Um framework de classificação de complexidade para infográficos
DOI:
https://doi.org/10.5753/rbie.2019.27.01.196Keywords:
Infográficos, Classificação, Complexidade, Aprendizado, FrameworkAbstract
Os infográficos passaram a ser empregados como material de apoio ao ensino devido a sua natureza informativa. As evidências empíricas mostram que o uso desse formato de visualização afeta o aprendizado e o interesse dos alunos. No entanto, ainda é necessário fornecer maiores detalhes sobre os parâmetros que garantem os resultados positivos. Um desses parâmetros é complexidade dos infográficos. Logo, é preciso obter informações sobre o impacto de infográficos com diferentes níveis de complexidade no aprendizado. Observando a ausência de diretrizes que pudessem ser aplicadas para classificar a complexidade de infográficos, este trabalho propôs um framework que considera três dimensões (visual, verbal e conceitual) e o utiliza para pontuar infográficos, gerando uma medida de complexidade. Para avaliar o framework foi realizado um experimento controlado cujo objetivo foi verificar se a complexidade medida representa a real complexidade pro usuário. Analisando os resultados verificou-se que, de fato, os usuários aprenderam mais a partir de infográficos classificados como de baixa e média complexidade. Conclui-se que o fator complexidade do infográfico afeta o aprendizado e deve ser considerado por professores e criadores de conteúdo na decisão de se utilizar infográficos como materiais de aprendizagem.
Descargas
Citas
Albers, M. J. (2014). Infographics: Horrid chartjunk or quality communication. InProfes-sional communication conference (ipcc)(pp. 1–4). Pittsburgh, PA, USA: IEEE. doi: 10.1109/IPCC.2014.7020344. [GS Seach].
Albers, M. J. (2015). Infographics and communicating complex information. InInternationalconference of design, user experience, and usability(pp. 267–276). Los Angeles, CA, USA:Springer, Cham. doi:10.1007/978-3-319-20898-5_26 [GS Seach].
Andrews, G., & Halford, G. S. (2002). A cognitive complexity metric applied to cognitivedevelopment.Cognitive Psychology,45(2), 153–219. doi: 10.1016/S0010-0285(02)00002-6 [GS Seach].
Andrews, G., Halford, G. S., Bunch, K. M., Bowden, D., & Jones, T. (2003). Theory of mindand relational complexity.Child development,74(5), 1476–1499. doi: 10.1111/1467-8624.00618. [GS Seach].
Baddeley, A. (1994). The magical number seven: Still magic after all these years?PsychologicalReview,101(2), 353-356. doi: 10.1037/0033-295X.101.2.353. [GS Seach].
Bertin, J. (2011).Semiology of graphics: Diagrams, networks, maps. ESRI Press. [GS Seach].
Brehmer, M., & Munzner, T. (2013). A multi-level typology of abstract visualization tasks.IEEE Transactions on Visualization and Computer Graphics,19(12), 2376–2385. doi:10.1109/TVCG.2013.124 [GS Seach].
