For educators
checkreal.ai for educators
AI text detectors are unreliable as standalone evidence. They are not unreliable as conversation starters. checkreal.ai supports educators by giving structured signals to discuss with a student — the patterns that look LLM-like in a submission — and explicit limits to keep the process honest.
The scenario
An essay submission feels off. The voice doesn't match earlier drafts, the structure is too uniform, the citations are vague. You want a second opinion, but you also know that AI-text detection is wrong often enough that it can't justify a failing grade.
Recommended workflow
1. Run the AI essay detector
Paste the essay. The output reports sentence-rhythm regularity, generic-transition density, and claim-specificity scores — the patterns the engine notices.
2. Compare against earlier student work
Run a known-authentic sample from the same student through the same tool. The contrast (or lack of it) is more informative than any one score.
3. Talk to the student
Use the signals as a starting point: 'this paragraph reads more uniformly than your earlier writing — can you walk me through how you wrote it?' The conversation, not the score, is the evidence.
4. Document, don't adjudicate
Detection score plus draft history plus conversation gives a defensible record. The score on its own does not.
Recommended reading
- Why AI detectors are not 100% accurateWhat every AI-detection tool can and cannot do, why false positives happen, and how to use detection responsibly.
- How AI image generation worksA non-technical explanation of how diffusion models like Stable Diffusion and Midjourney create images — and what that tells us about detection.
A note on limits
AI text detection has high false-positive rates on formal academic English. Never use the score as the sole basis for a grade or academic-integrity finding.