Kirstukas, S. J. (2018, June), Detection and Incidence of Plagiarism in a Solid Modeling Course  Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. 10.18260/1-2--30287

\bibitem{asee_peer_30287}
  Kirstukas, S. J. (2018, June), \emph{Detection and Incidence of Plagiarism in a Solid Modeling Course}
  Paper presented at 2018 ASEE Annual Conference \& Exposition , Salt Lake City, Utah.
  10.18260/1-2--30287

Steven Joseph Kirstukas.  "Detection and Incidence of Plagiarism in a Solid Modeling Course".  2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah, 2018, June.  ASEE Conferences, 2018.  https://peer.asee.org/30287 Internet.  14 Jan, 2025

\bibitem{asee_peer_30287}
  Steven Joseph Kirstukas.
  "Detection and Incidence of Plagiarism in a Solid Modeling Course".
  \emph{2018 ASEE Annual Conference \& Exposition , Salt Lake City, Utah, 2018, June}.
  ASEE Conferences, 2018.
  https://peer.asee.org/30287 Internet.  14 Jan, 2025

@INPROCEEDINGS{asee_peer_30287
author = "Steven Joseph Kirstukas"
title = "Detection and Incidence of Plagiarism in a Solid Modeling Course"
booktitle = "2018 ASEE Annual Conference \& Exposition "
year = "2018"
month = "June"
address = "Salt Lake City, Utah"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/30287}
number = {10.18260/1-2--30287}
}

TY  - CPAPER
AB  - This research paper presents the method used and results of a study in plagiarism detection of solid models. To aid in detecting plagiarism, a computer program was written that runs within a specific CAD package on the instructor’s computer. When a solid model is opened, this program reads the complete history that is stored within the CAD file. This history contains all save dates and times, a hardware identifier corresponding to each save time, and previous file names. For files that were created at the same times on the same machines, are older than expected, or have unexpected originating names, these files can be placed into one of twelve different categories that that predict whether a particular file is probable plagiarism, near-certain plagiarism, near-certain self-plagiarism, or a false positive. In this paper, the program was used to examine the incidence of these types of plagiarism over fourteen semesters during a seven-year period. We have found plagiarism in this CAD course to be a relatively uncommon occurrence, but nevertheless present in 1-2% of all submitted files, and has involved as many as 16% of all students in a particular section. Because we can now detect plagiarism, we hope that this will discourage future plagiarism and instead help students learn to be effective and efficient part modelers. 
AU  - Steven Joseph Kirstukas
CY  - Salt Lake City, Utah
DA  - 2018/06/23
PB  - ASEE Conferences
TI  - Detection and Incidence of Plagiarism in a Solid Modeling Course
UR  - https://peer.asee.org/30287
DO  - 10.18260/1-2--30287
ER  -