Burkhard, R. A. (2004). Learning from architects: the difference between knowledge visuali-zation and information visualization. InProceedings. eighth international conference oninformation visualisation, 2004. iv 2004.(p. 519-524). doi: 10.1109/IV.2004.1320194 [GS Seach]
Card, S. K., Mackinlay, J. D., & Shneiderman, B. (1999).Readings in information visualization:using vision to think. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc. [GS Seach]
Carr, D. (1999). Guidelines for designing information visualization applications. InProceedingsof the ericsson conference on usability engineering ecue(pp. 1–3). Stockholm, Sweden.[GS Seach]
Chen, C. (2005). Top 10 unsolved information visualization problems.IEEE Computer Graphicsand Applications,25(4), 12–16. doi: 10.1109/MCG.2005.91 [GS Seach]
Clark, R., Nguyen, F., & Sweller, J. (2011).Efficiency in learning: Evidence-based guidelines tomanage cognitive load. John Wiley & Sons. [GS Seach]
Cleveland, W. S. (1994).The elements of graphing data. AT&T Bell Laboratories. [GS Seach]
Collins-Thompson, K., & Callan, J. (2004). A language modeling approach to predicting readingdifficulty.In Proceedings of the Human Language Technology Conference of the NorthAmerican Chapter of the Association for Computational Linguistics: HLT-NAACL 2004.[GS Seach]
Cowan, N.(2010).The magical mystery four: How is working memory capacity li-mited, and why?Current directions in psychological science,19(1), 51–57.doi: 10.1177/0963721409359277 [GS Seach]
Cox, R. (1999). Representation construction, externalised cognition and individual differences.Learning and Instruction,9(4), 343–363. doi:10.1016/S0959-4752(98)00051-6 [GS Seach]
Cuevas, H. M., Fiore, S. M., & Oser, R. L. (2002). Scaffolding cognitive and metacognitiveprocesses in low verbal ability learners: Use of diagrams in computer-based training envi-ronments.Instructional Science,30(6), 433–464. doi:10.1023/A:1020516301541 [GS Seach]
Dale, E., & Chall, J. S. (1948). A formula for predicting readability: Instructions.EducationalResearch Bulletin,27(2), 37–54. Retrieved from http://www.jstor.org/stable/1473669 [GS Seach]
Diakopoulos, N., Kivran-swaine, F., & Naaman, M.(2011, may).Playable data : Cha-racterizing the design space of game-y infographics. InAcm chi conference on humanfactors in computing systems(pp. 1717–1726). Vancouver, BC, Canada: ACM. doi:10.1145/1978942.1979193 [GS Seach]
Elizabeth Thomson (1996, Dec). Mit research - brain processing of visual information.MITNews. Retrieved from [Link]. [GS Search]
Figueiras, A. (2013, July). A typology for data visualization on the web. InInformation visua-lization (iv), 2013 17th international conference(pp. 351–358). London, UK: IEEE. doi:10.1109/IV.2013.45 [GS Seach]
Flesch, R. (1948). A new readability yardstick.Journal of Applied Psychology,32(3), 221. doi:10.1037/h0057532 [GS Seach]
Freitas, C. M. D. S., Chubachi, O. M., Luzzardi, P. R. G., & Cava, R. A. (2001). Introduçãoà visualização de informações.Revista de Informática Teórica e Aplicada,8(2), 143–158.[GS Seach]
Fry, E. (1968). A readability formula that saves time.Journal of Reading,11(7), 513–578. [GS Seach]
Gärtner, J., Miksch, S., & Carl-McGrath, S. (2002, April). Vico: a metric for the complexityof information visualizations. InInternational conference on theory and application ofdiagrams(pp. 249–263). Callaway Gardens, GA, USA: Springer, Berlin, Heidelberg.doi:10.1007%2F3-540-46037-3_25. [GS Seach]
Gerber, R., Boulton-Lewis, G., & Bruce, C. (1995). Children’s understanding of graphic repre-sentations of quantitative data.Learning and Instruction,5(1), 77–100. [GS Seach]
Gyselinck, V., & Tardieu, H. (1999). The role of illustrations in text comprehension: what, when,for whom, and why?Lawrence Erlbaum Associates Publishers, 195-218. [GS Seach]
