Uma Metodologia de Avaliação da Relação entre Perfis de Personalidade e Desempenho Acadêmico em Alunos de Sistemas de Informação
Resumo
O objetivo deste artigo é compreender como perfis distintos de personalidade podem ser relacionados a diferentes desempenhos acadêmicos e níveis de habilidade em disciplinas de gestão, computação e matemática em estudantes de graduação em Sistemas de Informação. Com uma abordagem metodológica interdisciplinar, a pesquisa utiliza a teoria de tipos psicológicos de C. G. Jung para avaliar como predisposições de personalidade se ligam às diversas competências requeridas de um acadêmico em Sistemas de Informação.
Palavras-chave:
Fatores Humanos, Perfis Psicológicos, Desempenho Acadêmico
Referências
Barbosa, F., Maciel, L. M. Z., Vieira, E. M., Marques, P. M. A., Jr., J. E. and Muglia, V. F. 2010. Radiological reports: A comparison between the transmission eficiency of information in free text and in structured reports. Clinic Science 65, 1 , 15- 21.
Barcelos, L. P., Santos, R. S., Lima, P.S., de Paula, N. M A. and Reis, A. S. 2010. Os Genes BRCA1 e BRCA2 e Suas Relações Genéticas na Predisposição aos Carcinomas Mamários Hereditários e Esporádicos. Estudos (Goiânia. Online), pp. v. 37, p. 837-850..
Boaventura, R. S. 2009. Um Sistema de Consulta Orientado por Ontologia Para Auxiliar Estudantes na Interpretação de Mamogramas e Diagnóstico de Câncer de Mama Via Web. Revista CEPPG. 20, p. 182 - 195.
Bodenreider O. 2004. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res 2004, 32:D267-270.
Boyd, N. F., Byng, J. W., Jong, R. A., Fishell, E. K., Little, L. E., Miller, A. B., Lockwood, G. A., Tritchler, D. L. and Yaffe, M. J.: Quantitative classification of mammographic densities and breast cancer risk. J Natl Cancer Inst. 87:670-5: 1995.
Brazilian Cancer Institute, I. Available at: http://www.inca.gov.br
Breitman, K. 2005. Web Semântica, a Internet do Futuro. 1. s.l.: LTC - Livros Técnicos Científicos SA.
Bulu, H., Alpkocak, A. and Balci, P. 2012. Ontologybased mammography annotation and Case-based Retrieval of breast masses. Elsevier. Expert Systems with Application.
Bulu, H., Alpkocak, A. and Balci, P. 2013. Uncertainty Modeling for Ontology-based Mammography Annotation with Intelligent BI-RADS Scoring. Computers in Biology and Medicine, Vol.43, Issue.4, pp.301-3011.
Cancer Org. Available at: http://www.cancer.org/breastcancer/
Cheng, H., Cai, X., Chen, X., Hu, L. and Lou, X. 2003. Computer-Aided Detection and Classification of Microcalcifications in Mammograms: A Survey. Pattern Recognition, 36 (12), pp 2967-2991.
Dalton, L. W. Pinder, S. E. Elston, C. E. Ellis, I. O. Page, D. L Dupont, W. D. and Blamey, R. W. 2000. Histologic grading of breast cancer: linkage of patient outcome with level of pathologist agreement. Mod Pathol, Vol. 13, pp. 730-5.
Dasmahapatra, S. and O'Hara. 2006. Interpretations of Ontologies for Breast Cancer. Interpretations of Ontologies for Breast Cancer. TripleC, 4, (2),293-303. Kieron.
Dasmahapatra, S., Dupplaw, D., Hu, B., Lewis, H., Lewis, P. and Shadbolt, N. 2004. Facilitating Multi-Disciplinary Knowledge-Based Support for Breast Cancer Screening. Intl. Journal of Healthcare Technology and Management .
Dridi, O. and Ahmed, B. M. 2008. Building an Ontology- Based Framework for Semantic Information Retrieval: Application to Breast Cancer. In: 3rd Intern. Conf. on Information and Communication Technologies: from Theory to applications. Damascus: ICTTA, pp. 1–6.
Ellis, I. O. 2005. Pathology Reporting of Breast Disease: A Joint Document Incorporating the Third Edition of the NHS Breast Screening Programme’s Guidelines for Pathology Reporting in Breast Cancer Screening and the Second Edition of The Royal College of Pathologists’ Minimum Dataset for Breast Cancer Histopathology. Sheffi eld.; NHS Cancer Screening Programmes and The Royal College of Pathologists; January 2005.
