Um Estudo sobre a Aplicação de Técnicas de Gamificação em Aplicativo Crowdsourcing de Micro-tarefas
Resumo
Crowdsourcing é uma abordagem que utiliza o conhecimento das pessoas para resolver problemas. Existem diferentes tipos de crowdsourcing, um deles é conhecido como micro-tarefas, que são pequenas tarefas difíceis de serem resolvidas pelo computador, mas facilmente solucionadas pelas pessoas. No entanto, manter a motivação dos participantes é um desafio para o crowdsourcing. Para abordar esse desafio, a gamificação tem sido considerada uma abordagem promissora. Neste artigo, analisamos o impacto da gamificação na motivação das pessoas e os resultados mostraram um aumento na quantidade de micro-tarefas realizadas, após implementar técnicas de gamificação em um aplicativo móvel e realizar estudos com oito voluntários.
Referências
Alam, S. L. and Campbell, J. (2012). Crowdsourcing motivations in a not-for-profit glam context: the australian newspapers digitisation program.
Amorim, A. M. and Vieira, V. (2019). Exploratory study on the motivation of brazilian elderly people in crowdsourcing systems. In Proceedings of the 18th Brazilian Symposium on Human Factors in Computing Systems, pages 1–4.
Brabham, D. C. (2008). Crowdsourcing as a model for problem solving: An introduction and cases. Convergence: The International Journal of Research into New Media Technologies, 14(1):75–90.
Brabham, D. C. (2013). Using crowdsourcing in government. IBM Center for the Business of Government Washington, DC.
Brewer, R., Morris, M. R., and Piper, A. M. (2016). Why would anybody do this?”: Older adults’ understanding of and experiences with crowd work. Proceedings of CHI 2016.
CETIC.BR-NIC.BR (2021). Executive summary - survey on the use of information and communication technologies in brazilian households - ict households 2020. Regional Center for Studies on the Development of the Information Society – Cetic.br; Brazilian Network Information Center – NIC.br. Posted on November 25, 2021, available at: https://cetic.br/pt/pesquisa/domicilios/publicacoes/.
Chandler, D. and Kapelner, A. (2013). Breaking monotony with meaning: Motivation in crowdsourcing markets. Journal of Economic Behavior & Organization, 90:123–133.
Charmaz, K. (2014). Constructing Grounded Theory. SAGE Publications, Los Angeles, CA.
Chen, K.-W., Chang, Y.-J., and Chan, L. (2022). Predicting opportune moments to deliver notifications in virtual reality. In CHI Conference on Human Factors in Computing Systems, pages 1–18.
Chi, P.-Y., Batra, A., and Hsu, M. (2018). Mobile crowdsourcing in the wild: Challenges from a global community. In Proceedings of the 20th international conference on human-computer interaction with mobile devices and services adjunct, pages 410–415.
da Silva, A. V. D. and Vieira, V. (2018). Towards an api for user attention prediction in mobile notification overload. In Anais Estendidos do XXIV Simpósio Brasileiro de Sistemas Multimídia e Web, pages 13–17, Porto Alegre, RS, Brasil. SBC.
Deci, E. L. and Ryan, R. M. (1980). Self-determination theory: When mind mediates behavior. The Journal of mind and Behavior, pages 33–43.
Deci, E. L. and Ryan, R. M. (1985). Cognitive evaluation theory. In Intrinsic motivation and self-determination in human behavior, pages 43–85. Springer.
Deci, E. L. and Ryan, R. M. (2010). Intrinsic motivation. The corsini encyclopedia of psychology, pages 1–2.
Deterding, S., Sicart, M., Nacke, L., O’Hara, K., and Dixon, D. (2011). Gamification. using game-design elements in non-gaming contexts. In CHI ’11 Extended Abstracts on Human Factors in Computing Systems, CHI EA ’11, page 2425–2428, New York, NY, USA. Association for Computing Machinery.
Esteves, B., Fraser, K., Kulkarni, S., Conlan, O., and Rodriguez-Doncel, V. (2022). Now,later, never: A study of urgency in mobile push-notifications. In International Conference on Advances in Mobile Computing and Multimedia Intelligence, pages 38–44. Springer
Feng, Y., Ye, H. J., Yu, Y., Yang, C., and Cui, T. (2018). Gamification artifacts and crowdsourcing participation: Examining the mediating role of intrinsic motivations. Comput. Hum. Behav., 81:124–136.
Fitz, N., Kushlev, K., Jagannathan, R., Lewis, T., Paliwal, D., and Ariely, D. (2019). Batching smartphone notifications can improve well-being. Computers in Human Behavior, 101:84–94.
