@article {9999,
	title = {Gamers, citizen scientists, and data: Exploring participant contributions in two games with a purpose},
	journal = {Computers in Human Behavior},
	volume = {68},
	year = {2017},
	pages = {254{\textendash}268},
	abstract = {<p>Two key problems for crowd-sourcing systems are motivating contributions from participants and ensuring the quality of these contributions. Games have been suggested as a motivational approach to encourage contribution, but attracting participation through game play rather than intrinsic interest raises concerns about the quality of the contributions provided. These concerns are particularly important in the context of citizen science projects, when the contributions are data to be used for scientific research. To assess the validity of concerns about the effects of gaming on data quality, we compare the quality of data obtained from two citizen science games, one a {\textquotedblleft}gamified{\textquotedblright} version of a species classification task and one a fantasy game that used the classification task only as a way to advance in the game play. Surprisingly, though we did observe cheating in the fantasy game, data quality (i.e., classification accuracy) from participants in the two games was not significantly different. As well, data from short-time contributors was also at a usable level of accuracy. Finally, learning did not seem to affect data quality in our context. These findings suggest that various approaches to gamification can be useful for motivating contributions to citizen science projects.</p>},
	doi = {10.1016/j.chb.2016.11.035},
	attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/chb2016.pdf},
	author = {Nathan Prestopnik and Kevin Crowston and Wang, Jun}
}
@conference {2011,
	title = {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},
	booktitle = {{\textquotedblleft}Computing for Citizen Science{\textquotedblright} workshop at the IEEE eScience Conference},
	year = {2011},
	month = {12/2011},
	address = {Stockholm, Sweden},
	abstract = {In this paper, an ongoing design research project is described. Citizen Sort, currently under development, is a web-based social-computational system designed to support a citizen science task, the taxonomic classification of various insect, animal, and plant species. In addition to supporting this natural science objective, the Citizen Sort platform will also support information science research goals on the nature of motivation for social-computation and citizen science. In particular, this research program addresses the use of games to motivate participation in social-computational citizen science, and explores the effects of system design on motivation and data quality. A design science approach, where IT artifacts are developed to solve problems and answer research questions is described. Research questions, progress on Citizen Sort planning and implementation, and key challenges are discussed.},
	keywords = {Citizen Science, data quality, Design, Design Science, Games, Gaming, Motivation, Participation, Social Computational Systems},
	url = {http://itee.uq.edu.au/~eresearch/workshops/compcitsci2011/index.html},
	attachments = {https://crowston.syr.edu./sites/crowston.syr.edu/files/gamingforcitizenscience_ver6.pdf},
	author = {Nathan Prestopnik and Kevin Crowston}
}
