Moopec: A Tool for Creating Programming Problems

Author Rui C. Mendes



PDF
Thumbnail PDF

File

OASIcs.ICPEC.2021.9.pdf
  • Filesize: 0.6 MB
  • 7 pages

Document Identifiers

Author Details

Rui C. Mendes
  • Centro Algoritmi, Departamento de Informática, University of Minho, Braga, Portugal
  • www.di.uminho.pt/ rcm/

Acknowledgements

I want to thank Pedro Ribeiro for gently supplying the script used for providing the feedback shown in Fig. 1.

Cite As Get BibTex

Rui C. Mendes. Moopec: A Tool for Creating Programming Problems. In Second International Computer Programming Education Conference (ICPEC 2021). Open Access Series in Informatics (OASIcs), Volume 91, pp. 9:1-9:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/OASIcs.ICPEC.2021.9

Abstract

This paper presents a tool called Mooshak ProblEm Creator (Moopec) for facilitating the creation of programming exercises for a web-based multi-site programming contest system called Mooshak [Leal and Silva, 2003]. Users only need to create a text file for specifying all the information concerning problems including their description, tests and user feedback. This tool provides ways of automating most tasks involved in creating problems in Mooshak and, consequently, increases teachers' productivity. Moopec allows instructors to quickly create problem sets by simply editing a text file. Moopec is implemented in Python and is available at https://github.com/rcm/mooshak_problem_creator.

Subject Classification

ACM Subject Classification
  • Applied computing → Computer-managed instruction
Keywords
  • Automatic Program Assessment
  • Batch Generation
  • Testing

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Matt Bower. A taxonomy of task types in computing. In Proceedings of the 13th annual conference on Innovation and technology in computer science education, pages 281-285, 2008. Google Scholar
  2. Codeboard. https://codeboard.io/. Accessed: 2021-04-07.
  3. Michal Forišek. On the suitability of programming tasks for automated evaluation. Informatics in education, 5(1):63-76, 2006. Google Scholar
  4. International collegiate programming contest. https://icpc.global/. Accessed: 2021-04-07.
  5. International olympiads in informatics. https://ioinformatics.org/. Accessed: 2021-04-07.
  6. Tony Jenkins. On the difficulty of learning to program. In Proceedings of the 3rd Annual Conference of the LTSN Centre for Information and Computer Sciences, volume 4, pages 53-58. Citeseer, 2002. Google Scholar
  7. José Paulo Leal and Fernando Silva. Mooshak: A web-based multi-site programming contest system. Software: Practice and Experience, 33(6):567-581, 2003. Google Scholar
  8. José Carlos Paiva, Ricardo Queirós, José Paulo Leal, and Jakub Swacha. Yet Another Programming Exercises Interoperability Language (Short Paper). In Alberto Simões, Pedro Rangel Henriques, and Ricardo Queirós, editors, 9th Symposium on Languages, Applications and Technologies (SLATE 2020), volume 83 of OpenAccess Series in Informatics (OASIcs), pages 14:1-14:8, Dagstuhl, Germany, 2020. Schloss Dagstuhl-Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/OASIcs.SLATE.2020.14.
  9. Dale Parsons and Patricia Haden. Parson’s programming puzzles: a fun and effective learning tool for first programming courses. In Proceedings of the 8th Australasian Conference on Computing Education-Volume 52, pages 157-163, 2006. Google Scholar
  10. Ricardo Queirós and José Paulo Leal. Babelo—an extensible converter of programming exercises formats. IEEE Transactions on Learning Technologies, 6(1):38-45, 2012. Google Scholar
  11. Alberto Simões and Ricardo Queirós. On the Nature of Programming Exercises. In Ricardo Queirós, Filipe Portela, Mário Pinto, and Alberto Simões, editors, First International Computer Programming Education Conference (ICPEC 2020), volume 81 of OpenAccess Series in Informatics (OASIcs), pages 24:1-24:9, Dagstuhl, Germany, 2020. Schloss Dagstuhl-Leibniz-Zentrum für Informatik. URL: https://doi.org/10.4230/OASIcs.ICPEC.2020.24.
  12. Manfred Stienstra, Yuri takhteyev, Waylan limberg, and Waylan Limberg. Python-markdown. https://pypi.org/project/Markdown/. Accessed: 2021-04-07.
  13. Errol Thompson, Andrew Luxton-Reilly, Jacqueline L Whalley, Minjie Hu, and Phil Robbins. Bloom’s taxonomy for cs assessment. In Proceedings of the tenth conference on Australasian computing education-Volume 78, pages 155-161, 2008. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail