A Guide to Using Asynchronous Remote Communities (ARC) for Researching Distributed Populations

Haley MacLeod; Ben Jelen; Annu Prabhakar; Lora Oehlberg; Katie Siek; Kay Connelly

Research Article

A Guide to Using Asynchronous Remote Communities (ARC) for Researching Distributed Populations

Download6467 downloads

Cite: BibTeX Plain Text

@ARTICLE{10.4108/eai.18-7-2017.152898,
    author={Haley MacLeod and Ben Jelen and Annu Prabhakar and Lora Oehlberg and Katie Siek and Kay Connelly},
    title={A Guide to Using Asynchronous Remote Communities (ARC) for Researching Distributed Populations},
    journal={EAI Endorsed Transactions on Pervasive Health and Technology},
    volume={3},
    number={11},
    publisher={EAI},
    journal_a={PHAT},
    year={2017},
    month={7},
    keywords={class file, LATEX 2ε, EAI Endorsed Transactions},
    doi={10.4108/eai.18-7-2017.152898}
}

Haley MacLeod
Ben Jelen
Annu Prabhakar
Lora Oehlberg
Katie Siek
Kay Connelly
Year: 2017
A Guide to Using Asynchronous Remote Communities (ARC) for Researching Distributed Populations
PHAT
EAI
DOI: 10.4108/eai.18-7-2017.152898

Haley MacLeod¹^,*, Ben Jelen¹, Annu Prabhakar¹, Lora Oehlberg², Katie Siek¹, Kay Connelly¹

1: School of Informatics and Computing, Indiana University, Bloomington, Indiana, USA
2: Department of Computer Science, University of Calgary, Calgary, Alberta, Canada

*Contact email: hemacleo@indiana.edu

Abstract

Existing research methods are largely intended to be conducted co-located and synchronously with a study population, but this approach is not feasible with remote or distributed populations. We describe a needs assessment study we conducted on Facebook. We report on our use of adapted versions of commonly used HCI research methods and lessons learned from this approach.

Keywords: class file, LATEX 2ε, EAI Endorsed Transactions

Received: 2016-07-01
Accepted: 2017-02-02
Published: 2017-07-18
Publisher: EAI

: http://dx.doi.org/10.4108/eai.18-7-2017.152898

Copyright © 2017 Haley MacLeod et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.