Learning Trajectories Visualizations of Students Data on the Computational Thinking Context

Resumo


Learning trajectories are paths that students may follow in order to achieve learning goals. The visualization of learning trajectories of students can support teachers in tracking students evolution and identify difficulties. We propose visualizations of learning trajectories in a new and interactive way, representing different concepts of computational thinking and learning goals in concise or detailed manner, according to interactions of the user. To evaluate our proposal, we chose to represent a series of exercises found in code.org, a free and well known platform that introduces and exercises computational thinking through visual programming. These visualizations were evaluated by 20 elementary school teachers in usability perspective.

Palavras-chave: Learning Trajectories, Information Visualization, InfoVis, Computational Thinking

Referências

Berland, M., Martin, T., Benton, T., Smith, C. P., and Davis, D. (2013). Using learning analytics to understand the learning pathways of novice programmers. Journal of the Learning Sciences, 22(4):564–599.

Cai, R. (2018). Adaptive learning practice for online learning and assessment. In Proceedings of the 2018 International Conference on Distance Education and Learning, ICDEL'18, pages 103–108, New York, NY, USA. ACM.

Carmo, Ê ., Gasparini, I., Oliveira, E. (2019). Captura e Visualização das Trajetórias de Aprendizagem como Ferramentas para a Análise do Comportamento dos Estudantes em um Ambiente Adaptativo Educacional. Simpósio Brasileiro de Informática na Educação - SBIE, p. 309, nov. 2019.

da Silva, C. G. (2014). Visualização de informação: introdução e influências de IHC. In Boscarioli, C., Bim, S. A., Leitão, C. F., and Maciel, C., editors, Companion Proceedings of the 13th Brazilian Symposium on Human Factors in Computing Systems, IHC 2014, Foz do Iguaçu, Brazil, October 27-31, 2014, pages 81–82. ACM.

de Borba, J. E., Gasparini, I., Lichtnow, D., Pimenta, M. S., and de Oliveira, J. P. M. (2016). Captura e visualização da trajetória de aprendizagem do aluno: um mapeamento sistemático. TISE, 12:105–111.

de Melo, A. N. B., Zaina, L. M., Martinelli, S. R., and Sakata, T. (2018). Visualização de informações para acompanhamento do ensino do pensamento computacional: uma proposta baseada em design centrado no usuário - technical report. Available at: http://uxleris.net/?page_id=132.

Forsell, C. (2010). A guide to scientific evaluation in information visualization. In 2010 14th International Conference Information Visualization, pages 162–169.

Fortenbacher, A., Beuster, L., Elkina, M., Kappe, L., Merceron, A., Pursian, A., Schwarzrock, S., and Wenzlaff, B. (2013). Lemo: A learning analytics application focussing on user path analysis and interactive visualization. In 2013 IEEE 7th International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), volume 02, pages 748–753.

Fouh, E., Akbar, M., and Shaffer, C. A. (2012). The role of visualization in computer science education. Computers in the Schools, 29(1-2):95–117.

Grover, S. and Pea, R. (2013). Computational thinking in k–12: A review of the state of the field. Educational Researcher, 42(1):38–43.

Keim, D. A. (2002). Information visualization and visual data mining. IEEE Transactions on Visualization and Computer Graphics, 8(1):1–8.

Lazar, J., Feng, J. H., and Hochheiser, H. (2017). In Lazar, J., Feng, J. H., and Hochheiser, H., editors, Research Methods in Human Computer Interaction (Second Edition), page 508. Morgan Kaufmann, Boston.

Mazza, R. (2009). Introduction to Information Visualization. Springer Publishing Company, Incorporated, 1 edition.

Nascimento, H. A. D. and Ferreira, C. B. R. (2005). Visualização de informações – uma abordagem prática. In XXV Congresso da Sociedade Brasileira de Computação, pages 1262–1313. Universidade Federal de Goiás.

Raabe, A. L. A., Zorzo, A. F., Frango, I., Granville, L. R. L. Z., Salgado, L., da Cruz, M. K., Bigolin, N., Cavalheiro, S. A. C., and Fortes, S. (2017). Referenciais de formação em computação: Educação básica. Sociedade Brasileira de Computação.

Ramos, D. B., de Oliveira, E. H. T., Ramos, I. M. M., and Oliveira, K. M. T. (2015). Trilhas de aprendizagem em ambientes virtuais de ensino-aprendizagem: Uma revisão sistemática da literatura. In Anais do XXVI Simpósio Brasileiro de Informática na Educação, pages 182–190. CBIE-LACLO.

Rich, K. M., Binkowski, T. A., Strickland, C., and Franklin, D. (2018). Decomposition: A k-8 computational thinking learning trajectory. In Proceedings of the 2018 ACM Conference on International Computing Education Research, ICER ’18, pages 124– 132, New York, NY, USA. ACM.

Rich, K. M., Strickland, C., Binkowski, T. A., Moran, C., and Franklin, D. (2017). K-8 learning trajectories derived from research literature: Sequence, repetition, conditionals. In Proceedings of the 2017 ACM Conference on International Computing Education Research, ICER'17, pages 182–190, New York, NY, USA. ACM.

Seiter, L. and Foreman, B. (2013). Modeling the learning progressions of computational thinking of primary grade students. In Proceedings of the Ninth Annual International ACM Conference on International Computing Education Research, ICER ’13, page 59–66, New York, NY, USA. ACM.

Simon, M. (1995). Reconstructing mathematics pedagogy from a constructivist perspective. Journal for Research in Mathematics Education, 26.

Strauss, A. and Corbin, J. (1998). Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory, volume 4. Thousand Oaks, CA: Sage, 2 edition.

Sáez-López, J.-M., Román-González, M., and Vázquez-Cano, E. (2016). Visual programming languages integrated across the curriculum in elementary school: A two year case study using "scratch" in five schools. Computers & Education, 97:129 – 141.

Tafner, E. P., Tomelin, J. F., and Müller, R. B. (2012). Trilhas de aprendizagem: uma nova concepção nos ambientes virtuais de aprendizagem-ava. In Anais do 18o. Congresso Internacional de Educação a Distância

Wing, J. (2008). Computational thinking and thinking about computing. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 366:3717– 25.

Yang, S., Domeniconi, C., Revelle, M., Sweeney, M., Gelman, B. U., Beckley, C., and Johri, A. (2015). Uncovering trajectories of informal learning in large online communities of creators. In Proceedings of the Second (2015) ACM Conference on Learning @ Scale, L@S'15, pages 131–140, New York, NY, USA. ACM.

Yi, J. S., ah Kang, Y., Stasko, J., and Jacko, J. A. (2007). Toward a deeper understanding of the role of interaction in information visualization. IEEE Transactions on Visualization and Computer Graphics, 13(6):1224–1231.
Publicado
22/11/2021
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VIEIRA, José Michel Fogaça; ZAINA, Luciana A. M.. Learning Trajectories Visualizations of Students Data on the Computational Thinking Context. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 32. , 2021, Online. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 705-717. DOI: https://doi.org/10.5753/sbie.2021.218612.