Crowdsourcing and Tech in the Wild

会議の名前
CHI 2025
Describing Explored Places through OpenStreetMap Data
要旨

Mobile navigation applications are good at providing efficient navigation instructions. However, they currently lack the capability to facilitate free exploration. Therefore, users are limited to encountering only places close to the shortest paths, neglecting places that could diversify navigation and foster spatial learning. To better understand what characteristics places have that users like to explore we collected a dataset with a mobile application that encourages free exploration using gamification (n = 39, t = 455 days, 106.50 km2). Using OpenStreetMap data, we found highly frequented freely explored places comprising office, educational, retail, touristic and commercial places. When comparing the characteristics of the freely explored places to those along the shortest path, those categories were different. Based on our findings, we propose that implementing more diverse routing algorithms can enhance navigation diversity, improve spatial learning, and optimise the utilisation of urban spaces for travel.

著者
Eve Schade
University of St. Gallen, St. Gallen, Switzerland
Gian-Luca Savino
University of St. Gallen, St. Gallen, Switzerland
Jasmin Niess
University of Oslo, Oslo, Norway
Johannes Schöning
University of St. Gallen, St. Gallen, Switzerland
DOI

10.1145/3706598.3713695

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713695

動画
Snap, Sweat, and Sketch: Designing Home Exercise Experiences for Augmented Reality Head-mounted Displays
要旨

Augmented Reality (AR) head-mounted displays (HMDs) offer potential for more inclusive and immersive exercising and exergaming experiences at home. Previous work found that augmenting home objects can create more engaging exercise experiences and identified various home objects that can be augmented to facilitate different exercises. However, it is unclear how these objects can be augmented to enhance exercising and tailored based on the exercise. We conducted a multi-part study involving a design activity using Snapchat and focus group discussion with 28 participants. We present five themes relating to participants' preferences for the augmentation of home objects for exercising, and identify and discuss key guidelines that designers and researchers should consider when augmenting home objects. Our results provide designers with guidelines and ideas for the augmentation of four different exercises, and advance the foundation for future work developing home-based exergaming through AR HMDs to increase people's physical activity levels.

著者
Michelle Adiwangsa
Australian National University, Canberra, Australian Capital Territory, Australia
Penny Sweetser
The Australian National University, Canberra, ACT, Australia
Anne Ozdowska
The Australian National University, Canberra, ACT, Australia
DOI

10.1145/3706598.3713575

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713575

動画
Friend or Foe? Navigating and Re-configuring ``Snipers' Alley''
要旨

In a 'digital by default’ society, essential services must be accessed online. This opens users to digital deception not only from criminal fraudsters but from a range of actors in a marketised digital economy. Using grounded empirical research from northern England, we show how supposedly 'trusted' actors, such as governments, (re)produce the insecurities and harms that they seek to prevent. Enhanced by a weakening of social institutions amid a drive for efficiency and scale, this has built a constricted, unpredictable digital channel. We conceptualise this as a ''snipers' alley''. Four key snipers articulated by participants' lived experiences are examined: 1) Governments; 2) Business; 3) Criminal Fraudsters; and 4) Friends and Family to explore how snipers are differentially experienced and transfigure through this constricted digital channel. We discuss strategies to re-configure the alley, and how crafting and adopting opportunity models can enable more equitable forms of security for all.

著者
Andrew C. Dwyer
Royal Holloway, University of London, Egham, Surrey, United Kingdom
Lizzie Coles-Kemp
Royal Holloway University of London, Egham, United Kingdom
Claude P. R.. Heath
Royal Holloway University of London, London, United Kingdom
Clara Crivellaro
Newcastle University, Newcastle upon Tyne, United Kingdom
DOI

10.1145/3706598.3713317

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713317

動画
Why does Automation Adoption in Organizations Remain a Fallacy?: Scrutinizing Practitioners' Imaginaries in an International Airport
要旨

In organizations, the interest in automation is long-standing. However, adopting automated processes remains challenging, even in environments that appear highly standardized and technically suitable for it. Through a case study in Amsterdam Airport Schiphol, this paper investigates automation as a broader sociotechnical system influenced by a complex network of actors and contextual factors. We study practitioners' collective understandings of automation and subsequent efforts taken to implement it. Using imaginaries as a lens, we report findings from a qualitative interview study with 16 practitioners involved in airside automation projects. Our findings illustrate the organizational dynamics and complexities surrounding automation adoption, as reflected in the captured problem formulations, conceptions of the technology, envisioned human roles in autonomous operations, and perspectives on automation fit in the airside ecosystem. Ultimately, we advocate for contextual automation design, which carefully considers human roles, accounts for existing organizational politics, and avoids techno-solutionist approaches.

