Addressing student cheating

Dick, Martin; Sheard, Judy; Bareiss, Cathy; Carter, Janet; Joyce, Donald; Harding, Trevor S.; Laxer, Cary

doi:10.1145/960568.783000

Cited by 17 publications

(2 citation statements)

References 10 publications

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“…Plagiarism is a form of academic cheating that occurs by copying other people's work and consider it as their own . In programming courses (where most works submitted for the assessments are source codes), overcoming this issue is not a trivial task considering three rationales.…”

Section: Related Workmentioning

confidence: 99%

ES‐Plag: Efficient and sensitive source code plagiarism detection tool for academic environment

Sulistiani

Karnalim

2018

Comp Applic In Engineering

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Source code plagiarism detection using Running‐Karp‐Rabin Greedy‐String‐Tiling (RKRGST) is a common practice in academic environment. However, such approach is time‐inefficient (due to RKRGST's cubic time complexity) and insensitive (toward token subsequence rearrangement). This paper proposes ES‐Plag, a plagiarism detection tool featured with cosine‐based filtering and penalty mechanism to handle aforementioned issues. Cosine‐based filtering mitigates time‐inefficiency by excluding non‐potential pairs from RKRGST comparison; while penalty mechanism mitigates insensitivity by reducing the number of matched tokens with the number of matched subsequences prior similarity normalization. In addition to issue‐solving features, ES‐Plag is also featured with project‐based input, colorized adjacency similarity matrix, matched token highlighting, and various similarity algorithms (e.g., Cosine Similarity and Local Alignment). Three findings can be deducted from our evaluation. First, cosine‐based filtering boosts up time efficiency with a trade‐off in effectiveness. Second, penalty mechanism enhances sensitivity even though its improvement in terms of effectiveness is quite limited. Third, ES‐Plag's features are beneficial for examiners.

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Section: Related Workmentioning

confidence: 99%

ES‐Plag: Efficient and sensitive source code plagiarism detection tool for academic environment

Sulistiani

Karnalim

2018

Comp Applic In Engineering

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“…unsolicited collaboration on assignments, public posting of solutions, reuse of past year solutions) as serious offences ((Dick et al 2001;Sheard & Dick 2003;Cosma & Joy 2006), even if these are explicitly prohibited by the Student code of conduct. Detection of similarities between student assignment solutions can be used to prevent cheating (Dick et al 2003). The presence of such a system, publicly announced, discourages cheating.…”

Section: Related Workmentioning

confidence: 99%

SOURCE CODE VALIDATION AND PLAGIARISM DETECTION - Technology-rich Course Experiences

Bosnić

Mihaljević

Orlić

et al. 2012

Proceedings of the 4th International Conference on Computer Supported Education

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Learning various programming languages in a short amount of time is a challenging task. To help students tackle several programming languages during the course of a semester, while reducing the teaching assistants' support efforts, a system named ORVViS was implemented and integrated with Moodle Learning Management System. ORVViS is used to assist students validate assignment solutions, and also to check for source code plagiarism. This paper presents the course Open computing, our motivation, system use cases, as well as our results and experiences. These observations helped us improve the assignments to better suit our teaching goals and help students learn the course concepts more quickly.

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