Investigando a Geração de Desafios Semelhantes e Exemplos Resolvidos em Jogos de Programação
Resumo
Jogos de programação engajam estudantes em desafios lúdicos que demandam raciocínio computacional e habilidades relacionadas à programação. A Geração Procedural de Conteúdo (Procedural Content Generation – PCG) possibilita a criação automática de níveis e cenários, além de apoiar funcionalidades pedagógicas, como a apresentação de exemplos resolvidos e a geração de desafios semelhantes após erros dos estudantes. Este artigo investiga essas duas funcionalidades por meio de um experimento controlado online com 51 participantes, utilizando um delineamento fatorial 2x2. Foram analisadas métricas de engajamento e desempenho entre os diferentes tratamentos, bem como as lições aprendidas durante o estudo. Embora as tendências observadas indiquem potenciais benefícios em algumas condições, os testes estatísticos não identificaram diferenças significativas para α = 5%. Também são discutidos fatores metodológicos que podem ter limitado a detecção dos efeitos investigados.
Palavras-chave:
Jogos de Programação, Geração Procedural de Conteúdo, Exemplos Resolvidos
Referências
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Hassany, M., Brusilovsky, P., Ke, J., Akhuseyinoglu, K., and Narayanan, A. B. L. (2024). Human-ai co-creation of worked examples for programming classes. arXiv preprint arXiv:2402.16235.
Jedlitschka, A., Ciolkowski, M., and Pfahl, D. (2008). Reporting experiments in software engineering. In Guide to Advanced Empirical Software Engineering, pages 201–228. Springer London, London.
Jury, B., Lorusso, A., Leinonen, J., Denny, P., and Luxton-Reilly, A. (2024). Evaluating llm-generated worked examples in an introductory programming course. In Proceedings of the 26th Australasian computing education conference, pages 77–86.
Ko, A. J., Latoza, T. D., and Burnett, M. M. (2015). A practical guide to controlled experiments of software engineering tools with human participants. Empirical Software Engineering, 20(1):110–141.
Lambić, D., Dorić, B., and Ivakić, S. (2020). Investigating the effect of the use of code.org on younger elementary school students' attitudes towards programming. Behaviour & Information Technology, pages 1–12.
Lindberg, R. S. N., Laine, T. H., and Haaranen, L. (2018). Gamifying programming education in k-12: A review of programming curricula in seven countries and programming games. British Journal of Educational Technology.
Lui, A., Cheung, Y., and Li, S. (2008). Leveraging students' programming laboratory work as worked examples. ACM SIGCSE Bulletin, 40:69–73.
Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., and Settle, A. (2014). Computational thinking in k-9 education. In Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference (ITiCSE-WGR '14).
Margulieux, L. E. et al. (2020a). Reducing withdrawal and failure rates in introductory programming with subgoal labeled worked examples. International Journal of STEM Education, 7(1).
Margulieux, L. E., Morrison, B. B., and Decker, A. (2020b). Reducing withdrawal and failure rates in introductory programming with subgoal labeled worked examples. International Journal of STEM Education, 7(1):19.
McLaren, B. M. and Isotani, S. (2011a). When is it best to learn with all worked examples? In International conference on artificial intelligence in education, pages 222–229. Springer.
McLaren, B. M. and Isotani, S. (2011b). When is it best to learn with all worked examples? In Proceedings of the 15th International Conference on Artificial Intelligence in Education (AIED '11), pages 222–229.
Montgomery, D. C. (2020). Design and Analysis of Experiments. John Wiley & Sons, Inc., Hoboken, NJ, USA.
Muldner, K., Jennings, J., and Chiarelli, V. (2022). A review of worked examples in programming activities. ACM Transactions on Computing Education, 23(1):1–35.
Rahman, S. and Du Boulay, B. (2010). Learning programming via worked examples.
Sandhu, A. and McCoy, J. (2019). A framework for integrating architectural design patterns into pcg. In Proceedings of the 14th International Conference on the Foundations of Digital Games (FDG '19).
Santana, A. and Aranha, E. (2019). An approach to generate virtual tutors for game programming classes. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19).
Silva, B. A. and D'Emery, R. A. (2024). Desenvolvimento e avaliação do jogo sério educacional coding hunter: um ambiente para prática de pensamento computacional. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 791–806. SBC.
Silva, G., Pessoa, J. O., da Magatti, I. N., Gonçalves, A. C., Garcia, K. R., Brandão, A. L., and Vittori, K. (2024). Newbot: Jogo educativo para o ensino do pensamento computacional. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 3127–3138. SBC.
Silva, T., Santana, A., and Aranha, E. (2019). Investigating video classes formats for teaching digital game programming in high school. In Brazilian Symposium on Computers in Education (SBIE), page 753.
Sweller, J. (2011). Cognitive load theory and e-learning. In International Conference on Artificial Intelligence in Education, pages 5–6. Springer.
Zhi, R., Lytle, N., and Price, T. W. (2018). Exploring instructional support design in an educational game for k-12 computing education. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18), pages 747–752.
