Revisão Sistemática sobre Inventário de Conceitos aplicados em disciplinas introdutórias de cursos de computação
Resumo
Este estudo realiza uma Revisão Sistemática da Literatura (RSL) sobre o uso de Inventários de Conceitos (ICs) em disciplinas introdutórias de computação. Os ICs são ferramentas valiosas para identificar e avaliar concepções errôneas, ou seja, a compreensão equivocada dos estudantes sobre determinados conceitos fundamentais da área, que dificultam significativamente o processo de aprendizagem. Essa RSL demonstra a importância dos ICs na aprendizagem em computação, ao identificar lacunas de conhecimento dos estudantes e orientar práticas pedagógicas. A pesquisa também aponta desafios como a construção de itens do IC de alta qualidade e sua adaptação a diferentes contextos. Os resultados dessa pesquisa contribuem para o avanço da pesquisa em educação em computação, oferecendo subsídios para o desenvolvimento de ICs, evidenciando a necessidade de expandir o uso de IC para diversas disciplinas, níveis de ensino e diferentes contextos educacionais.Referências
Adams, W. K. and Wieman, C. E. (2011). Development and validation of instruments to measure learning of expert-like thinking. International journal of science education, 33(9):1289–1312.
Ali, M., Ghosh, S., Rao, P., Dhegaskar, R., Jawort, S., Medler, A., Shi, M., and Dasgupta, S. (2023). Taking stock of concept inventories in computing education: A systematic literature review. In Proceedings of the 2023 ACM Conference on International Computing Education Research-Volume 1, pages 397–415.
Almstrum, V. L., Henderson, P. B., Harvey, V., Heeren, C., Marion, W., Riedesel, C., Soh, L.-K., and Tew, A. E. (2006). Concept inventories in computer science for the topic discrete mathematics. In Working group reports on ITiCSE on Innovation and technology in computer science education, pages 132–145.
Barbosa, L. S., Fernandes, T. C., and Campos, A. M. (2011). Takkou: Uma ferramenta proposta ao ensino de algoritmos. In XVIII Workshop sobre Educaçao em Computaçao (WEI 2011).
Brasil (2022). Base nacional comum curricular (bncc) de computação. Anexo ao Parecer CNE/CEB nº 2/2022. Acesso em: 2 nov. 2024.
Brasil (2023). Lei nº 14.533, de 11 de janeiro de 2023. Institui a Política Nacional de Educação Digital e dá outras providências. Acesso em: 2 nov. 2024.
Braz, A. C. R., Carvalho, L. S., Oliveira, E. H., Oliveira, D. B., Bittencourt, R. A., Santana, B. L., and Pereira, F. D. (2021). Tradução e validação de um inventário de conceitos sobre programação introdutória. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, pages 1253–1264. SBC.
Caceffo, R., de França, B., Gama, G., Benatti, R., Aparecida, T., Caldas, T., and Azevedo, R. (2017). An antipattern documentation about misconceptions related to an introductory programming course in c. In Technical Report 17-15, page 42. Institute of Computing, University of Campinas.
Caceffo, R., Frank-Bolton, P., Souza, R., and Azevedo, R. (2019). Identifying and validating java misconceptions toward a cs1 concept inventory. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, pages 23–29.
Caceffo, R., Gama, G., Benatti, R., Aparecida, T., Caldas, T., and Azevedo, R. (2018). A concept inventory for cs1 introductory programming courses in c. Institute of Computing, University of Campinas, Tech. Rep. IC-18-06, page 107.
Caceffo, R., Wolfman, S., Booth, K. S., and Azevedo, R. (2016). Developing a computer science concept inventory for introductory programming. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education, pages 364–369.
Dermeval, D., Coelho, J. A. d. M., and BITTENCOURT, I. I. (2020). Mapeamento sistemático e revisão sistemática da literatura em informática na educação. JAQUES, Patrícia Augustin; SIQUEIRA; Sean; BITTENCOURT, Ig; PIMENTEL, Mariano.(Org.) Metodologia de Pesquisa Científica em Informática na Educação: Abordagem Quantitativa. Porto Alegre: SBC.
