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Accomplishing Collaboration at Scale: How Professionals Jointly Frame Problems on Stack Overflow

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Title: Accomplishing Collaboration at Scale: How Professionals Jointly Frame Problems on Stack Overflow
Language: English
Authors: Alena Seredko (ORCID 0009-0003-8672-4180)
Source: International Journal of Computer-Supported Collaborative Learning. 2025 20(4):463-489.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 27
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Descriptors: Cooperative Learning, Problem Solving, Educational Technology, MOOCs, Computer Software, Sequential Approach, Norms, Mutual Intelligibility
DOI: 10.1007/s11412-025-09451-w
ISSN: 1556-1607
1556-1615
Abstract: This study investigates how collaboration is practically accomplished on large-scale online platforms, with scale understood qualitatively as asynchronous and fluid participation. Using Stack Overflow as an empirical case, it specifically examines how users collaboratively frame programming problems through questions, comments and iterative edits. Drawing on the practice-based perspective and ethnomethodology, the study uses trace ethnography and sequential analysis of selected Stack Overflow threads. Findings reveal that profession-specific shared objects (minimal reproducible examples) structured within the platform's dual-space design, consisting of distinct question and commenting spaces, serve as crucial resources, enabling both immediate and future unknown contributors to understand and effectively engage in problem faming and problem-solving processes. Furthermore, the study identifies key interactional methods, i.e., standardized norm-enforcing requests and explicit referencing, which ensure mutual intelligibility of users' comments and edits, essential for accomplishing collaboration at scale. The findings contribute to theoretical understandings of mass collaboration, offer design insights for platforms to facilitate the coordination of collaborative activities and provide recommendations for professional education to support productive participation in large-scale collaboration.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1497465
Database: ERIC
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  Data: Accomplishing Collaboration at Scale: How Professionals Jointly Frame Problems on Stack Overflow
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  Data: <searchLink fieldCode="AR" term="%22Alena+Seredko%22">Alena Seredko</searchLink> (ORCID <externalLink term="http://orcid.org/0009-0003-8672-4180">0009-0003-8672-4180</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+of+Computer-Supported+Collaborative+Learning%22"><i>International Journal of Computer-Supported Collaborative Learning</i></searchLink>. 2025 20(4):463-489.
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  Data: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
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  Data: This study investigates how collaboration is practically accomplished on large-scale online platforms, with scale understood qualitatively as asynchronous and fluid participation. Using Stack Overflow as an empirical case, it specifically examines how users collaboratively frame programming problems through questions, comments and iterative edits. Drawing on the practice-based perspective and ethnomethodology, the study uses trace ethnography and sequential analysis of selected Stack Overflow threads. Findings reveal that profession-specific shared objects (minimal reproducible examples) structured within the platform's dual-space design, consisting of distinct question and commenting spaces, serve as crucial resources, enabling both immediate and future unknown contributors to understand and effectively engage in problem faming and problem-solving processes. Furthermore, the study identifies key interactional methods, i.e., standardized norm-enforcing requests and explicit referencing, which ensure mutual intelligibility of users' comments and edits, essential for accomplishing collaboration at scale. The findings contribute to theoretical understandings of mass collaboration, offer design insights for platforms to facilitate the coordination of collaborative activities and provide recommendations for professional education to support productive participation in large-scale collaboration.
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