Papers

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2019
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)
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
PDF icon Impacts_of_machine_learning_on_work__revision_.pdf (300.76 KB)
2011
Prestopnik, N., & Crowston, K.. (2011). Gaming for (citizen) science: Exploring motivation and data quality in the context of crowdsourced science through the design and evaluation of a social-computational system. In “Computing for Citizen Science” workshop at the IEEE eScience Conference. Presented at the “Computing for Citizen Science” workshop at the IEEE eScience Conference, Stockholm, Sweden. Retrieved de http://itee.uq.edu.au/~eresearch/workshops/compcitsci2011/index.html
PDF icon gamingforcitizenscience_ver6.pdf (217.69 KB)
2006
Crowston, K., & Scozzi, B.. (2006). The role of mental models in FLOSS development work practices. In Proceedings of the IFIP 2nd International Conference on Open Source Software (pp. 91-97). Lake Como, Italy, 8–9 June.
PDF icon oss2006crowstonscozzi.pdf (160.74 KB)