Toward Crowdsourced User Studies for Software Evaluation
Florian Daniel, Pavel Kucherbaev

TL;DR
This paper explores the potential of crowdsourcing to conduct fast, reliable, and cost-effective software user experience studies, aiming to replace traditional lab-based methods with scalable online approaches.
Contribution
It proposes a vision and framework for crowdsourced user studies in software evaluation, addressing challenges in maintaining quality and reliability.
Findings
Identifies key challenges in crowdsourcing user studies.
Suggests methods to ensure data quality in crowdsourced experiments.
Highlights potential benefits of scalable, cost-effective user testing.
Abstract
This work-in-progress paper describes a vision, i.e., that of fast and reliable software user experience studies conducted with the help from the crowd. Commonly, user studies are controlled in-lab activities that require the instruction, monitoring, interviewing and compensation of a number of participants that are typically hard to recruit. The goal of this work is to study which user study methods can instead be crowdsourced to generic audiences to enable the conduct of user studies without the need for expensive lab experiments. The challenge is understanding how to conduct crowdsourced studies without giving up too many of the guarantees in-lab settings are able to provide.
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Taxonomy
TopicsMobile Crowdsensing and Crowdsourcing · Data Stream Mining Techniques · Open Source Software Innovations