Dewji, N., Wolfman, S. A., Herman, G. L., Porter, L., Taylor, C., and Vahrenhold, J. (2015). The cs concept inventory quiz show. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education, pages 669–670.
Duran, R., Bim, S. A., Gimenes, I., Ribeiro, L., and Correia, R. C. M. (2023). Potential factors for retention and intent to drop-out in brazilian computing programs. ACM Transactions on Computing Education, 23(3):1–33.
Evans, D., Gray, G. L., Krause, S., Martin, J., Midkiff, C., Notaros, B. M., Pavelich, M., Rancour, D., Reed-Rhoads, T., Steif, P., et al. (2003). Progress on concept inventory assessment tools. In 33rd Annual Frontiers in Education, 2003. FIE 2003., volume 1, pages T4G–1. IEEE.
Ferrao, R. C., Montagner, I. D. S., Caceffo, R., and Azevedo, R. (2022). How much c can students learn in one week? experiences teaching c in advanced cs courses. In 2022 IEEE frontiers in education conference (FIE), pages 1–8. IEEE.
Field, A. (2024). Discovering statistics using IBM SPSS statistics. Sage publications limited.
Fukao, A. T., Colanzi, T. E., Martimiano, L. A., and Feltrim, V. D. (2023). Estudo sobre evasao nos cursos de computaçao da universidade estadual de maringá. In Anais do III Simpósio Brasileiro de Educação em Computação, pages 86–96. SBC.
Goldman, K., Gross, P., Heeren, C., Herman, G. L., Kaczmarczyk, L., Loui, M. C., and Zilles, C. (2010). Setting the scope of concept inventories for introductory computing subjects. ACM Transactions on Computing Education (TOCE), 10(2):1–29.
Grover, S. (2020). Designing an assessment for introductory programming concepts in middle school computer science. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, pages 678–684.
Hamouda, S., Edwards, S. H., Elmongui, H. G., Ernst, J. V., and Shaffer, C. A. (2017). A basic recursion concept inventory. Computer Science Education, 27(2):121–148.
Henry, J. and Dumas, B. (2020). Developing an assessment to profile students based on their understanding of the variable programming concept. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, pages 33–39.
Herman, G. L., Loui, M. C., and Zilles, C. (2010). Creating the digital logic concept inventory. In Proceedings of the 41st ACM technical symposium on Computer science education, pages 102–106.
Hestenes, D., Wells, M., Swackhamer, G., et al. (1992). Force concept inventory. The physics teacher, 30(3):141–158.
Julie, H. and Bruno, D. (2019). Towards the identification of profiles based on the understanding of programming concepts: the case of the variable. In 2019 IEEE Frontiers in Education Conference (FIE), pages 1–8. IEEE.
Julie, H. and Bruno, D. (2020). Approach to develop a concept inventory informing teachers of novice programmers’ mental models. In 2020 IEEE frontiers in education conference (FIE), pages 1–9. IEEE.
Julie, H., Bruno, D., Patrick, H., and Tony, L. (2020a). Object-oriented programming: Diagnosis understanding by identifying and describing novice perceptions. In 2020 IEEE Frontiers in Education Conference (FIE), pages 1–5. IEEE.
Julie, H., Tom, M., Antoine, C., Benoit, V., and Bruno, D. (2020b). A tangible-augmented concept inventory to identify novices’ misconceptions in programming. In 2020 15th international conference on computer science & education (ICCSE), pages 370–374. IEEE.
Kaczmarczyk, L. C., Petrick, E. R., East, J. P., and Herman, G. L. (2019). The first of the top ten sigcse symposium research papers of the last 50 years: Identifying student misconceptions of programming. ACM Inroads, 10(2):65–69.
