draft syllabus statement on code, plagiarism, and generative AI

I’m spending a chunk of today starting on revisions to my Intro to Data Science course for my unit’s LIS and ICT graduate prograrms. I’d expected to spend most of the time shuffling around the content and assessment for particular weeks, but I quickly realized that I was going to need to update what I had to say in the syllabus about plagiarism and academic offenses. Last year’s offering of the course involved a case of potential plagiarism, so I wanted to include more explicit instruction that encourages students to borrow code while making it clear that there are right and wrong ways of doing so.

Just had a long conversation with a student that reminded me that we cannot (and should not try to) assess that which we do not effectively teach.

This semester, my efforts to trust students feel like they’re backfiring. I ungrade, but they don’t take work seriously. I never use plagiarism checkers, but I still have to deal with a last minute case. Not saying I’ll stop effort, but still sucks.

Family has been sick for the last week, and it’s been a struggle to keep up with grading even after cancelling nearly all my other commitments. Thought I was in the clear this morning, only for the first final project I opened to turn into suspected plagiarism. 😩

In a training last week, we discussed the trend of journals’ checking manuscripts with plagiarism software. People shared examples where editors couldn’t accept perfectly good reasons for authors to reuse material unless a certain software score was also reached.

In addition to cheating being flat-out wrong, students should also consider just how much regulation-reading and paperwork it creates for their professors.