University learning with anti-plagiarism systems

Abstract

We have designed an anti-plagiarism software to detect plagiarism in students’ assignments, especially written assignments, homework, and research reports, which will hereinafter be collectively referred to as student work. We used our university network to gather student work to detect plagiarism. To collect data, we used a domain name system to store the student work data based on the respective location, time, and the subject on which each student was assigned work. Once the student work data were collected, they were sent to an extraction module to remove unwanted data. The remaining data were then fed to a similarity index module, which produced similarity values based on comparisons between the collected data and the student work. This module uses mathematical equations that are built using semantic and syntactic similarity reports. Furthermore, in this study, we recommended procedures that can be applied to avoid plagiarism using the programming approach. This approach can raise awareness of plagiarism among students and encourage them to generate innovative ideas instead of plagiarizing. To attract faculty members to use the software, promotional materials can be customized based on the actual control factors that directly affect their adoption of the software. For example, the campaign should provide information highlighting the ease of implementation of the software for senior faculty members.