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JPlag – Detecting Software Plagiarism

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Re: JPlag – Detecting Software Plagiarism

#31

Earlier quoted context omitted.

It’s no secret that huge portion of all students are cheating or plagiarizing - let’s not pretend it’s only international students. My few data points being a TA for many years at a top engineering school: about 70% of the cases I reported for violations were domestic students.

Depending on the distribution of international / domestic students, this also sounds wild and in congruence with the other commenter. If there is 10 out of 100 international students, and they do 30% of 10 cases, then 30% (!!) of international students cheat while only 7% of domestic students cheat - in conclusion, international students do most of the cheating. Regardless of this statistical thought experiment, I do…

This is a silly game. At MIT, 29.1% of students are international. [1]

[1] https://facts.mit.edu/enrollment-statistics/

Re: JPlag – Detecting Software Plagiarism

#32

Earlier quoted context omitted.

It’s no secret that huge portion of all students are cheating or plagiarizing - let’s not pretend it’s only international students. My few data points being a TA for many years at a top engineering school: about 70% of the cases I reported for violations were domestic students.

Depending on the distribution of international / domestic students, this also sounds wild and in congruence with the other commenter. If there is 10 out of 100 international students, and they do 30% of 10 cases, then 30% (!!) of international students cheat while only 7% of domestic students cheat - in conclusion, international students do most of the cheating. Regardless of this statistical thought experiment, I do…

In my experience as a TA, ChatGPT has leveled the playing field. Previously, some nationalities cheated significantly more often, but now almost everyone (at least 85 %, probably more) cheat with ChatGPT. There is not much point in providing homework assignments anymore.

Re: JPlag – Detecting Software Plagiarism

#33
post #2

I recently had to check code from some of my students at the university as I suspected plagiarism. I discovered JPlag which works like a charm and generates nice reports

Next time just ask them a few questions about the programming choices they made. Far easier.

Re: JPlag – Detecting Software Plagiarism

#34
post #31

Earlier quoted context omitted.

Depending on the distribution of international / domestic students, this also sounds wild and in congruence with the other commenter. If there is 10 out of 100 international students, and they do 30% of 10 cases, then 30% (!!) of international students cheat while only 7% of domestic students cheat - in conclusion, international students do most of the cheating. Regardless of this statistical thought experiment, I do…

This is a silly game. At MIT, 29.1% of students are international. [1] [1] https://facts.mit.edu/enrollment-statistics/

Same link confirms that only 11% of undergrads are international students.

Re: JPlag – Detecting Software Plagiarism

#35
post #9

It's funny how we drill the idea that everything must be reimplemented from first principles into students, only to flip that when they join the workforce.

> only to flip that when they join the workforce.

A surprisingly large number of people do not realise that code on StackOverflow is under a relatively restrictive license.

https://meta.stackexchange.com/questions/12527/do-i-have-to-...

Some companies take this very seriously and others do not care at all. And, of course, there are companies that outright ban any library without the right licence.

Re: JPlag – Detecting Software Plagiarism

#36

Earlier quoted context omitted.

It’s no secret that huge portion of all students are cheating or plagiarizing - let’s not pretend it’s only international students. My few data points being a TA for many years at a top engineering school: about 70% of the cases I reported for violations were domestic students.

Depending on the distribution of international / domestic students, this also sounds wild and in congruence with the other commenter. If there is 10 out of 100 international students, and they do 30% of 10 cases, then 30% (!!) of international students cheat while only 7% of domestic students cheat - in conclusion, international students do most of the cheating. Regardless of this statistical thought experiment, I do…

Yes, given made up numbers you can support an unsubstantiated claim. Let's not do that.

Re: JPlag – Detecting Software Plagiarism

#37

Earlier quoted context omitted.

You might be surprised. Many students who use ChatGPT for assignments end up turning in code identical (or nearly identical) to other students who use ChatGPT.

Surprising because you get different answers each time you ask ChatGPT.

Different in an exact string match but code that is copied and pasted from ChatGPT has a lot of similarities in the way that it is (over) commented. I've seen a lot of Python where the student who "authored" it cannot tell me how a method works or why it was implemented despite having the comments prefixed to every line in the file.

Re: JPlag – Detecting Software Plagiarism

#38
post #2

I recently had to check code from some of my students at the university as I suspected plagiarism. I discovered JPlag which works like a charm and generates nice reports

How do you deal with disputes? One's code is flagged even if the student in question didn't actually cheat. What then? Do you trust tools over the students' word? In addition, do things like stack overflow and using LLM-generated code count as cheating? Because that is horrible in and of itself, though a separate concern.

The output of plagiarism tools should only serve as a hint to look at a pair of solutions more closely. All judgement should be derived entirely from similarities between solutions and not some artificial similarity score computed by some program.

Re: JPlag – Detecting Software Plagiarism

#39

Earlier quoted context omitted.

Surprising because you get different answers each time you ask ChatGPT.

Different in an exact string match but code that is copied and pasted from ChatGPT has a lot of similarities in the way that it is (over) commented. I've seen a lot of Python where the student who "authored" it cannot tell me how a method works or why it was implemented despite having the comments prefixed to every line in the file.

Ah yes, good old "Did you even read the essay before handing it in? Next time, please do."

Re: JPlag – Detecting Software Plagiarism

#40

Earlier quoted context omitted.

How do you deal with disputes? One's code is flagged even if the student in question didn't actually cheat. What then? Do you trust tools over the students' word? In addition, do things like stack overflow and using LLM-generated code count as cheating? Because that is horrible in and of itself, though a separate concern.

The output of plagiarism tools should only serve as a hint to look at a pair of solutions more closely. All judgement should be derived entirely from similarities between solutions and not some artificial similarity score computed by some program.

Unfortunately, this is not really what happens in my experience. The output of plagiarism tools is taken as fact (especially at high school levels). Without extraordinary evidence of the tool being incorrect, students have no recourse, even if they could sit and explain the thought process behind every word/line of code/whatever.
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