Kennedy, C. and Kraemer, E. T. (2019). Qualitative observations of student reasoning: Coding in the wild. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, pages 224–230.
Lu, K.-C. and Krishnamurthi, S. (2024). Identifying and correcting programming language behavior misconceptions. Proceedings of the ACM on Programming Languages, 8(OOPSLA1):334–361.
Luxton-Reilly, A., Becker, B. A., Cao, Y., McDermott, R., Mirolo, C., Mühling, A., Petersen, A., Sanders, K., Simon, and Whalley, J. (2018). Developing assessments to determine mastery of programming fundamentals. In Proceedings of the 2017 ITiCSE Conference on Working Group Reports, pages 47–69.
Parker, M. C., Davidson, M. J., Kao, Y. S., Margulieux, L. E., Tidler, Z. R., and Vahrenhold, J. (2023). Toward cs1 content subscales: A mixed-methods analysis of an introductory computing assessment. In Proceedings of the 23rd Koli Calling International Conference on Computing Education Research, pages 1–13.
Parker, M. C., Guzdial, M., and Engleman, S. (2016). Replication, validation, and use of a language independent cs1 knowledge assessment. In Proceedings of the 2016 ACM conference on international computing education research, pages 93–101.
Porter, L., Taylor, C., and Webb, K. C. (2014). Leveraging open source principles for flexible concept inventory development. In Proceedings of the 2014 conference on Innovation & technology in computer science education, pages 243–248.
Porter, L., Zingaro, D., Liao, S. N., Taylor, C., Webb, K. C., Lee, C., and Clancy, M. (2019). Bdsi: A validated concept inventory for basic data structures. In Proceedings of the 2019 ACM Conference on International Computing Education Research, pages 111–119.
Rachmatullah, A., Akram, B., Boulden, D., Mott, B., Boyer, K., Lester, J., and Wiebe, E. (2020). Development and validation of the middle grades computer science concept inventory (mg-csci) assessment. EURASIA Journal of Mathematics, Science and Technology Education, 16(5):em1841.
Saarinen, S., Krishnamurthi, S., Fisler, K., and Tunnell Wilson, P. (2019). Harnessing the wisdom of the classes: Classsourcing and machine learning for assessment instrument generation. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, pages 606–612.
Semesp, I. (2023). 13º mapa do ensino superior no brasil 2023. Acesso em: 2 nov. 2024.
Sherman, A. T., Herman, G. L., Oliva, L., Peterson, P. A., Golaszewski, E., Poulsen, S., Scheponik, T., and Gorti, A. (2020). Experiences and lessons learned creating and validating concept inventories for cybersecurity. In National Cyber Summit, pages 3–34. Springer.
Stephens-Martinez, K., Ju, A., Parashar, K., Ongowarsito, R., Jain, N., Venkat, S., and Fox, A. (2017). Taking advantage of scale by analyzing frequent constructed-response, code tracing wrong answers. In Proceedings of the 2017 ACM Conference on International Computing Education Research, pages 56–64.
Taylor, C., Zingaro, D., Porter, L., Webb, K. C., Lee, C. B., and Clancy, M. (2014). Computer science concept inventories: past and future. Computer Science Education, 24(4):253–276.
Vahrenhold, J. and Paul, W. (2014). Developing and validating test items for first-year computer science courses. Computer science education, 24(4):304–333.
Webb, K. C. and Taylor, C. (2014). Developing a pre-and post-course concept inventory to gauge operating systems learning. In Proceedings of the 45th ACM technical symposium on Computer science education, pages 103–108.
Wiegand, R. P., Bucci, A., Kumar, A. N., Albert, J., and Gaspar, A. (2021). Identifying informatively easy and informatively hard concepts. ACM Transactions on Computing Education (TOCE), 22(1):1–28.
Wiegand, R. P., Bucci, A., Kumar, A. N., Albert, J. L., and Gaspar, A. (2016). A data-driven analysis of informatively hard concepts in introductory programming. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education, pages 370–375.
