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Crowston, K., & Bolici, F.. (2020). Impacts of the Use of Machine Learning on Work Design. In 8th International Conference on Human-Agent Interaction. https://doi.org/10.1145/3406499.3415070
PDF icon Impacts_of_ML_for_HAI_2020.pdf (453.59 KB)
Crowston, K., Østerlund, C., Lee, T. Kyoung, Jackson, C. B., Harandi, M., Allen, S., et al.. (2020). Knowledge Tracing to Model Learning in Online Citizen Science Projects. Ieee Transactions On Learning Technologies, 13, 123-134. https://doi.org/10.1109/TLT.2019.2936480
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Crowston, K. (2020). Lessons for Supporting Data Science from the Everyday Automation Experience of Spell-Checkers. In Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual. Presented at the Automation Experience across Domains (AutomationXP20), CHI'20 Workshop, 26 April 2020, Virtual, Virtual workshop.
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Saltz, J., Crowston, K., Heckman, R., & Hegde, Y.. (2020). MIDST: An enhanced development environment that improves the maintainability of a data science analysis. International Journal Of Information Systems And Project Management, 8(3). https://doi.org/10.12821/ijispm080301
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You, S., Crowston, K., Saltz, J., & Hegde, Y.. (2019). Coordination in OSS 2.0: ANT Approach. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.120
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Saltz, J., Heckman, R., Crowston, K., You, S., & Hegde, Y.. (2019). Helping data science students develop task modularity. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.134
PDF icon modularity-HICSS-final-afterReview.pdf (242.49 KB)
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Crowston, K., & Bolici, F.. (2019). Impacts of machine learning on work. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.719
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Dalgali, A., & Crowston, K.. (2019). Sharing open deep learning models. In Proceedings of the 52nd Hawai'i International Conference on System Sciences (HICSS-52). https://doi.org/10.24251/HICSS.2019.256
PDF icon Hicss paper2018_DalgaliCrowston.pdf (669.11 KB)
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Crowston, K., Mitchell, E. Michelle, & Østerlund, C.. (2018). Coordinating advanced crowd work: Extending citizen science. In Hawai'i International Conference on System Sciences (51st ed.). https://doi.org/10.24251/HICSS.2018.212
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Jackson, C. B., Crowston, K., & Østerlund, C.. (2018). Did they login? Patterns of anonymous contributions to online communities. Proceedings Of The Acm On Human-Computer Interaction, 2(CSCW), Article 77. https://doi.org/10.1145/3274346
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Jackson, C. B., Crowston, K., Østerlund, C., & Harandi, M.. (2018). Folksonomies to support coordination and coordination of folksonomies. Computer Supported Cooperative Work, 27(3–6), 647–678. https://doi.org/10.1007/s10606-018-9327-z
PDF icon ECSCW-Paper-Final.pdf (2.14 MB)
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Crowston, K., & Fagnot, I.. (2018). Stages of motivation for contributing user-generated content: A theory and empirical test. International Journal Of Human-Computer Studies, 109, 89-101. https://doi.org/10.1016/j.ijhcs.2017.08.005
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Curty, R. G., Crowston, K., Specht, A., Grant, B., & Walton, E. D.. (2017). Attitudes and norms affecting scientists’ data reuse. Plos One, 12(12). https://doi.org/10.1371/journal.pone.0189288
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Crowston, K., Østerlund, C., & Lee, T. Kyoung. (2017). Blending machine and human learning processes. In Hawai'i International Conference on System Sciences. https://doi.org/10.24251/HICSS.2017.009
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