How Can Canvas Detect Cheating

The use of online learning is increasing greatly in modern education, thanks in part to platforms such as Canvas. As more and more students utilize this platform, there are growing concerns about preserving academic honesty. This raises the question, “how does Canvas identify cheating?” In this article, we’ll examine some of the techniques employed by Canvas for this purpose.

Canvas Quiz Log Feature

One of the principal methods that Canvas uses to detect cheating during online exams is the Quiz Log feature. This tool provides professors with valuable insights into what activities students engage in while taking an exam.

function QuizLogFeature() {
    // Quiz log feature provides a timeline of student's actions during a test
    return 'Student activity insights';

It captures actions such as page navigation, new tabs opening, and even periods of inactivity. If a student navigates away from the test tab, the log will record this activity, which could indicate potential cheating.

Canvas Fingerprinting

Another method Canvas employs to ensure academic integrity is Canvas Fingerprinting. This technique involves creating a unique identifier for each student’s browser and device. It is mostly used for tracking and identification purposes.

function CanvasFingerprinting() {
    // Using browser data and device information to create a unique identifier
    return 'Unique student fingerprint';

This identifier can be used to detect unusual patterns during an exam. For instance, if two exams present identical fingerprints but come from different accounts, the system may flag this as potential cheating.

Proctoring Tools

Canvas also integrates with various proctoring tools that record students while they take exams. These tools can detect suspicious behavior like eye movements or the presence of other people in the room. While these tools are not directly part of Canvas, their integration provides a robust anti-cheating system.

Statistics and Analytics

Canvas also uses statistical data to detect potential cheating. By analyzing a student’s performance over time, it can flag sudden improvements or unusually high scores as potential indicators of academic dishonesty.


While these methods are highly effective, they have limitations. For instance, they may not entirely prevent cheating, especially if students find sophisticated ways to beat the system. This is why it’s crucial for educators to use a combination of these tools and traditional methods to ensure academic integrity.


In conclusion, Canvas utilizes various tools and techniques to detect cheating, including a quiz log feature, fingerprinting, proctoring tools, and statistical analysis. These mechanisms, while not foolproof, provide a strong foundation for maintaining academic integrity in the age of online learning.