Xie, B., Davidson, M. J., Li, M., and Ko, A. J. (2019). An item response theory evaluation of a language-independent cs1 knowledge assessment. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, pages 699–705.
Ali, M., Ghosh, S., Rao, P., Dhegaskar, R., Jawort, S., Medler, A., Shi, M., and Dasgupta, S. (2023). Taking stock of concept inventories in computing education: A systematic literature review. In Proceedings of the 2023 ACM Conference on International Computing Education Research-Volume 1, pages 397–415.
Almstrum, V. L., Henderson, P. B., Harvey, V., Heeren, C., Marion, W., Riedesel, C., Soh, L.-K., and Tew, A. E. (2006). Concept inventories in computer science for the topic discrete mathematics. In Working group reports on ITiCSE on Innovation and technology in computer science education, pages 132–145.
Barbosa, L. S., Fernandes, T. C., and Campos, A. M. (2011). Takkou: Uma ferramenta proposta ao ensino de algoritmos. In XVIII Workshop sobre Educaçao em Computaçao (WEI 2011).
Brasil (2022). Base nacional comum curricular (bncc) de computação. Anexo ao Parecer CNE/CEB nº 2/2022. Acesso em: 2 nov. 2024.
Brasil (2023). Lei nº 14.533, de 11 de janeiro de 2023. Institui a Política Nacional de Educação Digital e dá outras providências. Acesso em: 2 nov. 2024.
Braz, A. C. R., Carvalho, L. S., Oliveira, E. H., Oliveira, D. B., Bittencourt, R. A., Santana, B. L., and Pereira, F. D. (2021). Tradução e validação de um inventário de conceitos sobre programação introdutória. In Anais do XXXII Simpósio Brasileiro de Informática na Educação, pages 1253–1264. SBC.
Caceffo, R., de França, B., Gama, G., Benatti, R., Aparecida, T., Caldas, T., and Azevedo, R. (2017). An antipattern documentation about misconceptions related to an introductory programming course in c. In Technical Report 17-15, page 42. Institute of Computing, University of Campinas.
Caceffo, R., Frank-Bolton, P., Souza, R., and Azevedo, R. (2019). Identifying and validating java misconceptions toward a cs1 concept inventory. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, pages 23–29.
Caceffo, R., Gama, G., Benatti, R., Aparecida, T., Caldas, T., and Azevedo, R. (2018). A concept inventory for cs1 introductory programming courses in c. Institute of Computing, University of Campinas, Tech. Rep. IC-18-06, page 107.
Caceffo, R., Wolfman, S., Booth, K. S., and Azevedo, R. (2016). Developing a computer science concept inventory for introductory programming. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education, pages 364–369.
Dermeval, D., Coelho, J. A. d. M., and BITTENCOURT, I. I. (2020). Mapeamento sistemático e revisão sistemática da literatura em informática na educação. JAQUES, Patrícia Augustin; SIQUEIRA; Sean; BITTENCOURT, Ig; PIMENTEL, Mariano.(Org.) Metodologia de Pesquisa Científica em Informática na Educação: Abordagem Quantitativa. Porto Alegre: SBC.
Dewji, N., Wolfman, S. A., Herman, G. L., Porter, L., Taylor, C., and Vahrenhold, J. (2015). The cs concept inventory quiz show. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education, pages 669–670.
Duran, R., Bim, S. A., Gimenes, I., Ribeiro, L., and Correia, R. C. M. (2023). Potential factors for retention and intent to drop-out in brazilian computing programs. ACM Transactions on Computing Education, 23(3):1–33.
Evans, D., Gray, G. L., Krause, S., Martin, J., Midkiff, C., Notaros, B. M., Pavelich, M., Rancour, D., Reed-Rhoads, T., Steif, P., et al. (2003). Progress on concept inventory assessment tools. In 33rd Annual Frontiers in Education, 2003. FIE 2003., volume 1, pages T4G–1. IEEE.