Elston, C. W. and Ellis, I. O. 1991. Pathological Prognostic Factors In Breast Cancer. The Value Of Histological Grade In Breast Cancer: Experience From A Large Study With Long-Term Follow-Up. Histopathology, 19:403-410.
Genestie, C. Zafrani, B. Asselain, B. Fourquet, A. Rozan, S. Validire, P. Vincent-Salomon, A. and Sastre-Garau, X. 1998. Comparison of the prognostic value of Scarff- Bloom-Richardson and Nottingham histological grades in a series of 825 cases of breast cancer: major importance of the mitotic count as a component of both grading systems. Anticancer Res, Vol. 18, pp. 571-6.
Guliato, D., Boaventura, R., Maia, M. A., Rangayyan, R., Simedo, M. and Macedo, T. A. A. 2009. INDIAM an e- Learning System for the Interpretation of Mammograms. Journal of Digital Imaging, v. 22, p. 405-420.
Hu, B., Dasmahapatra S, Lewis P. and Shadbolt N. 2003. Ontology-based medical image annotation with description logics. IEEE ICTAI'03, November 3--5, pp.77--82.
Hussein, R., Engelmann, U. Schroeter, A. and Meinzer, H. 2004. Dicom Structured Reporting. part 1: overview and characteristics. RadioGraphics 24, pp, 981- 986.
Hwang K., H., Lee, H. and Choi, D. 2012. Medical image retrieval: Past and present. Health Information Research 18(1) 3–9.
INCA. National Cancer Institute / Healthy Ministry, 2013. Estimative 2014 (In Portuguese).
Kondylakis, H., Analyti, A. and Plexousakis, D. 2007 Quete: Ontology-Based Query System for Distributed Sources. ADBIS, volume 4690 Lecture Notes in Computer Science, pp. 359-375. Springer.
Langlotz, C. and Meininger, L. Enhancing the Expressiveness and Usability of Structured Image Reporting Systems. Procedings AMIA annu Fall Sym, pp, 467 - 471.
Li, S., Ting, N. S., Zheng, L. and Chen, P. 2000. Functional link of BRCA1 and ataxia telangiectasia gene product in DNA damage response. Nature, n. 406, p.210- 215.
Maffon, H. P., Melo, J. S., Morais, T. A., Klavdianos, P. B., Brasil, L. M., Amaral, T. L. and Curilem, G. M. 2013.
Architecture of an Intelligent Tutoring System Applied to the Breast Cancer Based on Ontology, Artificial Neural Networks and Expert Systems ACHI 2013: The Sixth International Conference on Advances in Computer- Human Interactions.
Meriem, B. and Yamina, T. 2012. Interpretation breast cancer imaging by using ontology. Cyber Journals: Multidisciplinary Journals in Science and Technology. Journal of Selected Areas in Bioengineering (JSAB). p. March Edition.
Mustafa, J., Khan, S and Latif K. 2008. Ontology based semantic information retrieval. Intelligent Systems. IS'08. 4th International IEEE Conference 3, 22-14.
Pickler, M. E. V. 2007. Web Semântica: Ontologias como Ferramentas de Representação do Conhecimento Belo Horizonte: v. 12, n. 1. Perspectiva em Ciência da Informação. pp. 65-83.
Rakha, E. A., Reis-Filho, J. S., Baehner, F., Dabbs, D. J., Decker, T., Eusebi, V. Fox, S. B., Ichihara, S., Jacquemier, J., Lakhani, S. R., Palacios, J., Richardson, A. L., Schnitt, S. J., Schmitt, F. C., Tan, P. H., Tse, G. M., Badve, S. and Ellis, I. O. 2010. Breast cancer prognostic classification in the molecular era: the role of histological grade. 4, Breast Cancer Research, Vol. 12, p. 207, 2010.
Rosse, C. and Mejino, J.L.F. 2003. The Foundational Model of Anatomy ontology. In Anatomy Ontologies for Bioinformatics (eds. Burger, A. et al.) (Springer, New York, in the press).
Rubin, D.L. 2008. Creating and curating a terminology for radiology: ontology modeling and analysis. J Digit Imaging, 21:355-62.
