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Abstract: In this paper we present a new cheating technique that is successful at defeating cheating detectors and could become popular with students. The idea is to use obfuscating code transformations (such as those found in the SANDMARK tool) to apply a sequence of minor code transformations to a copied programming assignment. This purpose is to produce a copy that will defeat detection. We show that this technique is successful in defeating common plagiarism detectors such as Moss. This paper is offered as a cautionary tale to the Computer Science teaching community. With the advent of powerful code transformation tools it will become necessary to develop correspondingly more powerful cheating detectors, or to revert back to manually testing for plagiarism.

Many computer science teachers are very concerned about students cheating in their courses. Surveys report that almost three-quarters of high school students admit to cheating within the past year. John Barrie, founder of the plagiarism-detecting Web site Turnitin.com, says that about a third of the papers submitted to the site have significant levels of plagiarism.

Enrollment in undergraduate computer science courses is at an all-time high at colleges nationwide. But this trend that's been hailed by the U.S. tech industry has a dark side: a disproportionate number of students taking these courses are caught cheating. Enrollment in undergraduate computer science courses is at an all-time high at colleges nationwide.

Online-teaching pioneers such as Coursera and Udacity are beaming top professors' lessons into students' homes worldwide, while slashing costs, getting rid of stuffy lecture halls and improving public access. But they're having a harder time with one of teaching's eternal headaches: stopping students' cheating. The Chronicle of Higher Education this week [...]

Cheating in American high schools is widespread if not endemic. And it usually works. That's the report card from American teenagers. In an exclusive ABCNEWS Primetime poll of 12- to 17-year-olds, seven in 10 say at least some kids in their school cheat on tests. Six in 10 have friends who've...

Ethical Issues of Online Cheating

We describe a cheating strategy enabled by the features of massive open online courses (MOOCs) and detectable by virtue of the sophisticated data systems that MOOCs provide. The strategy, Copying Answers using Multiple Existences Online (CAMEO), involves a user who gathers solutions to assessment questions using a "harvester" account and then submits correct answers using a separate "master" account. We use "clickstream" learner data to detect CAMEO use among 1.9 million course participants in 115 MOOCs from two universities. Using conservative thresholds, we estimate CAMEO prevalence at 1,237 certificates, accounting for 1.3% of the certificates in the 69 MOOCs with CAMEO users. Among earners of 20 or more certificates, 25% have used the CAMEO strategy. CAMEO users are more likely to be young, male, and international than other MOOC certificate earners. We identify preventive strategies that can decrease CAMEO rates and show evidence of their effectiveness in science courses.

Abstract - Program assignments are traditionally an area of serious concern in maintaining the integrity of the educa- tional process. Systematic inspection of all solutions for pos- sible plagiarism has generally required unrealistic amounts of time and effort. The "Measure Of Software Similarity" tool developed by Alex Aiken at UC Berkeley makes it pos- sible to objectively and automatically check all solutions for evidence of plagiarism. We have used MOSS in several large sections of a C programming course. (MOSS can also handle a variety of other languages.) We feel that MOSS is a major innovation for faculty who teach programming and recom- mend that it be used routinely to screen for plagiarism.

Editorial Board | Tuesday, November 11 2014Some students enrolled in Computer Science 201 found themselves especially anxious evening. The cause wasn't an upcoming midterm exam, but an email from the computer science department notifying students of an investigation into cheating in the class.

This article examines how student perception of cheating has changed throughout the years

MOSS is effective in detecting similar structures in nearly every different type of language that we use here at the University at Buffalo, including C, C++, Java, LISP, Perl, Python, Scheme, Matlab and Prolog. As you can guess, it is not fooled by renaming variables, rearranging or functionalizing blocks of code, extracting code to different modules or files, or the placing of NOP or junk code between useful codes. MOSS can also exclude matching base files (code supplied by instructors or TAs) and it can exclude the consideration of code that is matched across many different submissions (code perhaps supplied by a coding book or website, like a sorting algorithm, that is not central to the assignment).

Emma Baccellieri | Thursday, November 6 2014The computer science department has launched an investigation into academic integrity violations in core course Computer Science 201. All students who are currently enrolled in the class and who took the class in Spring 2014 received an email Wednesday night, notifying them that concerns about academic dishonesty have prompted a review of assignments.

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