Use the Knowledge Checks Dashboard to go beyond pass/fail data and understand exactly which questions users are getting wrong.
Using Question-Level Data to Improve Content
Start here when: You want to go beyond pass/fail data and understand exactly which questions users are getting wrong — and use that insight to improve your content and Knowledge Checks.
User Question Performance Table
This table gives you the most granular view of Knowledge Check performance available. For each record you can see:
- User Name
- Knowledge Check
- Question Name
- Is Correct (True/False)
- User Answer (the literal answer the user selected or submitted)
This table is most powerful when you look across multiple users' responses to the same question to identify patterns that signal content quality issues. The User Answer column is especially useful for open-ended or multi-select questions — it lets you see exactly what users are getting wrong, not just that they got it wrong.
How to identify content improvement opportunities:
| Signal | What It Means | Action |
|---|---|---|
| The majority of users answered the same question incorrectly | The underlying content may not clearly explain this concept | Review and update the relevant Spek to make the answer more explicit — then monitor whether scores improve on future attempts |
| Multiple users submit the same incorrect User Answer | Users share a common misconception, or the question/answer options are ambiguous | Review the wrong answer users are converging on — it often reveals exactly where the confusion comes from |
| One question has a high failure rate but all others pass easily | The question itself may be ambiguous or misleading | Review the question wording and answer options — sometimes a poorly written question is the problem, not the content |
| Failure patterns differ significantly between teams | The content may be relevant to one team but unclear for another | Consider creating team-specific content or tailoring the Knowledge Check for different audiences |
Pro Tip: Filter the User Question Performance table by a specific Knowledge Check and look for questions where Is Correct = False appears most frequently across users. Check the User Answer column for those rows to see exactly which wrong answer users keep choosing — that's often your fastest path to a fix.
Best Practices
- Review question-level data after every major training rollout — patterns in wrong answers are your most direct signal that content needs updating, more than Pass/Fail results alone.
- When you update content based on question performance data, monitor subsequent attempts to confirm the change made a difference.
- Use question names that clearly reference the concept being tested so wrong answers map easily back to the relevant content, and share question performance insights — including the actual User Answer values — with your content Experts so they can take ownership of updates.