Serna, A., Gerrikagoitia, J. K. and Huerga, I. 2009. Supporting Clinical Processes with Semantic Web Technologies: A Case in Breast Cancer Treatment. Inderscience publishers, International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 5, pp. 309–320.
Serna, A., Gerrikagoitia, J. K., Huerga, I. Zumalakarregi, J. A. and Pijoan, J. I. 2009.Archetypes and Ontologies to Facilitate the Breast Cancer Identification and Treatment Process. 1st Symposium on Healthcare Systems Interoperability. Madrid, Spain.
Shadbolt, N., Lewis, P., Dasmahapatra, S., Dupplaw, D., Hu, B. and Lewis, H. 2004. MIAKT: Combining grid and web services for collaborative medical decision making. In Proceedings of AHM2004 UK e Science All Hands Meeting .
Shehzad, A., Ngo, H. Q, Pham, K. A. and Lee, S. Y. 2004. Formal Modeling in Context Aware Systems. Proceedings of the First International Workshop on Modeling and Retrieval of Context.
SNOMED SNOMED CT, http://www.nlm.nih.gov.research/umls/Snomed.snomed_main.html
Tavassoli, F. A. and Devilee, P. 2003. World Health Organization classification of tumours. In Pathology and Genetics Tumours of the Breast and Female Genital Organs. Lyon: IARC Press; 19-23.
The Gene Ontology Consortium: Gene Ontology: tool for the unification of biology. Nature Genet 2000, 25:25-29.
Tutac, A. E. Racoceanu, D. Putti, T. Xiong, W. Leow, W. K. and Cretu, V. 2008. Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology Images. Int. Conf. on Biomedical Engineering and Informatics (BMEI). 5 de 2008, pp. 27-30.
Uschold, M. and Gruninger, M. 1996. Principles methods and applications. Knowledge Engeneering Review, pp. 11:93-136.
Vallet, D., Fernández, M. and Castells, P. 2005. An Ontology-Based Information Retrieval Model. Second European Semantic Web Conference, ESWC 2005, Heraklion, Crete, Greece, pp 455-470.
VisualLab avaliable in: http://visual.ic.uff.br.
Wang, X.H., Zhang, D.Q., Gu, T. and Pung, H.K. 2004. Ontology based context modeling and reasoning using OWL. Proceedings of 2nd IEEE Conf. Pervasive Computing and Communications (PerCom 2004), Workshop on Context Modeling and Reasoning. pp 18-22.
Barcelos, L. P., Santos, R. S., Lima, P.S., de Paula, N. M A. and Reis, A. S. 2010. Os Genes BRCA1 e BRCA2 e Suas Relações Genéticas na Predisposição aos Carcinomas Mamários Hereditários e Esporádicos. Estudos (Goiânia. Online), pp. v. 37, p. 837-850..
Boaventura, R. S. 2009. Um Sistema de Consulta Orientado por Ontologia Para Auxiliar Estudantes na Interpretação de Mamogramas e Diagnóstico de Câncer de Mama Via Web. Revista CEPPG. 20, p. 182 - 195.
Bodenreider O. 2004. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res 2004, 32:D267-270.
Boyd, N. F., Byng, J. W., Jong, R. A., Fishell, E. K., Little, L. E., Miller, A. B., Lockwood, G. A., Tritchler, D. L. and Yaffe, M. J.: Quantitative classification of mammographic densities and breast cancer risk. J Natl Cancer Inst. 87:670-5: 1995.
Brazilian Cancer Institute, I. Available at: http://www.inca.gov.br
Breitman, K. 2005. Web Semântica, a Internet do Futuro. 1. s.l.: LTC - Livros Técnicos Científicos SA.
Bulu, H., Alpkocak, A. and Balci, P. 2012. Ontologybased mammography annotation and Case-based Retrieval of breast masses. Elsevier. Expert Systems with Application.
Bulu, H., Alpkocak, A. and Balci, P. 2013. Uncertainty Modeling for Ontology-based Mammography Annotation with Intelligent BI-RADS Scoring. Computers in Biology and Medicine, Vol.43, Issue.4, pp.301-3011.
Cancer Org. Available at: http://www.cancer.org/breastcancer/
Cheng, H., Cai, X., Chen, X., Hu, L. and Lou, X. 2003. Computer-Aided Detection and Classification of Microcalcifications in Mammograms: A Survey. Pattern Recognition, 36 (12), pp 2967-2991.