Ferrao, R. C., Montagner, I. D. S., Caceffo, R., and Azevedo, R. (2022). How much c can students learn in one week? experiences teaching c in advanced cs courses. In 2022 IEEE frontiers in education conference (FIE), pages 1–8. IEEE.
Field, A. (2024). Discovering statistics using IBM SPSS statistics. Sage publications limited.
Fukao, A. T., Colanzi, T. E., Martimiano, L. A., and Feltrim, V. D. (2023). Estudo sobre evasao nos cursos de computaçao da universidade estadual de maringá. In Anais do III Simpósio Brasileiro de Educação em Computação, pages 86–96. SBC.
Goldman, K., Gross, P., Heeren, C., Herman, G. L., Kaczmarczyk, L., Loui, M. C., and Zilles, C. (2010). Setting the scope of concept inventories for introductory computing subjects. ACM Transactions on Computing Education (TOCE), 10(2):1–29.
Grover, S. (2020). Designing an assessment for introductory programming concepts in middle school computer science. In Proceedings of the 51st ACM Technical Symposium on Computer Science Education, pages 678–684.
Hamouda, S., Edwards, S. H., Elmongui, H. G., Ernst, J. V., and Shaffer, C. A. (2017). A basic recursion concept inventory. Computer Science Education, 27(2):121–148.
Henry, J. and Dumas, B. (2020). Developing an assessment to profile students based on their understanding of the variable programming concept. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education, pages 33–39.
Herman, G. L., Loui, M. C., and Zilles, C. (2010). Creating the digital logic concept inventory. In Proceedings of the 41st ACM technical symposium on Computer science education, pages 102–106.
Hestenes, D., Wells, M., Swackhamer, G., et al. (1992). Force concept inventory. The physics teacher, 30(3):141–158.
Julie, H. and Bruno, D. (2019). Towards the identification of profiles based on the understanding of programming concepts: the case of the variable. In 2019 IEEE Frontiers in Education Conference (FIE), pages 1–8. IEEE.
Julie, H. and Bruno, D. (2020). Approach to develop a concept inventory informing teachers of novice programmers’ mental models. In 2020 IEEE frontiers in education conference (FIE), pages 1–9. IEEE.
Julie, H., Bruno, D., Patrick, H., and Tony, L. (2020a). Object-oriented programming: Diagnosis understanding by identifying and describing novice perceptions. In 2020 IEEE Frontiers in Education Conference (FIE), pages 1–5. IEEE.
Julie, H., Tom, M., Antoine, C., Benoit, V., and Bruno, D. (2020b). A tangible-augmented concept inventory to identify novices’ misconceptions in programming. In 2020 15th international conference on computer science & education (ICCSE), pages 370–374. IEEE.
Kaczmarczyk, L. C., Petrick, E. R., East, J. P., and Herman, G. L. (2019). The first of the top ten sigcse symposium research papers of the last 50 years: Identifying student misconceptions of programming. ACM Inroads, 10(2):65–69.
Kennedy, C. and Kraemer, E. T. (2019). Qualitative observations of student reasoning: Coding in the wild. In Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education, pages 224–230.
Lu, K.-C. and Krishnamurthi, S. (2024). Identifying and correcting programming language behavior misconceptions. Proceedings of the ACM on Programming Languages, 8(OOPSLA1):334–361.
Luxton-Reilly, A., Becker, B. A., Cao, Y., McDermott, R., Mirolo, C., Mühling, A., Petersen, A., Sanders, K., Simon, and Whalley, J. (2018). Developing assessments to determine mastery of programming fundamentals. In Proceedings of the 2017 ITiCSE Conference on Working Group Reports, pages 47–69.
Parker, M. C., Davidson, M. J., Kao, Y. S., Margulieux, L. E., Tidler, Z. R., and Vahrenhold, J. (2023). Toward cs1 content subscales: A mixed-methods analysis of an introductory computing assessment. In Proceedings of the 23rd Koli Calling International Conference on Computing Education Research, pages 1–13.
