Automated Correction for Trace Tables in a CS1 Course

  • Fernando Teubl UFABC
  • Francisco Zampirolli UFABC

Resumo


This work presents a remote, asynchronous, parametric, and automatically corrected evaluation based on the Trace Table method for an introductory programming course. Moodle was used as the learning platform, VPL as the evaluation module/interface, and MCTest as the test generator. The Trace Table method allows for the analysis of students’ knowledge in pseudocode, without relying on any specific programming language. The answers were formatted in a table, and the evaluations were automatically corrected during the student’s problem-solving process. Two evaluations were applied throughout the course: an intermediate and a final. The course had 309 students and the results indicated a high acceptance rate, with over 80% approval of the method.

Referências

Brusilovsky, P., Edwards, S., Kumar, A., Malmi, L., Benotti, L., Buck, D., Ihantola, P., Prince, R., Sirkiä, T., Sosnovsky, S., Urquiza, J., Vihavainen, A., and Wollowski, M. (2014). Increasing adoption of smart learning content for computer science education. In ITiCSE-WGR, pages 31–57.

Combéfis, S. (2022). Automated code assessment for education: review, classification and perspectives on techniques and tools. Software, 1(1):3–30.

Mendoza, B. and Zavala, L. (2018). An intervention strategy to hone students’ code under-standing skills. Journal of Computing Sciences in Colleges, 33(3):105–114.

Paiva, J. C., Leal, J. P., and Figueira, A. (2022). Automated assessment in computer science education: A state-of-the-art review. ACM Transactions on Computing Education, 22(3):1–40.

Risha, Z. and Brusilovsky, P. (2020). Making it smart: Converting static code into an interactive trace table. In Proc. of Sixth SPLICE Workshop.

Rodríguez del Pino, J. C., Rubio Royo, E., and Hernández Figueroa, Z. J. (2010). VPL: laboratorio virtual de programación para moodle. In Jornadas de Enseñanza Universitaria de la Informática, pages 429–435.

Zampirolli, F. A., Borovina Josko, J. M., Venero, M. L., Kobayashi, G., Fraga, F. J., Goya, D., and Savegnago, H. R. (2021a). An experience of automated assessment in a large-scale introduction programming course. Computer Applications in Engineering Education, 29(5):1284–1299.

Zampirolli, F. A., Teubl, F., and Batista, V. (2019). Online generator and corrector of parametric questions in hard copy useful for the elaboration of thousands of individualized exams. In CSEDU, pages 352–359.

Zampirolli, F. A., Teubl, F., Kobayashi, G., Neves, R., Rozante, L., and Batista, V. (2021b). Introductory computer science course by adopting many programming languages. In SBIE, pages 1118–1127, Porto Alegre, RS, Brasil. SBC.

Zavala, L. and Mendoza, B. (2017). Precursor skills to writing code. Journal of Computing Science in Colleges, 32(3):149–156.
Publicado
06/11/2023
TEUBL, Fernando; ZAMPIROLLI, Francisco. Automated Correction for Trace Tables in a CS1 Course. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 34. , 2023, Passo Fundo/RS. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 1546-1556. DOI: https://doi.org/10.5753/sbie.2023.233468.