Dalton, L. W. Pinder, S. E. Elston, C. E. Ellis, I. O. Page, D. L Dupont, W. D. and Blamey, R. W. 2000. Histologic grading of breast cancer: linkage of patient outcome with level of pathologist agreement. Mod Pathol, Vol. 13, pp. 730-5.
Dasmahapatra, S. and O'Hara. 2006. Interpretations of Ontologies for Breast Cancer. Interpretations of Ontologies for Breast Cancer. TripleC, 4, (2),293-303. Kieron.
Dasmahapatra, S., Dupplaw, D., Hu, B., Lewis, H., Lewis, P. and Shadbolt, N. 2004. Facilitating Multi-Disciplinary Knowledge-Based Support for Breast Cancer Screening. Intl. Journal of Healthcare Technology and Management .
Dridi, O. and Ahmed, B. M. 2008. Building an Ontology- Based Framework for Semantic Information Retrieval: Application to Breast Cancer. In: 3rd Intern. Conf. on Information and Communication Technologies: from Theory to applications. Damascus: ICTTA, pp. 1–6.
Ellis, I. O. 2005. Pathology Reporting of Breast Disease: A Joint Document Incorporating the Third Edition of the NHS Breast Screening Programme’s Guidelines for Pathology Reporting in Breast Cancer Screening and the Second Edition of The Royal College of Pathologists’ Minimum Dataset for Breast Cancer Histopathology. Sheffi eld.; NHS Cancer Screening Programmes and The Royal College of Pathologists; January 2005.
Elston, C. W. and Ellis, I. O. 1991. Pathological Prognostic Factors In Breast Cancer. The Value Of Histological Grade In Breast Cancer: Experience From A Large Study With Long-Term Follow-Up. Histopathology, 19:403-410.
Genestie, C. Zafrani, B. Asselain, B. Fourquet, A. Rozan, S. Validire, P. Vincent-Salomon, A. and Sastre-Garau, X. 1998. Comparison of the prognostic value of Scarff- Bloom-Richardson and Nottingham histological grades in a series of 825 cases of breast cancer: major importance of the mitotic count as a component of both grading systems. Anticancer Res, Vol. 18, pp. 571-6.
Guliato, D., Boaventura, R., Maia, M. A., Rangayyan, R., Simedo, M. and Macedo, T. A. A. 2009. INDIAM an e- Learning System for the Interpretation of Mammograms. Journal of Digital Imaging, v. 22, p. 405-420.
Hu, B., Dasmahapatra S, Lewis P. and Shadbolt N. 2003. Ontology-based medical image annotation with description logics. IEEE ICTAI'03, November 3--5, pp.77--82.
Hussein, R., Engelmann, U. Schroeter, A. and Meinzer, H. 2004. Dicom Structured Reporting. part 1: overview and characteristics. RadioGraphics 24, pp, 981- 986.
Hwang K., H., Lee, H. and Choi, D. 2012. Medical image retrieval: Past and present. Health Information Research 18(1) 3–9.
INCA. National Cancer Institute / Healthy Ministry, 2013. Estimative 2014 (In Portuguese).
Kondylakis, H., Analyti, A. and Plexousakis, D. 2007 Quete: Ontology-Based Query System for Distributed Sources. ADBIS, volume 4690 Lecture Notes in Computer Science, pp. 359-375. Springer.
Langlotz, C. and Meininger, L. Enhancing the Expressiveness and Usability of Structured Image Reporting Systems. Procedings AMIA annu Fall Sym, pp, 467 - 471.
Li, S., Ting, N. S., Zheng, L. and Chen, P. 2000. Functional link of BRCA1 and ataxia telangiectasia gene product in DNA damage response. Nature, n. 406, p.210- 215.
Maffon, H. P., Melo, J. S., Morais, T. A., Klavdianos, P. B., Brasil, L. M., Amaral, T. L. and Curilem, G. M. 2013.
Architecture of an Intelligent Tutoring System Applied to the Breast Cancer Based on Ontology, Artificial Neural Networks and Expert Systems ACHI 2013: The Sixth International Conference on Advances in Computer- Human Interactions.
Meriem, B. and Yamina, T. 2012. Interpretation breast cancer imaging by using ontology. Cyber Journals: Multidisciplinary Journals in Science and Technology. Journal of Selected Areas in Bioengineering (JSAB). p. March Edition.
