Summary of Examining Monitoring System: Detecting Abnormal Behavior in Online Examinations, by Dinh An Ngo et al.
Examining Monitoring System: Detecting Abnormal Behavior In Online Examinations
by Dinh An Ngo, Thanh Dat Nguyen, Thi Le Chi Dang, Huy Hoan Le, Ton Bao Ho, Vo Thanh Khang Nguyen, Truong Thanh Hung Nguyen
First submitted to arxiv on: 19 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed “Exam Monitoring System” detects abnormal behavior in online examinations to combat cheating. The system demonstrates high accuracy and speed in real-time scenarios, providing valuable information for proctors’ decision-making. By leveraging machine learning techniques and analyzing various features, the system identifies unusual student behavior, potentially mitigating the widespread issue of academic dishonesty in online exams. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The “Exam Monitoring System” is a tool that helps prevent cheating in online exams. It uses special computer programs to find suspicious behavior, like looking at notes during an exam or copying answers from someone else. The system is very good at catching cheaters and can make decisions quickly. This makes it easier for teachers to catch students who are trying to cheat. |
Keywords
» Artificial intelligence » Machine learning