Gadiraju, U., Kawase, R., and Dietze, S. (2014). A taxonomy of microtasks on the web. In Proceedings of the 25th ACM Conference on Hypertext and Social Media, HT ’14, page 218–223, New York, NY, USA. Association for Computing Machinery.
Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6):1–4.
Kaufmann, N., Schulze, T., and Veit, D. (2011). More than fun and money: Worker
motivation in crowdsourcing-a study on mechanical turk.
Kobayashi, M., Arita, S., Itoko, T., Saito, S., and Takagi, H. (2015). Motivating multigenerational crowd workers in social-purpose work. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pages 1813–1824.
Law, E., Yin, M., Goh, J., Chen, K., Terry, M. A., and Gajos, K. Z. (2016). Curiosity killed the cat, but makes crowdwork better. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pages 4098–4110.
Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Research methods in human-computer interaction. Morgan Kaufmann, Cambridge, MA.
Lee, T. Y., Dugan, C., Geyer, W., Ratchford, T., Rasmussen, J., Shami, N. S., and Lupushor, S. (2013). Experiments on motivational feedback for crowdsourced workers.
Morschheuser, B., Hamari, J., and Koivisto, J. (2016). Gamification in crowdsourcing: a review. In 2016 49th Hawaii International Conference on System Sciences (HICSS), pages 4375–4384. IEEE.
Ooge, J., De Croon, R., Verbert, K., and Vanden Abeele, V. (2020). Tailoring gamification for adolescents: a validation study of big five and hexad in dutch. In Proceedings of the Annual Symposium on Computer-Human Interaction in Play, pages 206–218.
Park, S., Kwon, S., and Lee, U. (2018). Campuswatch: Exploring communitysourced patrolling with pervasive mobile technology. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW):1–25.
Pestana, M. C. and Vieira, V. (2016). Um modelo de distribuição de tarefas crowdsourcing sensível ao contexto para administração de campus universitário. In Anais Estendidos do XXII Simpósio Brasileiro de Sistemas Multimídia e Web, pages 23–28. SBC.
Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Oliveira, W., Avila-Santos, A. P., Gasparini, I., and Isotani, S. (2021). Personalization improves gamification: Evidence from a mixed-methods study. Proceedings of the ACM on Human-Computer Interaction, 5(CHI PLAY):1–25.
Sailer, M., Hense, J., Mandl, J., and Klevers, M. (2014). Psychological perspectives on motivation through gamification. Interaction Design and Architecture Journal, (19):28–37.
Stol, K.-J. and Fitzgerald, B. (2014). Two’s company, three’s a crowd: A case study of crowdsourcing software development. In Proceedings of the 36th International Conference on Software Engineering, ICSE 2014, page 187–198, New York, NY, USA. Association for Computing Machinery.
Toda, A., Klock, A., Pereira, F. D., Rodrigues, L. A., Palomino, P. T., Lopes, V., Stewart, C., Oliveira, E. H., Gasparini, I., Isotani, S., et al. (2022a). Towards the understanding of cultural differences in between gamification preferences: A data-driven comparison between the us and brazil. In Proceedings of the 15th International Conference on Educational Data Mining, page 560.
Toda, A., Palomino, P. T., Rodrigues, L., Klock, A. C., Pereira, F., Borges, S., Gasparini, I., Teixeira, E. H., Isotani, S., and Cristea, A. I. (2022b). Gamification through the looking glass-perceived biases and ethical concerns of brazilian teachers. In International Conference on Artificial Intelligence in Education, pages 259–262. Springer.
Tondello, G. F. and Nacke, L. E. (2020). Validation of user preferences and effects of personalized gamification on task performance. Frontiers in Computer Science, 2:29.
Tsvetkova, M., Muller, S., Vuculescu, O., Ham, H., and Sergeev, R. A. (2022). Relative feedback increases disparities in effort and performance in crowdsourcing contests: Evidence from a quasi-experiment on topcoder. Proceedings of the ACM on Human Computer Interaction, 6(CSCW2):1–27.
Vaughan, J. W. (2017). Making better use of the crowd: How crowdsourcing can advance machine learning research. J. Mach. Learn. Res., 18(1):7026–7071.
Walter, V., Kolle, M., and Collmar, D. (2022). A gamification approach for the improvement of paid crowd-based labelling of geospatial data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 5(4):113–120.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M., Regnell, B., and Wesslén, A. (2000). Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers, Norwell, MA, USA.
