Research Article

Integrating Plagiarism Detection into a Class Management System for Academic Integrity

by  Neda Lotfi, Suhair Amer, Ankita Maharjan
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Issue 66
Published: December 2025
Authors: Neda Lotfi, Suhair Amer, Ankita Maharjan
10.5120/ijca2025926107
PDF

Neda Lotfi, Suhair Amer, Ankita Maharjan . Integrating Plagiarism Detection into a Class Management System for Academic Integrity. International Journal of Computer Applications. 187, 66 (December 2025), 1-8. DOI=10.5120/ijca2025926107

                        @article{ 10.5120/ijca2025926107,
                        author  = { Neda Lotfi,Suhair Amer,Ankita Maharjan },
                        title   = { Integrating Plagiarism Detection into a Class Management System for Academic Integrity },
                        journal = { International Journal of Computer Applications },
                        year    = { 2025 },
                        volume  = { 187 },
                        number  = { 66 },
                        pages   = { 1-8 },
                        doi     = { 10.5120/ijca2025926107 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2025
                        %A Neda Lotfi
                        %A Suhair Amer
                        %A Ankita Maharjan
                        %T Integrating Plagiarism Detection into a Class Management System for Academic Integrity%T 
                        %J International Journal of Computer Applications
                        %V 187
                        %N 66
                        %P 1-8
                        %R 10.5120/ijca2025926107
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

This system is a comprehensive database designed to assist faculty members in efficiently managing academic information and monitoring student performance. It allows tracking and maintenance of key data, including class details, student records, activities, grades, and submitted documents. Faculty members can store and update information such as student names and addresses, class names, numbers, locations, times, and enrolled students. The system also supports management of classroom activities by recording activity names, numbers, maximum points, due dates, and instructions. A built-in grade book enables faculty to maintain and analyze student scores for each activity, while an integrated plagiarism detection feature compares newly uploaded files against previously submitted ones to ensure academic integrity. Additionally, the system provides tools for retrieving information, identifying missing assignments, and generating performance summaries such as highest, lowest, and average scores, thereby enhancing the overall efficiency of academic record management.

References
  • Sanchez, L., Penarreta, J., & Soria Poma, X. (2024). Learning management systems for higher education: A brief comparison. Discover Education, 3(1). https://doi.org/10.1007/s44217-024-00143-5
  • León, J. L., Quaresma, P., & Nogueira, V. (2024, October). Plagiarism detection: Report. University of Évora.
  • LMS Review Committee. (2022, January 11). LMS Review Report and Recommendations. University at Buffalo. https://www.buffalo.edu/content/dam/www/lms/project-overview/LMS_Review_Report_and_Recommendations_011122.pdf
  • Ahmad Ayobami Abdulquadir, Opeyemi Abdulsalam, Russell Mcmahon, and Annu Prabhakar. 2023. Usability Study of a Learning Management System (LMS). In Proceedings of the 24th Annual Conference on Information Technology Education (SIGITE '23). Association for Computing Machinery, New York, NY, USA, 150–156. https://doi.org/10.1145/3585059.3611415
  • Gi-Zen Liu, Hsiang-Yee Lo, Hei-Chia Wang. Design and usability testing of a learning and plagiarism avoidance tutorial system for paraphrasing and citing in English: A case study, Computers & Education, Volume 69, 2013, Pages 1-14, ISSN 0360-1315, https://doi.org/10.1016/j.compedu.2013.06.011.
  • A. K. S. Sabonchi and A. K. Görür, "Plagiarism detection in learning management system," 2017 8th International Conference on Information Technology (ICIT), Amman, Jordan, 2017, pp. 495-500, doi: 10.1109/ICITECH.2017.8080048.
  • Dewi Tresnawati, Arief Syaichu R, Kuspriyanto. Plagiarism Detection System Design for Programming Assignment in Virtual Classroom based on Moodle, Procedia - Social and Behavioral Sciences, Volume 67, 2012, Pages 114-122, ISSN 1877-0428, https://doi.org/10.1016/j.sbspro.2012.11.312.
  • Volaric, Tomislav & Martinovic, Goran & Ljubić, Hrvoje. (2023). Detecting Academic Fraud at Online Tests During COVID-19 Using Machine Learning-Based Methods. 10.1007/978-3-031-36833-2_11.
  • Scott Crossley, Yu Tian, Joon Suh Choi, Langdon Holmes, & Wesley Morris. (2024). Plagiarism Detection Using Keystroke Logs. Proceedings of the 17th International Conference on Educational Data Mining, 476--483. https://doi.org/10.5281/zenodo.12729864
  • Khalil, M., Er, E. (2023). Will ChatGPT Get You Caught? Rethinking of Plagiarism Detection. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14040. Springer, Cham. https://doi.org/10.1007/978-3-031-34411-4_32
  • Vandenhoek, T. (2023, December 31). Assessing the Accuracy of Plagiarism Detection Systems. International Journal of Education and Development using ICT [Online], 19(3). Available: http://ijedict.dec.uwi.edu/viewarticle.php?id=3209.
  • Hirsch, A. (2024, December 12). AI detectors: An ethical minefield. Center for Innovative Teaching and Learning. https://citl.news.niu.edu/2024/12/12/ai-detectors-an-ethical-minefield/citl.news.niu.edu
  • Abdelhamid, M., Azouaou, F., & Batata, S. (2022). A survey of plagiarism detection systems: Case of use with English, French and Arabic languages. arXiv preprint arXiv:2203.00871. https://arxiv.org/abs/2203.00871
  • Belani, A. J., Bahri, A. R. D., Izhar, A., Shadman, B., Mukhtiyar, F., Das, P., & Amin, N. U. (2025). Design and implementation of an enhanced learning management system: Addressing modern academic challenges. Preprints. https://doi.org/10.20944/preprints202505.1522.v1
  • Sameer Qazi, Muhammad Bilal Kadri, Muhammad Naveed, Bilal A. Khawaja, Sohaib Zia Khan, Muhammad Mansoor Alam, Mazliham Mohd Su’ud. AI-driven learning management systems: Modern developments, challenges, and future trends during the age of ChatGPT. Computers, Materials and Continua, Volume 80, Issue 2, 2024, Pages 3289-3314, ISSN 1546-2218,https://doi.org/10.3991/ijet.v19i6.40217
  • Fidas CA, Belk M, Constantinides A, Portugal D, Martins P, Pietron AM, Pitsillides A, Avouris N. Ensuring Academic Integrity and Trust in Online Learning Environments: A Longitudinal Study of an AI-Centered Proctoring System in Tertiary Educational Institutions. Education Sciences. 2023; 13(6):566. https://doi.org/10.3390/educsci13060566
Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Database system student management class information grade book plagiarism detection academic records faculty tools performance tracking information retrieval automation

Powered by PhDFocusTM