Halford, G. S., Andrews, G., & Jensen, I. (1998). Category induction and hierarchical classifica-tion assessed by property inference: The influence of complexity.ERIC. [GS Seach]
Halford, G. S., Wilson, W. H., & Phillips, S. (1998). Processing capacity defined by rela-tional complexity: implications for comparative, developmental, and cognitive psycho-logy.The Behavioral and brain sciences,21(6), 803–831; discussion 831–864. doi:10.1017/S0140525X98001769 [GS Seach]
Hegarty, M., Carpenter, P. A., & Just, M. A. (1991). Diagrams in the comprehension of scientifictexts. ,2, 641-668. [GS Seach]
Jonassen, D. H., Reeves, T. C., Hong, N., Harvey, D., & Peters, K. (1997). Concept mapping ascognitive learning and assessment tools.Journal of interactive learning research,8(3), 289.[GS Seach]
Kincaid, J. P., Fishburne Jr, R. P., Rogers, R. L., & Chissom, B. S. (1975). Derivation of new readability formulas (automated readability index, fog count and flesch reading ease formula)for navy enlisted personnel.Institute for Simulation and Training, University of CentralFlorida. [GS Seach]
King, D. B., & Wertheimer, M. (2005).Max wertheimer and gestalt theory. Transaction Publishers. [GS Seach]
Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words.Cognitive Science,11(1), 65 - 100. doi:10.1016/S0364-0213(87)80026-5 [GS Seach]
Lee, E.-J., & Kim, Y. W. (2016). Effects of infographics on news elaboration, acquisition, andevaluation: Prior knowledge and issue involvement as moderators.New Media & Society,18(8), 1579-1598. doi:10.1177/1461444814567982 [GS Seach]
Leturia, E. (1998). ¿ qué es infografía.Revista Latina de Comunicación Social,4(10). [GS Seach]
Lyra, K., & Isotani, S. (2017). Impacto do uso de infográficos como materiais de aprendizagem esuas correlações com satisfação, estilos de aprendizagem e complexidade visual. InAnaisdos workshops do congresso brasileiro de informática na educação (cbie)(Vol. 6, p. 46).doi:10.5753/cbie.wcbie.2017.46 [GS Seach]
Lyra, K. T. (2017, 4). Impacto do uso de infográficos como materiais de aprendizagem e suascorrelações com satisfação, estilos de aprendizagem e complexidade visual.Dissertaçãode Mestrado. Instituto de Ciências Matemáticas e de Computação - Universidade de SãoPaulo. doi:10.11606/D.55.2017.tde-02082017-104605 [GS Seach]
Lyra, K. T., Isotani, S., Reis, R. C. D., Marques, L. B., Pedro, L. Z., Jaques, P. A., & Bitencourt,I. I. (2016, July). Infographics or graphics+text: Which material is best for robust lear-ning? In2016 ieee 16th international conference on advanced learning technologies (icalt)(p. 366-370). doi:10.1109/ICALT.2016.83 [GS Seach]
Lyra, K. T., Oliveira, B. R., Reis, R. C., Cruz, W. M., Nakagawa, E. Y., & Isotani, S. (2016). In-fográficos versus materiais de aprendizagem tradicionais: uma investigação empírica.RE-NOTE - Revista Novas Tecnologias na Educação,14(2). doi:10.22456/1679-1916.70653 [GS Seach]
Machado, V., Margarida, L., & Tarouco, R. (2010). Infográfico : características , autoria e uso educacional.Novas Tecnologias na Educação,8(3). [GS Seach]
Martins, T. B. F., Ghiraldelo, C. M., Nunes, M. G. V., & Júnior, O. N. O. (1996).ReadabilityFormulas Applied to Textbooks in Brazilian Portuguese. Notas do ICMSC-USP ICMC. [GS Seach]
Masud, L., Valsecchi, F., Ciuccarelli, P., Ricci, D., & Caviglia, G. (2010). From data to kno-wledge: Visualizations as transformation processes within the data-information-knowledgecontinuum.Proceedings of the International Conference on Information Visualisation, 445–449. doi:10.1109/IV.2010.68 [GS Seach]
Mayer, R. E. (2003). The promise of multimedia learning: using the same instructional de-sign methods across different media.Learning and instruction,13(2), 125–139. doi:10.1016/S0959-4752(02)00016-6 [GS Seach]
Mayer, R. E., Bove, W., Bryman, A., Mars, R., & Tapangco, L. (1996). When less is more:Meaningful learning from visual and verbal summaries of science textbook lessons.Journalof educational psychology,88(1), 64. [GS Seach]