Parker, M. C., Guzdial, M., and Engleman, S. (2016). Replication, validation, and use of a language independent cs1 knowledge assessment. In Proceedings of the 2016 ACM conference on international computing education research, pages 93–101.
Porter, L., Taylor, C., and Webb, K. C. (2014). Leveraging open source principles for flexible concept inventory development. In Proceedings of the 2014 conference on Innovation & technology in computer science education, pages 243–248.
Porter, L., Zingaro, D., Liao, S. N., Taylor, C., Webb, K. C., Lee, C., and Clancy, M. (2019). Bdsi: A validated concept inventory for basic data structures. In Proceedings of the 2019 ACM Conference on International Computing Education Research, pages 111–119.
Rachmatullah, A., Akram, B., Boulden, D., Mott, B., Boyer, K., Lester, J., and Wiebe, E. (2020). Development and validation of the middle grades computer science concept inventory (mg-csci) assessment. EURASIA Journal of Mathematics, Science and Technology Education, 16(5):em1841.
Saarinen, S., Krishnamurthi, S., Fisler, K., and Tunnell Wilson, P. (2019). Harnessing the wisdom of the classes: Classsourcing and machine learning for assessment instrument generation. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, pages 606–612.
Semesp, I. (2023). 13º mapa do ensino superior no brasil 2023. Acesso em: 2 nov. 2024.
Sherman, A. T., Herman, G. L., Oliva, L., Peterson, P. A., Golaszewski, E., Poulsen, S., Scheponik, T., and Gorti, A. (2020). Experiences and lessons learned creating and validating concept inventories for cybersecurity. In National Cyber Summit, pages 3–34. Springer.
Stephens-Martinez, K., Ju, A., Parashar, K., Ongowarsito, R., Jain, N., Venkat, S., and Fox, A. (2017). Taking advantage of scale by analyzing frequent constructed-response, code tracing wrong answers. In Proceedings of the 2017 ACM Conference on International Computing Education Research, pages 56–64.
Taylor, C., Zingaro, D., Porter, L., Webb, K. C., Lee, C. B., and Clancy, M. (2014). Computer science concept inventories: past and future. Computer Science Education, 24(4):253–276.
Vahrenhold, J. and Paul, W. (2014). Developing and validating test items for first-year computer science courses. Computer science education, 24(4):304–333.
Webb, K. C. and Taylor, C. (2014). Developing a pre-and post-course concept inventory to gauge operating systems learning. In Proceedings of the 45th ACM technical symposium on Computer science education, pages 103–108.
Wiegand, R. P., Bucci, A., Kumar, A. N., Albert, J., and Gaspar, A. (2021). Identifying informatively easy and informatively hard concepts. ACM Transactions on Computing Education (TOCE), 22(1):1–28.
Wiegand, R. P., Bucci, A., Kumar, A. N., Albert, J. L., and Gaspar, A. (2016). A data-driven analysis of informatively hard concepts in introductory programming. In Proceedings of the 47th ACM Technical Symposium on Computing Science Education, pages 370–375.
Xie, B., Davidson, M. J., Li, M., and Ko, A. J. (2019). An item response theory evaluation of a language-independent cs1 knowledge assessment. In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, pages 699–705.
Publicado
07/04/2025
Como Citar
ORTIZ, Inara Santana; CASTRO JUNIOR, Amaury Antônio; LIMA, Anderson Corrêa de.
Revisão Sistemática sobre Inventário de Conceitos aplicados em disciplinas introdutórias de cursos de computação. In: SIMPÓSIO BRASILEIRO DE EDUCAÇÃO EM COMPUTAÇÃO (EDUCOMP), 5. , 2025, Juiz de Fora/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 127-140.
ISSN 3086-0733.
DOI: https://doi.org/10.5753/educomp.2025.5280.
