Authors :
Kondreddi Lakshmi Narayana; Gonnuri Dinesh; Kola Karun Kumar; Puvvada Panduranga Adithya; Makinedi Hemanth Venkata Satya Sai; Velagala Chinni Manikanta Reddy
Volume/Issue :
Volume 10 - 2025, Issue 4 - April
Google Scholar :
https://tinyurl.com/5n8f4a6f
Scribd :
https://tinyurl.com/yx8atzbm
DOI :
https://doi.org/10.38124/ijisrt/25apr798
Google Scholar
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Abstract :
Online exams have become a crucial part of modern education and recruitment, offering convenience and
flexibility for both students and organizations. However, they face significant challenges such as cheating, impersonation,
and unauthorized access to resources, which undermine the integrity and fairness of the process [1][3]. These issues create
a need for reliable solutions to maintain the authenticity of online assessments. The Online Exam Proctoring system ensures
a secure and fair testing environment through real-time monitoring, detecting suspicious activities like tab-switching, sound
anomalies, and facial recognition-based alerts to prevent cheating [2][4][7]. With role-based access control (RBAC),
examiners can efficiently manage exams and sensitive data, while students take exams in a proctored interface [10]. By
automating monitoring and analysis, the system reduces human effort and errors [6][8], offering a reliable and transparent
solution for online assessments and ensuring the integrity of the process for educational institutions and organizations [1][4].
Keywords :
Online Exam, Proctoring, AI Proctoring, Exam Monitoring, Pie Charts, Bar Graphs, Statical Reports, Database.
References :
- Smith, J., & Brown, K. (2021). AI-Powered Proctoring: Transforming Online Examinations. Journal of Educational Technology Research, 15(3), 112-134.
- Gupta, R., & Sharma, P. (2020). Computer Vision for Exam Integrity: A Study on AI-Based Remote Proctoring. IEEE Transactions on Learning Technologies, 13(2), 98-115.
- Miller, D., & Jackson, L. (2019). The Role of Artificial Intelligence in Preventing Academic Misconduct. International Journal of AI in Education, 29(4), 287-305.
- Jones, B., & Carter, S. (2022). Enhancing Online Exam Security through AI and Computer Vision. Computers & Education, 180, 104432.
- Jurafsky, D., & Martin, J. H. (2021). Speech and Language Processing (3rd ed.). Pearson.
- OpenAI. (2023). AI in Proctoring: Ethical Considerations and Implementation Challenges. Research Report on AI & Ethics in Education.
- Choi, Y., & Lee, H. (2020). Deep Learning-Based Face and Object Detection for Academic Integrity in Online Assessments. IEEE Access, 8, 55832-55847.
- McKinsey & Company. (2022). AI in Education: Ensuring Fair and Secure Digital Assessments.
- Goldberg, Y. (2017). Neural Network Methods for Natural Language Processing. Synthesis Lectures on Human Language Technologies, 10(1), 1-309.
- Patel, R., & Kumar, S. (2023). Automated Proctoring Systems: A Review of AI-Driven Examination Security. Journal of Computer Science and Education Research, 21(1), 45-67.
- Wang, X., & Li, Z. (2021). Real-Time Face and Behavior Analysis in Online Exams Using Deep Learning. Journal of Intelligent Systems, 30(4), 567–582.
- Kumar, V., & Singh, M. (2022). A Survey on AI Techniques for Secure and Fair Online Testing Environments. ACM Computing Surveys, 55(6), Article 129.
- Hernandez, A., & Wallace, T. (2020). Privacy and Surveillance in AI-Based Proctoring Tools: A Policy Review. Educational Policy Review, 34(3), 211–230.
- Chen, R., & Zhou, X. (2023). Multi-modal Learning for Enhanced Online Exam Monitoring. Proceedings of the 31st International Conference on Artificial Intelligence in Education (AIED), 453–464.
- IBM Research. (2021). Responsible AI in Education: Challenges and Frameworks for Remote Monitoring. IBM Research White Paper.
Online exams have become a crucial part of modern education and recruitment, offering convenience and
flexibility for both students and organizations. However, they face significant challenges such as cheating, impersonation,
and unauthorized access to resources, which undermine the integrity and fairness of the process [1][3]. These issues create
a need for reliable solutions to maintain the authenticity of online assessments. The Online Exam Proctoring system ensures
a secure and fair testing environment through real-time monitoring, detecting suspicious activities like tab-switching, sound
anomalies, and facial recognition-based alerts to prevent cheating [2][4][7]. With role-based access control (RBAC),
examiners can efficiently manage exams and sensitive data, while students take exams in a proctored interface [10]. By
automating monitoring and analysis, the system reduces human effort and errors [6][8], offering a reliable and transparent
solution for online assessments and ensuring the integrity of the process for educational institutions and organizations [1][4].
Keywords :
Online Exam, Proctoring, AI Proctoring, Exam Monitoring, Pie Charts, Bar Graphs, Statical Reports, Database.