Online exams with webcam monitoring allow candidates to take tests remotely while still ensuring fairness and security. By using a webcam or multiple cameras, the exam platform can verify the candidate’s identity, observe their environment, and detect suspicious behavior throughout the test.
Conducting online exams with a camera provides many of the same measures as in-person proctoring, helping prevent cheating and maintaining exam integrity even when the assessment is taken from home.
An online exam with a webcam is a remote test where the candidate is monitored via their camera to verify their identity and surroundings throughout the exam. The camera provides visibility into the test environment, helping verify that the right person is taking the exam and that no unauthorized materials, devices, or assistance are present.
Online exams with camera work by using the candidate’s webcam to monitor their identity and behavior throughout the test. During the exam, the camera records or captures snapshots while AI or a human proctor checks for suspicious behavior such as leaving the frame, looking away repeatedly, or using another device.
Online exams can be monitored with either one camera or two cameras, depending on the security level required.
A single webcam (usually the built-in camera) captures the candidate’s face and upper body. This setup is simple and sufficient for basic monitoring, but has clear limitations. It cannot fully capture the desk area, the candidate’s hands, or what happens outside the immediate frame.
A two-camera system provides a much wider and more reliable view of the exam environment. Instead of connecting two webcams to the computer, which is technically difficult for candidates, most secure exam systems use the candidate’s mobile phone as the second camera.
Camera-based exam monitoring can capture the test environment in two main ways: continuous video or periodic photos (snapshots). Both methods serve different security needs.
Video continuously records the candidate’s webcam feed throughout the entire exam. It includes audio, allowing detection of talking, whispering, or background voices, and it captures every movement from start to finish. This provides strong evidence during post-exam review.
Because the recording is uninterrupted, video offers the highest security and the most complete context for proctoring.
Snapshot recording captures still images of the candidate at specific intervals, and the most important factor is the frequency of these captures. Depending on the exam’s security requirements, the system may take a photo every 10 seconds, every 50 seconds, or at shorter or longer intervals.
Higher frequency provides more visibility and reduces the chance of missing suspicious behavior, while lower frequency is lighter on system resources and storage.
Most systems also include automatic capture rules when unusual behavior is detected. For example, if the candidate moves out of the camera frame, leaves the seat, covers the webcam, or tries to block it, the system instantly takes an extra snapshot to document the suspicious event as proof.
Online exams can be monitored either in real time (live proctoring) or after the exam is completed (post-exam review).
With live proctoring, a human proctor watches the candidate’s webcam synchronously as the exam takes place. This allows immediate intervention if suspicious behavior occurs, such as someone entering the room, the candidate leaving the frame, or using unauthorized materials.
Post-exam review means that recordings, either video or snapshots, are examined after the exam ends. If the system uses video, reviewers can watch the full session and see everything that happened. If AI is used, reviewers can focus on the AI-detected moments.
If it uses snapshot-only monitoring, reviewers typically directly focus on the automatically detected events, such as moments where the candidate left the frame, looked away excessively, or triggered an alert.
AI-powered webcam proctoring strengthens online exam integrity by automatically detecting behaviors that may indicate cheating. AI analyzes the candidate’s webcam and microphone activity in real time.
The system monitors key signals such as:
AI generates flags and timestamps whenever unusual behavior is detected. If the organization uses post-exam review, proctors typically examine only the AI-flagged events, which significantly reduces review time and ensures consistency.
A camera helps prevent common online exam cheating methods by making the candidate’s environment visible. It can detect extra people in the room, hidden notes, and the use of phones or secondary devices through suspicious movements or glances. It also captures when a candidate leaves the frame or tries to block the camera. By providing this visibility, camera monitoring significantly reduces cheating opportunities and improves exam integrity.
Using a webcam during online tests is essential for ensuring fairness, preventing cheating, and verifying the identity of the person taking the test. A webcam provides real-time visibility into the exam environment, allowing the system or a human proctor to confirm that the candidate is alone and not using unauthorized materials.
Camera monitoring helps prevent common cheating attempts such as receiving help from someone in the room, using hidden notes, checking a secondary device, or leaving the seat during the exam. It also makes suspicious behavior easier to detect, especially when combined with AI analysis.
For organizations, using a camera improves trust and credibility. It helps maintain exam integrity across remote settings, supports compliance requirements, and ensures that all candidates are evaluated under the same conditions.
Combining camera monitoring with lockdown browser creates a stronger, dual-layer security system for online exams. Camera monitoring observes the candidate’s face, behavior, and surroundings, while lockdown browser restricts the device by blocking new tabs, preventing screen switching, and enforcing full-screen mode.
Together, they secure both the candidate’s environment and their computer, providing far more reliable exam integrity than using either method alone.
