Clearing up uncertainties in graduate programs candidate selection using a data science approach
Resumo
Brazilian Graduate Programs are evaluated by a specific foundation, CAPES. This evaluation qualifies the respective program with a grade, and this directly influences the permissions and funds assigned to this program, such as having a doctorate level, grading 4 or higher. One of the indicators is the student body, as an external variable outside the control of the program. Based on the Design Science Research methodology, we present a research on the construction of an artifact that clears up the selection of candidates for the programs, categorizing them according to the profiles of previous students, based on descriptive statistics and data analytics.
Palavras-chave:
Candidate students selection, Brazilian graduate programs, Data Science
Referências
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Elam, J. J., Jarvenpaa, S. L., and Schkad, D. A. (1992). Behavioral decision theory and DSS: New opportunities for collaborative research. In Information Systems and Decision Processes, pages 51–74, Los Alimotos, CA.
Fong, S. and Biuk-Aghai, R. (2009). An automated university admission recommender system for secondary school students. In The 6th International Conference on Information Technology and Applications (ICITA 2009). ICITA.
Grus, J. (2018). Data Science from Scratch: First Principles with Python. O’Reilly, USA.
Hevner, A. R. (2007). A three-cycle view of design science research. Scandinavian Journal of Information Systems, 19(4):87–92.
Junior, R. K. R. and Cegielski, C. (2015). Introdução a Sistemas de Informação. Apoiando e transformando negócios na era da mobilidade. CAMPUS, 5th edition.
Luhn, H. P. (1958). A Business Intelligence System. IBM Journal of Research and Development. 2(4):314–319. doi:10.1147/rd.24.0314.
March, J. G. and Simon, H. A. (1993). Organizations. Wiley-Blackwell, 2nd edition.
O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group, New York, NY, USA.
Peffers, K., Tuunanen, T., Rothenberger, M. A., and Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3):45–77.
Pimentel, M. (2017). Design science research e pesquisas com os cotidianos escolares para fazer pensar as pesquisas em informática na educação. In Anais do SBIE 2017, pages 414–424. SBC.
Pimentel, M., Filippo, D., and Santoro, F. M. (2019). Design science research: fazendo pesquisas científicas rigorosas atreladas ao desenvolvimento de artefatos computacionais projetados para a educação. Metodologia de Pesquisa em Informática na Educação: Concepção da Pesquisa., 1(5):414–424.
Premkumar, G., Ramamurthy, K., and Saunders, C. S. (2005). Information processing view of organizations: An exploratory examination of fit in the context of interorganizational relationships. Journal of Management Information Systems, 22(1):257–294.
Provost, F. and Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O’Reilly Media.
Rabelo, H., Burlamaqui, A., Valentim, R., de Souza Rabelo, D. S., and Medeiros, S. (2017). Utilização de técnicas de mineração de dados educacionais para predição de desempenho de alunos de EAD em ambientes virtuais de aprendizagem. In Anais do SBIE 2017, pages 1527–1536. SBC.
Recker, J. (2013). Scientific Research in Information Systems A Beginner’s Guide. Springer, Berlin.
Stair, R. and Reynolds, G. (2018). Principles of Information Systems. Cengage Learning, 13rd edition.
Sumpter, D. (2018). Outnumbered: From Facebook and Google to Fake News and Filter-bubbles – The Algorithms That Control Our Lives. Bloomsbury Sigma.
Turban, E., Delen, D., Sharda, R., and King, D. (2011). Business Intelligence: A Manage-rial Approach. Person Higher Ed, 4th edition.
Wieringa, R. (2014). Design Science Methodology for Information Systems and Software Engineering. Springer-Verlag Berlin Heidelberg
Benbassat, J. and Baumal, R. (2007). Uncertainties in the selection of applicants for medical school. Advances in Health Sciences Education, 12(4):509–521.
Carvalho, L. P., Raposo, G., Cappelli, C., Miceli, C. (2019) An analysis of female participation in informatics research at UFRJ’s PPGI. In 2019 Escola Regional de Sistemas de Informação (ERSI), Duque de Caxias. SBC, Porto Alegre.
