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Supporting Human and Machine Co-Learning in Citizen Science: Lessons From Gravity Spy Cover

Supporting Human and Machine Co-Learning in Citizen Science: Lessons From Gravity Spy

Citizen Science: Theory and Practice
Volume 9 (2024): Issue 1
By: Carsten Østerlund,  Kevin Crowston,  Corey B. Jackson,  Yunan Wu,  Alexander O. Smith and  Aggelos K. Katsaggelos  
Open Access
|Dec 2024

Authors

Carsten Østerlund

costerlu@syr.edu

Syracuse University, School of Information Studies

Kevin Crowston

crowston@syr.edu

Syracuse University

Corey B. Jackson

cbjackson2@wisc.edu

University of Wisconsin-Madison, School of Computer, Data, and Information Sciences

Yunan Wu

yunanwu2020@u.northwestern.edu

Northwestern University, Department of Electrical and Computer Engineering

Alexander O. Smith

aosmith@syr.edu

Syracuse University, School of Information Studies

Aggelos K. Katsaggelos

a-katsaggelos@northwestern.edu

Northwestern University, Department of Electrical and Computer Engineering
DOI: https://doi.org/10.5334/cstp.738 | Journal eISSN: 2057-4991
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Language: English
Submitted on: Feb 16, 2024
Accepted on: Aug 22, 2024
Published on: Dec 9, 2024
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
learning,
zone of proximal development,
human-artificial intelligence augmentation

© 2024 Carsten Østerlund, Kevin Crowston, Corey B. Jackson, Yunan Wu, Alexander O. Smith, Aggelos K. Katsaggelos, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.

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