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Plagiarism Detection in Algorithms - a Case Study using Algorithmi
Publication . Manso, António; Marques, C. G.; Santos, Paulo; Alencar, Vitor
Learning to program is crucial in computer science degree programmes. For students to gain this skill, they need to practise a lot, since programming is a difficult and complex process and practice improves it. The courses "Algorithmics" and "Introduction to programming" have therefore become almost insurmountable barriers with high failure rates. To overcome these barriers, researchers have sought to find new ways of teaching. For their part, students have looked for ways to succeed with less effort by repeatedly resorting to plagiarism. The need for classes to be taught remotely due to the pandemic has further aggravated this problem. To fight it, we created the Algorithmi tool and equipped it with a plagiarism detection module. This tool promotes stand-alone study by allowing self-correction of the exercises whilst validating authorship. This paper presents a case study on the application of the plagiarism module to the exercise resolutions submitted by the students in their personal repository. Through the analysis of the results obtained we can conclude that there was a high rate of plagiarism. The current version of the tool needs to be extended with new features, not only to become more accurate, but above all to prevent plagiarism from happening.
2020Conference object Open access Show more