Blogs (19) >>
Thu 16 Mar 2023 16:10 - 16:35 at 801B - Detecting Plagiarism and AI Code Generation Chair(s): Lauren Bricker

Recent work in computing education has explored the idea of analyzing and grading using the process of writing a computer program rather than just the final submitted code. We build on this idea by investigating the effect on plagiarism when the process of coding, in the form of keystroke logs, is submitted for grading in addition to the final code. We report results from two terms of a university CS1 course in which students submitted keystroke logs. We find that when students are required to submit a log of keystrokes together with their written code they are less likely to plagiarize. In this paper we explore issues of implementation, adoption, deterrence, anxiety, and privacy. Our keystroke logging software is available in the form of an IDE plugin in a public plugin repository.

Thu 16 Mar

Displayed time zone: Eastern Time (US & Canada) change

15:45 - 17:00
Detecting Plagiarism and AI Code GenerationPapers at 801B
Chair(s): Lauren Bricker University of Washington
15:45
25m
Paper
Impact of Several Low-Effort Cheating-Reduction Methods in a CS1 ClassCCIn-Person
Papers
Frank Vahid UC Riverside / zyBooks, Kelly Downey UC Riverside, Ashley Pang UC Riverside, Chelsea Gordon Zybooks
DOI
16:10
25m
Paper
Plagiarism Deterrence in CS1 Through Keystroke DataCCIn-Person
Papers
Kaden Hart Utah State University, Chad Mano Utah State University, John Edwards Utah State University
DOI
16:35
25m
Paper
Programming Is Hard - Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code GenerationCCIn-PersonPCI Best PaperGlobal
Papers
Brett Becker University College Dublin, Paul Denny The University of Auckland, James Finnie-Ansley The University of Auckland, Andrew Luxton-Reilly The University of Auckland, James Prather Abilene Christian University, Eddie Antonio Santos University College Dublin
DOI