Measuring Plagiarism in Introductory Programming Course Assignments

Autor:	Humayoun, Muhammad, Hashmi, Muhammad Adnan, Khan, Ali Hanzala
Rok vydání:	2022
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence
Druh dokumentu:	Working Paper
Popis:	Measuring plagiarism in programming assignments is an essential task to the educational procedure. This paper discusses the methods of plagiarism and its detection in introductory programming course assignments written in C++. A small corpus of assignments is made publically available. A general framework to compute the similarity between a solution pair is developed that uses the three token-based similarity methods as features and predicts if the solution is plagiarized. The importance of each feature is also measured, which in return ranks the effectiveness of each method in use. Finally, the artificially generated dataset improves the results compared to the original data. We achieved an F1 score of 0.955 and 0.971 on original and synthetic datasets. Comment: Accepted at IEEE conference, the 2022 8th International Conference on Information Technology Trends (ITT), at Higher Colleges of Technology - Dubai Men's Campus on 25-26 May 2022, Dubai, United Arab Emirates
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2205.08520 Zobrazit plný text záznamu View this record from Arxiv