著者
Garoa Gomez-Beldarrain
Delft University of Technology, Delft, Netherlands
Himanshu Verma
TU Delft, Delft, Netherlands
Euiyoung Kim
Delft University of Technology, Delft, Netherlands
Alessandro Bozzon
, Faculty of Industrial Design Engineering, TU Delft, Delft, Netherlands
DOI

10.1145/3706598.3713978

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713978

動画
Deploying and Examining Beacon for At-Home Patient Self-Monitoring with Critical Flicker Frequency
要旨

Chronic liver disease can lead to neurological conditions that result in coma or death. Although early detection can allow for intervention, testing is infrequent and unstandardized. Beacon is a device for at-home patient self-measurement of cognitive function via critical flicker frequency, which is the frequency at which a flickering light appears steady to an observer. This paper presents our efforts in iterating on Beacon’s hardware and software to enable at-home use, then reports on an at-home deployment with 21 patients taking measurements over 6 weeks. We found that measurements were stable despite being taken at different times and in different environments. Finally, through interviews with 15 patients and 5 hepatologists, we report on participant experiences with Beacon, preferences around how CFF data should be presented, and the role of caregivers in helping patients manage their condition. Informed by our experiences with Beacon, we further discuss design implications for home health devices.

受賞
Best Paper
著者
Richard Li
University of Washington, Seattle, Washington, United States
Philip Vutien
Division of Gastroenterology, Medicine, University of Washington, Seattle, Washington, United States
Sabrina Omer
Division of Gastroenterology, Medicine, University of Washington, Seattle, Washington, United States
Michael Yacoub
University of Washington, Seattle, Washington, United States
George Ioannou
University of Washington, Seattle, Washington, United States
Ravi Karkar
University of Massachusetts Amherst, Amherst, Massachusetts, United States
Sean A.. Munson
University of Washington, Seattle, Washington, United States
James Fogarty
University of Washington, Seattle, Washington, United States
DOI

10.1145/3706598.3714240

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714240

動画
Towards Fair and Equitable Incentives to Motivate Paid and Unpaid Crowd Contributions
要旨

Researchers commonly rely on contributions from either unpaid contributors or work done by paid crowdworkers. Rarely are the motivations of these workers and the accuracy of their contributions studied simultaneously in the wild over time. We maintain a public system where anyone can edit an evolving tabular dataset of Computer Science faculty profiles useful for the field of CS, and in this work, we analyze both the accuracy of contributions and the motivations of paid crowdworkers and unpaid contributors, combining data from real-world edit histories and a discrete choice experiment. The accuracy of edits made by unpaid contributors was 1.9 times higher than that of paid crowdworkers for difficult-to-find data and 1.5 times greater for data requiring domain-specific expertise. \actwo{Our discrete choice experiment reveals that while both groups are motivated by common attributes describing a contribution task: pay level, estimated completion time, interest, and the ability to help others, they make different trade-offs between these attributes when choosing crowd contribution tasks.} We provide recommendations to build hybrid data systems that mix extrinsic and intrinsic motivators to motivate highly accurate contributors, whether paid or unpaid.

著者
Shaun Wallace
University of Rhode Island, Kingston, Rhode Island, United States
Talie Massachi
Brown University, Providence, Rhode Island, United States
Jiaqi Su
Brown University, Providence, Rhode Island, United States
Dave B. Miller
Tufts University, Medford, Massachusetts, United States
Jeff Huang
Brown University, Providence, Rhode Island, United States
DOI

10.1145/3706598.3714195

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714195

動画
Crowdsourced Think-Aloud Studies
要旨

The think-aloud (TA) protocol is a useful method for evaluating user interfaces, including data visualizations. However, TA studies are time-consuming to conduct and hence often have a small number of participants. Crowdsourcing TA studies would help alleviate these problems, but the technical overhead and the unknown quality of results have restricted TA to synchronous studies. To address this gap we introduce CrowdAloud, a system for creating and analyzing asynchronous, crowdsourced TA studies. CrowdAloud captures audio and provenance (log) data as participants interact with a stimulus. Participant audio is automatically transcribed and visualized together with events data and a full recreation of the state of the stimulus as seen by participants. To gauge the value of crowdsourced TA studies, we conducted two experiments: one to compare lab-based and crowdsourced TA studies, and one to compare crowdsourced TA studies with crowdsourced text prompts. Our results suggest that crowdsourcing is a viable approach for conducting TA studies at scale.

著者
Zach Cutler
University of Utah, Salt Lake City, Utah, United States
Lane Harrison
Worcester Polytechnic Institute, Worcester, Massachusetts, United States
Carolina Nobre
University of Toronto, Toronto, Ontario, Canada
Alexander Lex
University of Utah, Salt Lake City, Utah, United States
DOI

10.1145/3706598.3714305

論文URL

https://dl.acm.org/doi/10.1145/3706598.3714305

動画