The Application Of Intelligent Context-Aware Systems To The Detection Of Online Student Cheating – Video Post

Here is the video version of a presentation for the ICAS 2013 workshop. I’m unable to attend this workshop in person as I’m attending ITiCSE 2013 at the same time, however one of my colleagues will provide the presentation at the workshop on my behalf.

The presentation looks at applying the growing research area of intelligent context-aware systems to one of my main research fields of student cheating and plagiarism. I’ve selected three particular problems within the field and proposed some initial solutions which use this type of computer systems.

This area is very much a work-in-progress, as there are several other plagiarism, cheating and academic integrity related problems which I could have selected. Further, with some more development of solutions, each one of these concerns could easily form the basis for a paper on its own.

My intention here is to open up the discussion, and ideas for research focus, solutions and collaboration opportunities are welcome.

The slides are also available here in my SlideShare account.

Who Are You Paying For Assignments?

Just spotted an interesting little remark as part of an online discussion about cheating:

We also had a student to went to one of the contract-cheating sites to do his program.  We then set him up so the offer to code came from one of our own grad students.  When he paid for the code, he was dismissed from the university.

I don’t think that anyone would debate that paying someone else to do an assignment for them is wrong.

There are lots of ways to being caught contract cheating, but paying someone is one of the worst (I wonder if the student got his money back?).

I think that the penalty, in this case, sends out the right message. What do you think?

Plagiarism Indicators For Academics

All academics, regardless of the level of the student, need to be aware that some students may take short cuts when producing academic work.

These slides (from my SlideShare account) outline five different indicators that work submitted may not all be the student’s own.

 

Many times, what you find when marking work will just be an indicator that something is out of place. This can lead to a more thorough search by hand.

TurnItIn, and other similar tools, are excellent as starting points, but often a specific Google search can identify parts of the web that are hidden to TurnItIn, so this approach is particularly useful.

 

What other indicators do academics use? Have you found any interesting plagiarism cases using indicators? Use the Comments box to share your findings.

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