Dolata, M., Schwabe, G., & Crowston, K. (2019). Getting your data refinery ready to work: Insights from cognitive application development projects.
First name
Kevin
Last name
Crowston
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
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
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
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
Harandi, M., Crowston, K., Jackson, C., & Østerlund, C. (2020). The Genie in the Bottle: Different Stakeholders, Different Interpretations of Machine Learning. In Hawai’i International Conference on System Science. https://doi.org/10.24251/HICSS.2020.719
Crowston, K., Østerlund, C., Lee, T. K., Jackson, C. B., Harandi, M., Allen, S., Bahaadini, S., Coughlin, S., Katsaggelos, A., Larson, S., Rohani, N., Smith, J., Trouille, L., & Zevin, M. (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
Harandi, M., Crowston, K., Jackson, C. B., & Østerlund, C. (2018). Perceptions of Machine Learning: The genie in the bottle.
Eseryel, Y., Wei, K., & Crowston, K. (2020). Decision-Making Processes in Community-based Free/Libre Open Source Software Development Teams with Internal Governance: An Extension to Decision-Making Theory. Communications of the Association for Information Systems, 46. https://doi.org/10.17705/1CAIS.04620