environments over 2-4 weeks. It contributes an understanding of (1) the process of creating personal physicalizations, (2) the types of personal insights facilitated, (3) the integration of self-reflection in the physicalization process, and (4) its benefits and challenges for self-reflection. We found that in constructive personal physicalization, data collection, construction and self-reflections are deeply intertwined. This extends previous models of visualization creation and data-driven self-reflection. We outline how benefits such as reflection through manual construction, personalization, and presence in everyday life can be transferred to a wider set of digital and physical systems.
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Details

Original languageEnglish
Title of host publicationProceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI'18)
Place of PublicationNew York, NY
PublisherACM
Number of pages13
ISBN (Electronic)9781450356206
DOIs
Publication statusPublished - 21 Apr 2018
EventACM CHI 2018 Conference on Human Factors in Computing Systems - Palais de Congrès, Montréal, Canada
Duration: 21 Apr 201826 Apr 2018
Conference number: 36
https://chi2018.acm.org/

Conference

ConferenceACM CHI 2018 Conference on Human Factors in Computing Systems
Abbreviated titleCHI
CountryCanada
CityMontréal
Period21/04/1826/04/18
Internet address

    Research areas

  • Self-Reflection, Constructive Visualization, Personal Data

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ID: 252301421