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dc.contributor.authorMani, Anaga
dc.contributor.authorVenkataramani, Divya
dc.contributor.authorPetit Silvestre, Jordi
dc.contributor.authorRoura Ferret, Salvador
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.identifier.citationMani, A. [et al.]. Better feedback for educational online judges. A: International Conference on Computer Supported Education. "Proceedings of the 6th International Conference on Computer Supported Education, Volume 2: Barcelona, Spain, 1-3 April, 2014". Barcelona: SciTePress, 2014, p. 176-183.
dc.description.abstractThe verdicts of most online programming judges are, essentially, binary: the submitted codes are either “good enough” or not. Whilst this policy is appropriate for competitive or recruitment platforms, it can hinder the adoption of online judges on educative settings, where it could be adequate to provide better feedback to a student (or instructor) that has submitted a wrong code. An obvious option would be to just show him or her an instance where the code fails. However, that particular instance could be not very significant, and so could induce unreflectively patching the code. The approach considered in this paper is to data mine all the past incorrect submissions by all the users of the judge, so to extract a small subset of private test cases that may be relevant to most future users. Our solution is based on parsing the test files, building a bipartite graph, and solving a Set Cover problem by means of Integer Linear Programming. We have tested our solution with a hundred problems in Those experiments suggest that our approach is general, efficient, and provides high quality results.
dc.format.extent8 p.
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subjectÀrees temàtiques de la UPC::Ensenyament i aprenentatge::TIC’s aplicades a l’educació
dc.subject.lcshData mining
dc.subject.lcshComputer-assisted instruction
dc.subject.otherOnline programming judges
dc.subject.otherAutomatic assessment
dc.subject.otherData mining
dc.titleBetter feedback for educational online judges
dc.typeConference report
dc.subject.lemacMineria de dades
dc.subject.lemacEnsenyament assistit per ordinador
dc.contributor.groupUniversitat Politècnica de Catalunya. ALBCOM - Algorismia, Bioinformàtica, Complexitat i Mètodes Formals
dc.rights.accessOpen Access
dc.description.versionPostprint (author’s final draft)
upcommons.citation.authorMani, A.; Venkataramani, D.; Petit, J.; Roura, S.
upcommons.citation.contributorInternational Conference on Computer Supported Education
upcommons.citation.publicationNameProceedings of the 6th International Conference on Computer Supported Education, Volume 2: Barcelona, Spain, 1-3 April, 2014

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