Gabber: Supporting Voice in Participatory Qualitative Practices

Jay Rainey; Kyle Montague; Pamela Briggs; Robert Anderson; Thomas Nappey; Patrick Olivier

doi:10.1145/3290605.3300607

Gabber: Supporting Voice in Participatory Qualitative Practices

Jay Rainey, Kyle Montague, Pamela Briggs, Robert Anderson, Thomas Nappey, Patrick Olivier

School of Psychology

Research output: Contribution to conference › Paper › peer-review

9 Citations (Scopus)

Abstract

We describe the iterative design, development and learning process we undertook to produce Gabber, a digital platform that aims to support distributed capture of spoken interviews and discussions, and their qualitative analysis. Our aim is to reduce both expertise and cost barriers associated with existing technologies, making the process more inclusive. Gabber structures distributed audio data capture, facilitates participatory sensemaking, and supports collaborative reuse of audio. We describe our design and development journey across three distinct field trials over a two-year period. Reflecting on the iterative design process, we offer insights into the challenges faced by non-experts throughout their qualitative practices, and provide guidance for researchers designing systems to support engagement in these practices.

Original language	English
Number of pages	12
DOIs	https://doi.org/10.1145/3290605.3300607
Publication status	Published - 2 May 2019
Event	ACM CHI Conference on Human Factors in Computing Systems 2019: CHI’19 Workshop: HCI in China: Research Agenda, Education Curriculum, Industry Partnership, and Communities Building - Scottish Event Campus, Glasgow, United Kingdom Duration: 4 May 2019 → 9 May 2019 https://chi2019.acm.org/ http://chi2019.acm.org

Conference

Conference	ACM CHI Conference on Human Factors in Computing Systems 2019
Abbreviated title	CHI 2019
Country/Territory	United Kingdom
City	Glasgow
Period	4/05/19 → 9/05/19
Internet address	https://chi2019.acm.org/ http://chi2019.acm.org

Keywords

Collaborative Sensemaking
QDAS
Audio annotation

Access to Document

10.1145/3290605.3300607

Cite this

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abstract = "We describe the iterative design, development and learning process we undertook to produce Gabber, a digital platform that aims to support distributed capture of spoken interviews and discussions, and their qualitative analysis. Our aim is to reduce both expertise and cost barriers associated with existing technologies, making the process more inclusive. Gabber structures distributed audio data capture, facilitates participatory sensemaking, and supports collaborative reuse of audio. We describe our design and development journey across three distinct field trials over a two-year period. Reflecting on the iterative design process, we offer insights into the challenges faced by non-experts throughout their qualitative practices, and provide guidance for researchers designing systems to support engagement in these practices.",

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T1 - Gabber

T2 - ACM CHI Conference on Human Factors in Computing Systems 2019

AU - Rainey, Jay

AU - Montague, Kyle

AU - Briggs, Pamela

AU - Anderson, Robert

AU - Nappey, Thomas

AU - Olivier, Patrick

PY - 2019/5/2

Y1 - 2019/5/2

N2 - We describe the iterative design, development and learning process we undertook to produce Gabber, a digital platform that aims to support distributed capture of spoken interviews and discussions, and their qualitative analysis. Our aim is to reduce both expertise and cost barriers associated with existing technologies, making the process more inclusive. Gabber structures distributed audio data capture, facilitates participatory sensemaking, and supports collaborative reuse of audio. We describe our design and development journey across three distinct field trials over a two-year period. Reflecting on the iterative design process, we offer insights into the challenges faced by non-experts throughout their qualitative practices, and provide guidance for researchers designing systems to support engagement in these practices.

AB - We describe the iterative design, development and learning process we undertook to produce Gabber, a digital platform that aims to support distributed capture of spoken interviews and discussions, and their qualitative analysis. Our aim is to reduce both expertise and cost barriers associated with existing technologies, making the process more inclusive. Gabber structures distributed audio data capture, facilitates participatory sensemaking, and supports collaborative reuse of audio. We describe our design and development journey across three distinct field trials over a two-year period. Reflecting on the iterative design process, we offer insights into the challenges faced by non-experts throughout their qualitative practices, and provide guidance for researchers designing systems to support engagement in these practices.

KW - Collaborative Sensemaking

KW - QDAS

KW - Audio annotation

UR - https://www.scopus.com/pages/publications/85067614291

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DO - 10.1145/3290605.3300607

M3 - Paper

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ER -

Gabber: Supporting Voice in Participatory Qualitative Practices

Abstract

Conference

Keywords

Access to Document

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TalkFutures: Supporting Qualitative Practices in Distributed Community Engagements

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