Mustafa, J., Khan, S and Latif K. 2008. Ontology based semantic information retrieval. Intelligent Systems. IS'08. 4th International IEEE Conference 3, 22-14.
Pickler, M. E. V. 2007. Web Semântica: Ontologias como Ferramentas de Representação do Conhecimento Belo Horizonte: v. 12, n. 1. Perspectiva em Ciência da Informação. pp. 65-83.
Rakha, E. A., Reis-Filho, J. S., Baehner, F., Dabbs, D. J., Decker, T., Eusebi, V. Fox, S. B., Ichihara, S., Jacquemier, J., Lakhani, S. R., Palacios, J., Richardson, A. L., Schnitt, S. J., Schmitt, F. C., Tan, P. H., Tse, G. M., Badve, S. and Ellis, I. O. 2010. Breast cancer prognostic classification in the molecular era: the role of histological grade. 4, Breast Cancer Research, Vol. 12, p. 207, 2010.
Rosse, C. and Mejino, J.L.F. 2003. The Foundational Model of Anatomy ontology. In Anatomy Ontologies for Bioinformatics (eds. Burger, A. et al.) (Springer, New York, in the press).
Rubin, D.L. 2008. Creating and curating a terminology for radiology: ontology modeling and analysis. J Digit Imaging, 21:355-62.
Serna, A., Gerrikagoitia, J. K. and Huerga, I. 2009. Supporting Clinical Processes with Semantic Web Technologies: A Case in Breast Cancer Treatment. Inderscience publishers, International Journal of Metadata, Semantics and Ontologies (IJMSO), Vol. 5, pp. 309–320.
Serna, A., Gerrikagoitia, J. K., Huerga, I. Zumalakarregi, J. A. and Pijoan, J. I. 2009.Archetypes and Ontologies to Facilitate the Breast Cancer Identification and Treatment Process. 1st Symposium on Healthcare Systems Interoperability. Madrid, Spain.
Shadbolt, N., Lewis, P., Dasmahapatra, S., Dupplaw, D., Hu, B. and Lewis, H. 2004. MIAKT: Combining grid and web services for collaborative medical decision making. In Proceedings of AHM2004 UK e Science All Hands Meeting .
Shehzad, A., Ngo, H. Q, Pham, K. A. and Lee, S. Y. 2004. Formal Modeling in Context Aware Systems. Proceedings of the First International Workshop on Modeling and Retrieval of Context.
SNOMED SNOMED CT, http://www.nlm.nih.gov.research/umls/Snomed.snomed_main.html
Tavassoli, F. A. and Devilee, P. 2003. World Health Organization classification of tumours. In Pathology and Genetics Tumours of the Breast and Female Genital Organs. Lyon: IARC Press; 19-23.
The Gene Ontology Consortium: Gene Ontology: tool for the unification of biology. Nature Genet 2000, 25:25-29.
Tutac, A. E. Racoceanu, D. Putti, T. Xiong, W. Leow, W. K. and Cretu, V. 2008. Knowledge-Guided Semantic Indexing of Breast Cancer Histopathology Images. Int. Conf. on Biomedical Engineering and Informatics (BMEI). 5 de 2008, pp. 27-30.
Uschold, M. and Gruninger, M. 1996. Principles methods and applications. Knowledge Engeneering Review, pp. 11:93-136.
Vallet, D., Fernández, M. and Castells, P. 2005. An Ontology-Based Information Retrieval Model. Second European Semantic Web Conference, ESWC 2005, Heraklion, Crete, Greece, pp 455-470.
VisualLab avaliable in: http://visual.ic.uff.br.
Wang, X.H., Zhang, D.Q., Gu, T. and Pung, H.K. 2004. Ontology based context modeling and reasoning using OWL. Proceedings of 2nd IEEE Conf. Pervasive Computing and Communications (PerCom 2004), Workshop on Context Modeling and Reasoning. pp 18-22.
Publicado
17/05/2016
Como Citar
FAQUIN, Giovanni Stroppa; FALCI, Maria Luiza Furtuozo; ARAÚJO, Marco Antônio Pereira.
Uma Metodologia de Avaliação da Relação entre Perfis de Personalidade e Desempenho Acadêmico em Alunos de Sistemas de Informação. In: SIMPÓSIO BRASILEIRO DE SISTEMAS DE INFORMAÇÃO (SBSI), 12. , 2016, Florianópolis.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 285-292.
DOI: https://doi.org/10.5753/sbsi.2016.5974.