Zhang, X., Xia, E., Shen, C., and Su, J. (2022). Factors influencing solvers’ behaviors in knowledge-intensive crowdsourcing: A systematic literature review. Journal of Theoretical and Applied Electronic Commerce Research, 17(4):1297–1319.
Amorim, A. M. and Vieira, V. (2019). Exploratory study on the motivation of brazilian elderly people in crowdsourcing systems. In Proceedings of the 18th Brazilian Symposium on Human Factors in Computing Systems, pages 1–4.
Brabham, D. C. (2008). Crowdsourcing as a model for problem solving: An introduction and cases. Convergence: The International Journal of Research into New Media Technologies, 14(1):75–90.
Brabham, D. C. (2013). Using crowdsourcing in government. IBM Center for the Business of Government Washington, DC.
Brewer, R., Morris, M. R., and Piper, A. M. (2016). Why would anybody do this?”: Older adults’ understanding of and experiences with crowd work. Proceedings of CHI 2016.
CETIC.BR-NIC.BR (2021). Executive summary - survey on the use of information and communication technologies in brazilian households - ict households 2020. Regional Center for Studies on the Development of the Information Society – Cetic.br; Brazilian Network Information Center – NIC.br. Posted on November 25, 2021, available at: https://cetic.br/pt/pesquisa/domicilios/publicacoes/.
Chandler, D. and Kapelner, A. (2013). Breaking monotony with meaning: Motivation in crowdsourcing markets. Journal of Economic Behavior & Organization, 90:123–133.
Charmaz, K. (2014). Constructing Grounded Theory. SAGE Publications, Los Angeles, CA.
Chen, K.-W., Chang, Y.-J., and Chan, L. (2022). Predicting opportune moments to deliver notifications in virtual reality. In CHI Conference on Human Factors in Computing Systems, pages 1–18.
Chi, P.-Y., Batra, A., and Hsu, M. (2018). Mobile crowdsourcing in the wild: Challenges from a global community. In Proceedings of the 20th international conference on human-computer interaction with mobile devices and services adjunct, pages 410–415.
da Silva, A. V. D. and Vieira, V. (2018). Towards an api for user attention prediction in mobile notification overload. In Anais Estendidos do XXIV Simpósio Brasileiro de Sistemas Multimídia e Web, pages 13–17, Porto Alegre, RS, Brasil. SBC.
Deci, E. L. and Ryan, R. M. (1980). Self-determination theory: When mind mediates behavior. The Journal of mind and Behavior, pages 33–43.
Deci, E. L. and Ryan, R. M. (1985). Cognitive evaluation theory. In Intrinsic motivation and self-determination in human behavior, pages 43–85. Springer.
Deci, E. L. and Ryan, R. M. (2010). Intrinsic motivation. The corsini encyclopedia of psychology, pages 1–2.
Deterding, S., Sicart, M., Nacke, L., O’Hara, K., and Dixon, D. (2011). Gamification. using game-design elements in non-gaming contexts. In CHI ’11 Extended Abstracts on Human Factors in Computing Systems, CHI EA ’11, page 2425–2428, New York, NY, USA. Association for Computing Machinery.
Esteves, B., Fraser, K., Kulkarni, S., Conlan, O., and Rodriguez-Doncel, V. (2022). Now,later, never: A study of urgency in mobile push-notifications. In International Conference on Advances in Mobile Computing and Multimedia Intelligence, pages 38–44. Springer
Feng, Y., Ye, H. J., Yu, Y., Yang, C., and Cui, T. (2018). Gamification artifacts and crowdsourcing participation: Examining the mediating role of intrinsic motivations. Comput. Hum. Behav., 81:124–136.
Fitz, N., Kushlev, K., Jagannathan, R., Lewis, T., Paliwal, D., and Ariely, D. (2019). Batching smartphone notifications can improve well-being. Computers in Human Behavior, 101:84–94.
Gadiraju, U., Kawase, R., and Dietze, S. (2014). A taxonomy of microtasks on the web. In Proceedings of the 25th ACM Conference on Hypertext and Social Media, HT ’14, page 218–223, New York, NY, USA. Association for Computing Machinery.
Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6):1–4.
Kaufmann, N., Schulze, T., and Veit, D. (2011). More than fun and money: Worker
motivation in crowdsourcing-a study on mechanical turk.
Kobayashi, M., Arita, S., Itoko, T., Saito, S., and Takagi, H. (2015). Motivating multigenerational crowd workers in social-purpose work. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pages 1813–1824.
Law, E., Yin, M., Goh, J., Chen, K., Terry, M. A., and Gajos, K. Z. (2016). Curiosity killed the cat, but makes crowdwork better. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, pages 4098–4110.
