ePrints.FRI - University of Ljubljana, Faculty of Computer and Information Science

Metode za pomoč pri zaznavi plagiatorstva

Žiga Makuc (2013) Metode za pomoč pri zaznavi plagiatorstva. EngD thesis.

[img]
Preview
PDF
Download (2034Kb)

    Abstract

    Modern technologies enable students to interact with each other much eas¬ier than in the past. This enables students to help each other with their school assignments, which can quickly lead to plagiarism. The purpose of this diploma thesis was to create an application which simplifies detecting plagiarism. It also has some functionalities which connect to social media websites and can add valuable information in detecting plagiarism. The application is designed in such a way that user can upload student submissions and then check them for plagiarism. This application supports source code plagiarism detection. After submissions have been checked (with external provider -Moss), the user can create visualisations which are based on retrieved data. Currently two types of visualisations are implemented ¬Graph visualisation of plagiarism and Co-Occurrence Matrix visualisation. The user can then check each plagiate and confirm or reject it. With that he can later create a list of persons which are potential plagiators and invite them on an interview to verify the suspicion of plagiarism. This application supports multiple assignments, so that the user can track each person for plagiarism through all assignments. Connection to social media websites such as Facebook and Twitter is also implemented. With that the user can retrieve information whether two persons are friends on those sites. Also a number of Google results including their names is provided. This leads to conclusion that different functionalities enable the user to get better overview of student work. With discovering plagiates the user can then determine why plagiarism has occurred in the first place and it can help him prevent this from happening in future courses.

    Item Type: Thesis (EngD thesis)
    Keywords: plagiarism, visualisation, Moss, Twitter, Facebook, Google
    Number of Pages: 87
    Language of Content: Slovenian
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Dejan Lavbič302Mentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=9986132)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 2083
    Date Deposited: 02 Jul 2013 12:59
    Last Modified: 22 Jul 2013 12:51
    URI: http://eprints.fri.uni-lj.si/id/eprint/2083

    Actions (login required)

    View Item