McCormick, B. H., DeFanti, T. A., & Brown, M. D. (1987). Visualization in scientific computing.IEEE Computer Graphics and Applications,7(10), 69–69. [GS Seach]
McLoud, S. (2000). Reinventing comics: How imagination and technology are revolutionizingan art form.Perennial, New York, 118–122. [GS Seach]
Montgomery, D. C. (2008).Design and analysis of experiments. John Wiley & Sons. [GS Seach]
Naps, T., Cooper, S., Koldehofe, B., Leska, C., Rößling, G., Dann, W., . . . McNally, M. (2003).Evaluating the educational impact of visualization. InAcm sigcse bulletin(Vol. 35, pp.124–136). [GS Seach]
Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of theinteraction between information structures and cognitive architecture.Instructional science,32(1-2), 1–8. [GS Seach]
Ribas, B. (2004). Infografia multimídia: um modelo narrativo para o webjornalismo.Anais do IISBPJor (CD-ROM). Salvador-BA/Brasil. [GS Seach]
Risch, J. S. (2008). On the role of metaphor in information visualization.arXiv preprint ar-Xiv:0809.0884, 20. [GS Seach]
Schwarm, S. E., & Ostendorf, M. (2005). Reading Level Assessment Using Support VectorMachines and Statistical Language Models.Annual Meeting of the Association for Computational Linguistics(June), 523–530. doi:10.3115/1219840.1219905 [GS Seach]
Sebrechts, M. M. (2005). Visualizing information in virtual space: Prospects and pitfalls. InKnowledge and information visualization(pp. 136–166). Springer. [GS Seach]
Smiciklas, M. (2012).The power of infographics: Using pictures to communicate and connectwith your audiences. Que Publishing. doi:10.4324/9780203075609 [GS Seach]
Stenner, A. J. (1996). Measuring reading comprehension with the lexile framework.ERIC. [GS Seach]
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning.Cognitive Science,12(2), 257–285. doi:10.1016/0364-0213(88)90023-7 [GS Seach]
Sweller, J., Van Merrienboer, J. J., & Paas, F. G. (1998). Cognitive architecture and instructionaldesign.Educational psychology review,10(3), 251–296. [GS Seach]
Toth, C. (2013). Revisiting a Genre: Teaching Infographics in Business and ProfessionalCommunication Courses.Business Communication Quarterly,76(4), 446–457.doi:10.1177/1080569913506253. [GS Seach]
Van Merrienboer, J. J., & Sweller, J. (2005). Cognitive load theory and complex learning: Recentdevelopments and future directions.Educational psychology review,17(2), 147–177. [GS Seach]
Van Merriënboer, J. J., & Sweller, J. (2010). Cognitive load theory in health professional educa-tion: design principles and strategies.Medical education,44(1), 85–93. [GS Seach]
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C., Regnell, B., & Wesslén, A. (2012).Experi-mentation in software engineering. Springer Science & Business Media. [GS Seach]
Wolfe, J. M., & Horowitz, T. S. (2004). What attributes guide the deployment of visual attentionand how do they do it?Nature reviews neuroscience,5(6), 495–501. [GS Seach]
Zhang-Kennedy, L., Chiasson, S., & Biddle, R. (2013, sep). Password advice shouldn’t be boring:Visualizing password guessing attacks.2013 APWG eCrime Researchers Summit, 1–11. doi:10.1109/eCRS.2013.6805770 [GS Seach]
Zhu, Y. (2007). Measuring effective data visualization. In G. Bebis et al. (Eds.),Advancesin visual computing(pp. 652–661). Berlin, Heidelberg: Springer Berlin Heidelberg. [GS Seach]
Zhu, Y., Suo, X., & Owen, G. S. (2007). Complexity analysis for information visualization designand evaluation. In G. Bebis et al. (Eds.),Advances in visual computing(pp. 576–585).Berlin, Heidelberg: Springer Berlin Heidelberg. [GS Seach]
Archivos adicionales
Published
Cómo citar
Issue
Section
Licencia
Derechos de autor 2019 Kamila Takayama Lyra, Rachel Reis, Wilmax Marreiro Cruz, Seiji Isotani
Esta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.
