Artefatos computacionais são considerados criativos?
Resumo
A criatividade é considerada uma competência essencial do século XXI. Apesar de ser tipicamente associada às artes, ela também pode ser desenvolvida como parte da educação em computação. No entanto, essa associação com as artes pode gerar um viés, resultando em dificuldade no reconhecimento da criatividade em artefatos típicos de computação. Isso pode desestimular professores e alunos que buscam desenvolver artefatos computacionais criativos. Assim, este artigo investiga um potencial viés artístico sobre a percepção da criatividade em artefatos computacionais com base em um survey com 213 professores e alunos de computação. Os resultados indicam que a percepção da criatividade nos artefatos computacionais tende a ficar atenuada devido a um viés associado às artes. Os resultados deste estudo podem ser utilizados para motivar maior reconhecimento da criatividade em artefatos computacionais, auxiliando pesquisadores e professores a promover o desenvolvimento da criatividade como parte do ensino de computação.
Palavras-chave:
Criatividade, Percepção, Survey, Crenças implícitas, Conceito leigo
Referências
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D. Cropley and J. Kaufman. 2019. The siren song of aesthetics? Domain differences and creativity in engineering and design. Journal of Mechanical Engineering Science, 233(2), 451-464.
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M. A. Boden. 2004. The creative mind: Myths and mechanism, Routledge.
N. da C. Alves, C. Gresse von Wangenheim and L. H. Martins-Pacheco. 2021. Assessing Product Creativity in Computing Education: A Systematic Mapping Study. Informatics in Education, 20(1), 19-45.
M. Romero, A. Lepage and B. Lille. 2017. Computational thinking development through creative programming in higher education. International Journal of Educational Technology in Higher Education, 14(1).
A. Yadav and S. Cooper. 2017. Fostering Creativity Through Computing. Comm. of the ACM, 60(2), 31-33.
S. Grover and R. Pea. 2013. Computational Thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43.
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L. S. Marques, C. Gresse Von Wangenheim and J. C. R. Hauck. 2020. Teaching Machine Learning in School: A Systematic Mapping of the State of the Art. Informatics in Education, 19(2), 283-321.
V. P. Glăveanu. 2014. Revisiting the “Art Bias” in Lay Conceptions of Creativity. Creativity Research Journal, 26(1), 11-20.
I. Lee, F. Martin, J. Denner, B. Coulter, W. Allan, J. Erickson, J. Malyn-Smith and L. Werner. 2011. Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37.
N. Lytle, V. Cateté, D. Boulden, Y. Dong, J. Houchins, A. Milliken, A. Isvik, D. Bounajim, E. Wiebe and T. Barnes. 2019. Use, Modify, Create: Comparing Computational Thinking Lesson Progressions for STEM Classes. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ’19), New York, NY, USA.
C. Bellettini, V. Lonati, D. Malchiodi, M. Monga, A. Morpurgo, M. Torelli and L. Zecca. 2014. Informatics education in Italian secondary school. ACM Transactions on Computing Education, 14(2), 1–5.
M. Tissenbaum, J. Sheldon and H. Abelson. 2019. From Computational Thinking to Computational Action. Comm. of the ACM, 62(3), 34-36.
A. Craft. 2005. Creativity in schools: tensions and dilemmas, London: Routledge.
R. Richards. 2007. Everyday creativity: Our hidden potential. In Everyday creativity and new views of human nature: Psychological, social, and spiritual perspectives, American Psychological Association, 25–53.
J. C. Kaufman and R. A. Beghetto. 2009. Beyond Big and Little: The Four C Model of Creativity. Review of General Psychology, 13(1), 1–12.
T. J. Patston, D. H. Cropley, R. L. Marrone and J. C. Kaufman. 2018. Teacher implicit beliefs of creativity: Is there an arts bias? Teaching and teacher education, 75, 366-374.
P. Kampylis, E. Berki and P. Saariluoma. 2009. In-service and prospective teachers’ conceptions of creativity. Thinking skills and creativity, 4(1), 15-29.
M. A. Runco. 1999. Implicit Theories. In Encyclopedia of creativity, London, Academic, 27-30.
M. A. Runco, D. J. Johnson and P. K. Bear. 1993. Parents' and teachers' implicit theories of children's creativity. Child Study Journal, 23(2), 91–113.