Lazar, J., Feng, J. H., and Hochheiser, H. (2017). Research methods in human-computer interaction. Morgan Kaufmann, Cambridge, MA.
Lee, T. Y., Dugan, C., Geyer, W., Ratchford, T., Rasmussen, J., Shami, N. S., and Lupushor, S. (2013). Experiments on motivational feedback for crowdsourced workers.
Morschheuser, B., Hamari, J., and Koivisto, J. (2016). Gamification in crowdsourcing: a review. In 2016 49th Hawaii International Conference on System Sciences (HICSS), pages 4375–4384. IEEE.
Ooge, J., De Croon, R., Verbert, K., and Vanden Abeele, V. (2020). Tailoring gamification for adolescents: a validation study of big five and hexad in dutch. In Proceedings of the Annual Symposium on Computer-Human Interaction in Play, pages 206–218.
Park, S., Kwon, S., and Lee, U. (2018). Campuswatch: Exploring communitysourced patrolling with pervasive mobile technology. Proceedings of the ACM on Human-Computer Interaction, 2(CSCW):1–25.
Pestana, M. C. and Vieira, V. (2016). Um modelo de distribuição de tarefas crowdsourcing sensível ao contexto para administração de campus universitário. In Anais Estendidos do XXII Simpósio Brasileiro de Sistemas Multimídia e Web, pages 23–28. SBC.
Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Oliveira, W., Avila-Santos, A. P., Gasparini, I., and Isotani, S. (2021). Personalization improves gamification: Evidence from a mixed-methods study. Proceedings of the ACM on Human-Computer Interaction, 5(CHI PLAY):1–25.
Sailer, M., Hense, J., Mandl, J., and Klevers, M. (2014). Psychological perspectives on motivation through gamification. Interaction Design and Architecture Journal, (19):28–37.
Stol, K.-J. and Fitzgerald, B. (2014). Two’s company, three’s a crowd: A case study of crowdsourcing software development. In Proceedings of the 36th International Conference on Software Engineering, ICSE 2014, page 187–198, New York, NY, USA. Association for Computing Machinery.
Toda, A., Klock, A., Pereira, F. D., Rodrigues, L. A., Palomino, P. T., Lopes, V., Stewart, C., Oliveira, E. H., Gasparini, I., Isotani, S., et al. (2022a). Towards the understanding of cultural differences in between gamification preferences: A data-driven comparison between the us and brazil. In Proceedings of the 15th International Conference on Educational Data Mining, page 560.
Toda, A., Palomino, P. T., Rodrigues, L., Klock, A. C., Pereira, F., Borges, S., Gasparini, I., Teixeira, E. H., Isotani, S., and Cristea, A. I. (2022b). Gamification through the looking glass-perceived biases and ethical concerns of brazilian teachers. In International Conference on Artificial Intelligence in Education, pages 259–262. Springer.
Tondello, G. F. and Nacke, L. E. (2020). Validation of user preferences and effects of personalized gamification on task performance. Frontiers in Computer Science, 2:29.
Tsvetkova, M., Muller, S., Vuculescu, O., Ham, H., and Sergeev, R. A. (2022). Relative feedback increases disparities in effort and performance in crowdsourcing contests: Evidence from a quasi-experiment on topcoder. Proceedings of the ACM on Human Computer Interaction, 6(CSCW2):1–27.
Vaughan, J. W. (2017). Making better use of the crowd: How crowdsourcing can advance machine learning research. J. Mach. Learn. Res., 18(1):7026–7071.
Walter, V., Kolle, M., and Collmar, D. (2022). A gamification approach for the improvement of paid crowd-based labelling of geospatial data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 5(4):113–120.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M., Regnell, B., and Wesslén, A. (2000). Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers, Norwell, MA, USA.
Zhang, X., Xia, E., Shen, C., and Su, J. (2022). Factors influencing solvers’ behaviors in knowledge-intensive crowdsourcing: A systematic literature review. Journal of Theoretical and Applied Electronic Commerce Research, 17(4):1297–1319.
Publicado
22/05/2023
Como Citar
MEIJON, Iago; AMORIM, Ana Maria; RIBEIRO, Ailton; PESTANA, Maria Clara; VIEIRA, Vaninha.
Um Estudo sobre a Aplicação de Técnicas de Gamificação em Aplicativo Crowdsourcing de Micro-tarefas. In: SIMPÓSIO BRASILEIRO DE SISTEMAS COLABORATIVOS (SBSC), 18. , 2023, Rio de Janeiro/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 57-71.
ISSN 2326-2842.
DOI: https://doi.org/10.5753/sbsc.2023.229082.