CAPES (2017). Ordinance nº 59, 21/03/2017, https://capes.gov.br/images/stories/download/avaliacao/27032017-Portaria-59-21-03-2017-Regulamento-da-Avaliacao-Quadrienal.pdf . BRAZIL, Education Ministry. Available in 17/03/2020.
Clemen, R. and Reilly, T. (2014). Making Hard Decisions with Decision Tools. Cengage Learning, 3rd edition.
De Villiers, M. R. R. and Harpur, P. A. (2013). Design-based research-the educational technology variant of design research: Illustrated by the design of an m-learning environment. In Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference, SAICSIT ’13, pages 252–261, New York, NY, USA. ACM.
Elam, J. J., Jarvenpaa, S. L., and Schkad, D. A. (1992). Behavioral decision theory and DSS: New opportunities for collaborative research. In Information Systems and Decision Processes, pages 51–74, Los Alimotos, CA.
Fong, S. and Biuk-Aghai, R. (2009). An automated university admission recommender system for secondary school students. In The 6th International Conference on Information Technology and Applications (ICITA 2009). ICITA.
Grus, J. (2018). Data Science from Scratch: First Principles with Python. O’Reilly, USA.
Hevner, A. R. (2007). A three-cycle view of design science research. Scandinavian Journal of Information Systems, 19(4):87–92.
Junior, R. K. R. and Cegielski, C. (2015). Introdução a Sistemas de Informação. Apoiando e transformando negócios na era da mobilidade. CAMPUS, 5th edition.
Luhn, H. P. (1958). A Business Intelligence System. IBM Journal of Research and Development. 2(4):314–319. doi:10.1147/rd.24.0314.
March, J. G. and Simon, H. A. (1993). Organizations. Wiley-Blackwell, 2nd edition.
O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishing Group, New York, NY, USA.
Peffers, K., Tuunanen, T., Rothenberger, M. A., and Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3):45–77.
Pimentel, M. (2017). Design science research e pesquisas com os cotidianos escolares para fazer pensar as pesquisas em informática na educação. In Anais do SBIE 2017, pages 414–424. SBC.
Pimentel, M., Filippo, D., and Santoro, F. M. (2019). Design science research: fazendo pesquisas científicas rigorosas atreladas ao desenvolvimento de artefatos computacionais projetados para a educação. Metodologia de Pesquisa em Informática na Educação: Concepção da Pesquisa., 1(5):414–424.
Premkumar, G., Ramamurthy, K., and Saunders, C. S. (2005). Information processing view of organizations: An exploratory examination of fit in the context of interorganizational relationships. Journal of Management Information Systems, 22(1):257–294.
Provost, F. and Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. O’Reilly Media.
Rabelo, H., Burlamaqui, A., Valentim, R., de Souza Rabelo, D. S., and Medeiros, S. (2017). Utilização de técnicas de mineração de dados educacionais para predição de desempenho de alunos de EAD em ambientes virtuais de aprendizagem. In Anais do SBIE 2017, pages 1527–1536. SBC.
Recker, J. (2013). Scientific Research in Information Systems A Beginner’s Guide. Springer, Berlin.
Stair, R. and Reynolds, G. (2018). Principles of Information Systems. Cengage Learning, 13rd edition.
Sumpter, D. (2018). Outnumbered: From Facebook and Google to Fake News and Filter-bubbles – The Algorithms That Control Our Lives. Bloomsbury Sigma.
Turban, E., Delen, D., Sharda, R., and King, D. (2011). Business Intelligence: A Manage-rial Approach. Person Higher Ed, 4th edition.
Wieringa, R. (2014). Design Science Methodology for Information Systems and Software Engineering. Springer-Verlag Berlin Heidelberg
Publicado
30/06/2020
Como Citar
COSTA, Evaldo B.; RAPOSO, Giselle; DA S. FILHO, Jose B.; CARVALHO, Luiz Paulo; VASCONCELLOS, Wander dos S.; DE FARIAS, Claudio Miceli.
Clearing up uncertainties in graduate programs candidate selection using a data science approach. In: WORKSHOP SOBRE AS IMPLICAÇÕES DA COMPUTAÇÃO NA SOCIEDADE (WICS), 1. , 2020, Cuiabá.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 13-24.
ISSN 2763-8707.
DOI: https://doi.org/10.5753/wics.2020.11033.