M. A. Runco. 2007. Creativity: Theories and themes: Research, development and practice, Burlington MA: Elsevier Academic Press.
C. Rocavert. 2020. Arts Bias. In Encyclopedia of creativity, Academic press.
W. Lim and J. A. Plucker. 2001. Creativity through a lens of social responsibility: Implicit theories of creativity with Korean samples. Journal of Creative Behavior, 35, 115–130.
D. R. Mullet, A. Willerson, K. N. Lamb and T. Kettler. 2016. Examining teacher perceptions of creativity: A systematic review of the literature. Thinking Skills and Creativity, 21, 9-30.
C. Tang, J. Baer and J. C. Kaufman. 2015. Implicit theories of creativity in computer science in the United States and China. The Journal of Creative Behavior, 49(2), 137-156.
F. Carnovalini and A. Rodà. 2020. Computational Creativity and Music Generation Systems: An Introduction to the State of the Art. Frontiers in Artificial Intelligence, 3, 14.
P. Atkinson and F. Parsayi. 2021. Video Games and Aesthetic Contemplation. Games and Culture, 16(5), 519-537.
F. A. Samejima. 1969. Estimation of latent ability using a response pattern of graded scores, Psychometric Monograph, 34(4), 2-17.
R. A. Beghetto, 2005. Does assessment kill student creativity?. The educational forum, 69(3), 254-263. Taylor & Francis Group.
J. A. Plucker, R. A. Beghetto, and G. T. Dow, 2004. Why isn’t creativity more important to educational psychologists? Potentials, pitfalls, and future directions in creativity research. Educational Psychologist, 39(2), 83–96.
L. Rosenstock and R. Riordan. 2017. Nurturing creativity in the classroom. In Changing the subject (R. A. Beghetto, & J. C. Kaufman (Eds.)), New York, NY, Cambridge University Press, 3-5.
M. F. Taguma. 2018. Future of Education and Skills 2030: Conceptual Learning Framework. OECD. Retrieved August 4, 2021 from https://www.oecd.org/education/2030-project/
R. A. Beghetto. 2010. Creativity in the classroom. In Cambridge handbook of creativity, J. C. Kaufman and R. J. Sternberg, Eds., New York, Cambridge University Press, 447–463.
F. Aktas. 2021. The emergence of creativity as an academic discipline: Examining the institutionalization of higher education programs. Higher Education Quarterly, 00, 1-18.
A. J. Cropley. 2014. Is there an ‘arts bias’ in the Creativity Research Journal? Comment on Glāveanu (2014). Creativity Research Journal, 26(3), 368-371.
D. Cropley and J. Kaufman. 2019. The siren song of aesthetics? Domain differences and creativity in engineering and design. Journal of Mechanical Engineering Science, 233(2), 451-464.
K. Brennan, P. Haduong, and E. Veno. 2020. Assessing creativity in computing classrooms. Retrieved August 4, 2021 from https://creativecomputing.gse.harvard.edu/assessment/
M. A. Boden. 2004. The creative mind: Myths and mechanism, Routledge.
N. da C. Alves, C. Gresse von Wangenheim and L. H. Martins-Pacheco. 2021. Assessing Product Creativity in Computing Education: A Systematic Mapping Study. Informatics in Education, 20(1), 19-45.
M. Romero, A. Lepage and B. Lille. 2017. Computational thinking development through creative programming in higher education. International Journal of Educational Technology in Higher Education, 14(1).
A. Yadav and S. Cooper. 2017. Fostering Creativity Through Computing. Comm. of the ACM, 60(2), 31-33.
S. Grover and R. Pea. 2013. Computational Thinking in K–12: A review of the state of the field. Educational Researcher, 42(1), 38–43.
D. F. Shell, M. P. Hazley, Soh.-K., L. Dee Miller, V. Chiriacescu and E. Ingraham. 2014. Improving learning of computational thinking using computational creativity exercises in a college CSI computer science course for engineers. In Proc. of the Frontiers in Education Conference, Madrid.
L. S. Marques, C. Gresse Von Wangenheim and J. C. R. Hauck. 2020. Teaching Machine Learning in School: A Systematic Mapping of the State of the Art. Informatics in Education, 19(2), 283-321.
V. P. Glăveanu. 2014. Revisiting the “Art Bias” in Lay Conceptions of Creativity. Creativity Research Journal, 26(1), 11-20.
