An Investigation of Machine Learning-Based Plagiarism Detection in Computer Programming

Brief Paper (Asynchronous) ID: 59425
  1. Michael Cao
    The Pennsylvania State University
  2. aaa
    Wei-Fan Chen
    The Pennsylvania State University

Abstract: This paper proposes the improvement of machine learning-based plagiarism detection systems in college-level computer science courses. Current plagiarism detection systems have been previously developed for other fields, but lack the inability to work accurately and efficiently in the field of computer science. As there are many factors to be considered in the reason why there is no such perfect system yet and, in the requirements, to develop such a system, this paper explores the challenges, needs, and benefits associated with the creation, development, and implementation of such a system. It is hoped to display the need for further development of such a system to further improve the process of plagiarism detection within the field of computer science, and to minimize human involvement in the process.

Topic

Conference attendees are able to comment on papers, view the full text and slides, and attend live presentations. If you are an attendee, please login to get full access.
x