Alena Seredko
Biographic Data
| ID | 5704069 |
|---|---|
| NAME | Alena Seredko |
| GIVEN NAMES | Alena |
| FAMILY NAME | Seredko |
| SIGNATURE | SEREDKO A |
| AFFILIATIONS | University of Gothenburg |
| ORCID | 0009-0003-8672-4180 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Collectively produced epistemic objects and their necessary incompleteness for professional learning on a large-scale online platform
This article presents a theoretical approach to examining professional knowledge practices on online platforms, employing the concept of epistemic objects and their incompleteness, and analysing how objects are actively produced and negotiated through interactions among users and the platform. We illustrate this approach by conducting an interaction analysis of two threads from Stack Overflow, a prominent online platform where millions of softwar…
Gaming Expertise Metrics
Online environments have the potential to disrupt traditional orderings of expertise and allow a wider audience to engage as experts in the process of knowledge creation. Many online environments use crowdsourced metric-based systems, such as upvotes and reputation scores, to help identify experts. While these online systems provide opportunities to recognize expertise in new ways, they continue to reproduce and reconfigure existing issues around…
Human-machine-learning integration and task allocation in citizen science
The field of citizen science involves the participation of citizens across different stages of a scientific project; within this field there is currently a rapid expansion of the integration of humans and AI computational technologies based on machine learning and/or neural networking-based paradigms. The distribution of tasks between citizens (“the crowd”), experts, and this type of technologies has received relatively little attention. To illus…
No prominent works on this page.
Human-machine-learning integration and task allocation in citizen science
The field of citizen science involves the participation of citizens across different stages of a scientific project; within this field there is currently a rapid expansion of the integration of humans and AI computational technologies based on machine learning and/or neural networking-based paradigms. The distribution of tasks between citizens (“the crowd”), experts, and this type of technologies has received relatively little attention. To illus…
Gaming Expertise Metrics
Online environments have the potential to disrupt traditional orderings of expertise and allow a wider audience to engage as experts in the process of knowledge creation. Many online environments use crowdsourced metric-based systems, such as upvotes and reputation scores, to help identify experts. While these online systems provide opportunities to recognize expertise in new ways, they continue to reproduce and reconfigure existing issues around…
Collectively produced epistemic objects and their necessary incompleteness for professional learning on a large-scale online platform
This article presents a theoretical approach to examining professional knowledge practices on online platforms, employing the concept of epistemic objects and their incompleteness, and analysing how objects are actively produced and negotiated through interactions among users and the platform. We illustrate this approach by conducting an interaction analysis of two threads from Stack Overflow, a prominent online platform where millions of softwar…
Computer Science (3 works) · Data science (3 works) · Knowledge management (3 works) · Sociology (3 works) · Crowdsourcing (2 works) · Epistemology (2 works) · Mobile Crowdsensing and Crowdsourcing (2 works) · Psychology (2 works) · World Wide Web (2 works) · Artificial Intelligence (1 work)