Falkner, K., Sentance, S., Vivian, R., Barksdale, S., Busuttil, L., Cole, E., Liebe, C., Maiorana, F., McGill, M. M., and Quille, K. (2019). An international study piloting the measuring teacher enacted computing curriculum (metrecc) instrument. In ITiCSE-WGR '19: Proceedings of the Working Group Reports on Innovation and Technology in Computer Science Education, pages 111–142.
Hafis, M., Tolle, H., and Supianto, A. A. (2019). A literature review of empirical evidence on procedural content generation in game-related implementation. Journal of Information Technology and Computer Science.
Harms, K. J., Balzuweit, E., Chen, J., and Kelleher, C. (2016). Learning programming from tutorials and code puzzles: Children's perceptions of value. In 2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pages 59–67.
Hassany, M., Brusilovsky, P., Ke, J., Akhuseyinoglu, K., and Narayanan, A. B. L. (2024). Human-ai co-creation of worked examples for programming classes. arXiv preprint arXiv:2402.16235.
Jedlitschka, A., Ciolkowski, M., and Pfahl, D. (2008). Reporting experiments in software engineering. In Guide to Advanced Empirical Software Engineering, pages 201–228. Springer London, London.
Jury, B., Lorusso, A., Leinonen, J., Denny, P., and Luxton-Reilly, A. (2024). Evaluating llm-generated worked examples in an introductory programming course. In Proceedings of the 26th Australasian computing education conference, pages 77–86.
Ko, A. J., Latoza, T. D., and Burnett, M. M. (2015). A practical guide to controlled experiments of software engineering tools with human participants. Empirical Software Engineering, 20(1):110–141.
Lambić, D., Dorić, B., and Ivakić, S. (2020). Investigating the effect of the use of code.org on younger elementary school students' attitudes towards programming. Behaviour & Information Technology, pages 1–12.
Lindberg, R. S. N., Laine, T. H., and Haaranen, L. (2018). Gamifying programming education in k-12: A review of programming curricula in seven countries and programming games. British Journal of Educational Technology.
Lui, A., Cheung, Y., and Li, S. (2008). Leveraging students' programming laboratory work as worked examples. ACM SIGCSE Bulletin, 40:69–73.
Mannila, L., Dagiene, V., Demo, B., Grgurina, N., Mirolo, C., Rolandsson, L., and Settle, A. (2014). Computational thinking in k-9 education. In Proceedings of the Working Group Reports of the 2014 on Innovation & Technology in Computer Science Education Conference (ITiCSE-WGR '14).
Margulieux, L. E. et al. (2020a). Reducing withdrawal and failure rates in introductory programming with subgoal labeled worked examples. International Journal of STEM Education, 7(1).
Margulieux, L. E., Morrison, B. B., and Decker, A. (2020b). Reducing withdrawal and failure rates in introductory programming with subgoal labeled worked examples. International Journal of STEM Education, 7(1):19.
McLaren, B. M. and Isotani, S. (2011a). When is it best to learn with all worked examples? In International conference on artificial intelligence in education, pages 222–229. Springer.
McLaren, B. M. and Isotani, S. (2011b). When is it best to learn with all worked examples? In Proceedings of the 15th International Conference on Artificial Intelligence in Education (AIED '11), pages 222–229.
Montgomery, D. C. (2020). Design and Analysis of Experiments. John Wiley & Sons, Inc., Hoboken, NJ, USA.
Muldner, K., Jennings, J., and Chiarelli, V. (2022). A review of worked examples in programming activities. ACM Transactions on Computing Education, 23(1):1–35.
Rahman, S. and Du Boulay, B. (2010). Learning programming via worked examples.
Sandhu, A. and McCoy, J. (2019). A framework for integrating architectural design patterns into pcg. In Proceedings of the 14th International Conference on the Foundations of Digital Games (FDG '19).
Santana, A. and Aranha, E. (2019). An approach to generate virtual tutors for game programming classes. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education (SIGCSE '19).
Silva, B. A. and D'Emery, R. A. (2024). Desenvolvimento e avaliação do jogo sério educacional coding hunter: um ambiente para prática de pensamento computacional. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 791–806. SBC.
Silva, G., Pessoa, J. O., da Magatti, I. N., Gonçalves, A. C., Garcia, K. R., Brandão, A. L., and Vittori, K. (2024). Newbot: Jogo educativo para o ensino do pensamento computacional. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 3127–3138. SBC.
Silva, T., Santana, A., and Aranha, E. (2019). Investigating video classes formats for teaching digital game programming in high school. In Brazilian Symposium on Computers in Education (SBIE), page 753.
Sweller, J. (2011). Cognitive load theory and e-learning. In International Conference on Artificial Intelligence in Education, pages 5–6. Springer.
Zhi, R., Lytle, N., and Price, T. W. (2018). Exploring instructional support design in an educational game for k-12 computing education. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE '18), pages 747–752.
Publicado
05/10/2026
Como Citar
SANTANA, Alan de Oliveira; DA SILVA, Thiago Reis; ARANHA, Eduardo Henrique da Silva.
Investigando a Geração de Desafios Semelhantes e Exemplos Resolvidos em Jogos de Programação. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 37. , 2026, Goiânia/GO.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 1248-1261.
DOI: https://doi.org/10.5753/sbie.2026.27724.