I. Lee, F. Martin, J. Denner, B. Coulter, W. Allan, J. Erickson, J. Malyn-Smith and L. Werner. 2011. Computational thinking for youth in practice. ACM Inroads, 2(1), 32–37.
N. Lytle, V. Cateté, D. Boulden, Y. Dong, J. Houchins, A. Milliken, A. Isvik, D. Bounajim, E. Wiebe and T. Barnes. 2019. Use, Modify, Create: Comparing Computational Thinking Lesson Progressions for STEM Classes. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education (ITiCSE ’19), New York, NY, USA.
C. Bellettini, V. Lonati, D. Malchiodi, M. Monga, A. Morpurgo, M. Torelli and L. Zecca. 2014. Informatics education in Italian secondary school. ACM Transactions on Computing Education, 14(2), 1–5.
M. Tissenbaum, J. Sheldon and H. Abelson. 2019. From Computational Thinking to Computational Action. Comm. of the ACM, 62(3), 34-36.
A. Craft. 2005. Creativity in schools: tensions and dilemmas, London: Routledge.
R. Richards. 2007. Everyday creativity: Our hidden potential. In Everyday creativity and new views of human nature: Psychological, social, and spiritual perspectives, American Psychological Association, 25–53.
J. C. Kaufman and R. A. Beghetto. 2009. Beyond Big and Little: The Four C Model of Creativity. Review of General Psychology, 13(1), 1–12.
T. J. Patston, D. H. Cropley, R. L. Marrone and J. C. Kaufman. 2018. Teacher implicit beliefs of creativity: Is there an arts bias? Teaching and teacher education, 75, 366-374.
P. Kampylis, E. Berki and P. Saariluoma. 2009. In-service and prospective teachers’ conceptions of creativity. Thinking skills and creativity, 4(1), 15-29.
M. A. Runco. 1999. Implicit Theories. In Encyclopedia of creativity, London, Academic, 27-30.
M. A. Runco, D. J. Johnson and P. K. Bear. 1993. Parents' and teachers' implicit theories of children's creativity. Child Study Journal, 23(2), 91–113.
M. A. Runco. 2007. Creativity: Theories and themes: Research, development and practice, Burlington MA: Elsevier Academic Press.
C. Rocavert. 2020. Arts Bias. In Encyclopedia of creativity, Academic press.
W. Lim and J. A. Plucker. 2001. Creativity through a lens of social responsibility: Implicit theories of creativity with Korean samples. Journal of Creative Behavior, 35, 115–130.
D. R. Mullet, A. Willerson, K. N. Lamb and T. Kettler. 2016. Examining teacher perceptions of creativity: A systematic review of the literature. Thinking Skills and Creativity, 21, 9-30.
C. Tang, J. Baer and J. C. Kaufman. 2015. Implicit theories of creativity in computer science in the United States and China. The Journal of Creative Behavior, 49(2), 137-156.
F. Carnovalini and A. Rodà. 2020. Computational Creativity and Music Generation Systems: An Introduction to the State of the Art. Frontiers in Artificial Intelligence, 3, 14.
P. Atkinson and F. Parsayi. 2021. Video Games and Aesthetic Contemplation. Games and Culture, 16(5), 519-537.
F. A. Samejima. 1969. Estimation of latent ability using a response pattern of graded scores, Psychometric Monograph, 34(4), 2-17.
R. A. Beghetto, 2005. Does assessment kill student creativity?. The educational forum, 69(3), 254-263. Taylor & Francis Group.
J. A. Plucker, R. A. Beghetto, and G. T. Dow, 2004. Why isn’t creativity more important to educational psychologists? Potentials, pitfalls, and future directions in creativity research. Educational Psychologist, 39(2), 83–96.
Publicado
24/04/2022
Como Citar
DA CRUZ ALVES, Nathalia; GRESSE VON WANGENHEIM, Christiane; MARTINS-PACHECO, Lúcia Helena; FERRETI BORGATTO, Adriano.
Artefatos computacionais são considerados criativos?. In: SIMPÓSIO BRASILEIRO DE EDUCAÇÃO EM COMPUTAÇÃO (EDUCOMP), 2. , 2022, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 01-09.
DOI: https://doi.org/10.5753/educomp.2022.19193.
