Knowledge Level

What knowledge level measures

Knowledge level is the assessment side of security awareness, showing how well people understand concepts such as phishing recognition, password hygiene, privacy handling, and mobile security. It does not measure whether someone merely completed a course; it measures whether the person can answer questions or recognise correct security practice after training.

That distinction matters because training programs often report activity, completion, or one-off behaviour changes without proving understanding. Knowledge level gives a clearer view of whether the message has been learned, retained, and can be applied in later decisions.

Why knowledge level is useful

Security leaders use knowledge-level measures to see whether awareness efforts are improving comprehension across a population, rather than producing only short-term campaign effects. That makes the metric useful for comparing teams, tracking learning over time, and identifying topics where users still misunderstand the policy or the threat.

It is especially helpful when organisations need evidence that people can recognise risky situations before they act on them. A good score on a phishing quiz, for example, suggests the user can identify suspicious cues even if they have not yet encountered a live attempt in the workplace.

How knowledge level differs from behaviour metrics

Behaviour metrics show what users did, such as whether they clicked, reported, or ignored a simulated phishing message. Knowledge level shows what they know, such as whether they can explain why a message is suspicious, choose a stronger password, or identify a safer way to handle data.

Those measures complement each other. Behaviour can improve because of a single campaign or a short-lived prompt, while knowledge may stay flat. Likewise, knowledge can improve before behaviour changes become visible at scale, so the two metrics should be read together rather than treated as substitutes.

Using knowledge level in a security programme

Knowledge level works best when it is tied to the exact risks an organisation wants users to understand. The assessment content should reflect the real working environment, including the policy decisions, communication channels, and devices people actually use, otherwise the score may look good without translating into safer conduct.

It is also more meaningful when tracked as a trend over time instead of as a single test result. Repeated measurement helps show whether awareness content is reinforcing the right concepts, whether certain groups need extra support, and whether training is keeping pace with changing threats and policy requirements.

Risk and Threat Considerations

Low knowledge levels can leave users unable to recognise phishing, weak password practice, unsafe data handling, or risky mobile behaviour, which creates an exposure even when formal training has been delivered. The main risk is false confidence: an organisation may believe awareness is effective because completion rates are high, while the underlying understanding remains weak.

Failure mechanism: If assessments are poorly designed, too generic, or disconnected from real user tasks, they can overstate understanding and hide where people would still make unsafe decisions under pressure.

Impact: That gap can increase the chance of credential theft, privacy mistakes, and policy violations, and it can reduce the organisation’s ability to prove that training is changing understanding in a regulated setting.

Practitioner Guidance

Why practitioners should care: Knowledge level is most useful when it is treated as a control signal, not a vanity metric. A good programme uses it to decide which topics need reinforcement, which audiences need targeted education, and whether awareness content is aligned with the threats people actually face.

Common misunderstanding: A high completion rate does not mean a high knowledge level. Completion shows attendance; knowledge level shows retained understanding, which is the more useful indicator when you need to demonstrate that users can recognise and respond to risky situations.

Practitioner takeaway: Use knowledge-level data alongside behaviour results so you can tell the difference between people who complied once and people who actually learned.

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