← Part of the Feedback Flows toolkit

Writing fingerprints

Authorship checker that compares work to each learner's style

Build a style profile from previous authentic samples, then compare a new submission. See how vocabulary, structure and habits align — evidence for authorship conversations. Built for UK schools, FE colleges and training providers that want authorship checker with human review, clear exports and evidence trails that fit existing quality processes.

  • Profile from previous work
  • Flags shifts in style
  • Side-by-side evidence
  • Batch class comparisons
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Writing fingerprint comparison between a new submission and past work
Similarity to the learner's own portfolio
Writing fingerprint analysis interface

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Free authorship checker

Compare one authentic student writing sample against a new submission across 6 stylometric dimensions without signing up — then use Writing Fingerprints to maintain multi-sample portfolios and run whole-class ZIP checks.

Free authorship checker →
Why it matters

Authorship is about consistency with the same learner

An authorship checker should measure stylistic consistency with a student's authentic portfolio — sentence variation, vocabulary, punctuation habits and structure — not copying from the open web. Writing fingerprints answer 'does this sound like them?' rather than 'did they copy the internet?'.

A low score is a prompt to investigate: evolving style, support from others, or work that may not be theirs. Use detailed explanations and pair with the AI detector when AI generation is also a concern. This is different from Similarity Scoring, which compares learners with each other inside your organisation.

Build portfolios from controlled classroom writing of a similar genre. Three solid authentic samples beat a single old homework. Batch ZIP mode helps on deadline day; interpret low scores with process evidence before any formal step.

Refresh portfolios after major genre shifts (for example creative to analytical). An authorship checker is only as fair as the baseline you compare against. Write a one-page local policy for authorship checker: which assessments qualify, who reviews drafts, how long files are retained, and how learners receive feedback. Clear policy keeps staff confident and makes procurement or inspection conversations easier.

Who uses it

Where authorship checker fits

Secondary schools

Compare controlled classroom samples with take-home coursework when authorship is uncertain. Review a sample of outputs together the first time you introduce authorship checker, then agree override norms.

Further education

Build baselines early so late submissions can be checked fairly. Review a sample of outputs together the first time you introduce authorship checker, then agree override norms.

Independent training providers

Support integrity discussions on written portfolio evidence. Review a sample of outputs together the first time you introduce authorship checker, then agree override norms.

Higher education

Give departments an authorship signal alongside AI detection for dissertations and essays. Review a sample of outputs together the first time you introduce authorship checker, then agree override norms.

Worked example

GCSE English — batch authorship check on coursework

The department has three authentic in-class samples per learner. On deadline day they run the authorship checker as a class ZIP. Two low scores prompt meetings; one is explained by a supported rewrite process, the other leads to a supervised redraft after combining with AI detector quotes. Afterwards they note scheme or template tweaks so the next run needs fewer overrides, and they file exports with the usual authorship checker moderation pack.
Compared

By hand vs with writing fingerprints

Aspect Manual With Feedback Flows
Baseline Remember how a student 'usually' writes when deadlines are tight and staffing is thin Portfolio of authentic samples on the profile with teacher review and an export trail before release
Scale Spot-check a few scripts by eye when deadlines are tight and staffing is thin Batch ZIP comparisons for a whole class with teacher review and an export trail before release
Question answered Often mixed with plagiarism hunches when deadlines are tight and staffing is thin Clear focus: similarity to their own style with teacher review and an export trail before release
Evidence Hard to show parents or panels when deadlines are tight and staffing is thin Scores and explanations you can discuss with teacher review and an export trail before release
How it works

Portfolio, compare, interpret

Build the portfolio

Add authentic samples of similar task types to the student profile. Check names and classes carefully so history lands on the right learner.

Submit new work

Run a comparison for one learner or batch a class ZIP. Check names and classes carefully so history lands on the right learner.

Read the score

See similarity to their own baseline and supporting detail. Check names and classes carefully so history lands on the right learner.

Decide next steps

Combine with process evidence and, if needed, AI detection. Check names and classes carefully so history lands on the right learner.

Capabilities

What writing fingerprints cover

Stylometric features

Linguistic habits beyond simple word overlap. Designed to sit beside your other Feedback Flows tools for authorship checker.

Portfolio baseline

Comparisons against the learner's own samples. Designed to sit beside your other Feedback Flows tools for authorship checker.

Batch mode

Class ZIP uploads for deadline-day authenticity checks. Designed to sit beside your other Feedback Flows tools for authorship checker.

History

Track similarity scores over time on the profile. Designed to sit beside your other Feedback Flows tools for authorship checker.

Explanations

Context to support professional judgement. Designed to sit beside your other Feedback Flows tools for authorship checker.

Not cross-learner copying

Use Similarity Scoring for organisation-only peer copying. Designed to sit beside your other Feedback Flows tools for authorship checker.

On screen

Evidence against their own writing

Results show how closely new work matches the learner you already know. Training Centre walkthroughs mirror the same authorship checker screens so new markers practise review before live work. Leaders can sample completed jobs monthly to confirm overrides stay proportionate and comments stay in the department voice.

  • Clear similarity to own baseline
  • Batch options for whole classes
  • Complements AI detection
Writing fingerprint comparison between a new submission and past work
Writing fingerprint analysis interface
Guides

Research and practice

Related tools

Continue exploring

AI writing detector A hybrid check with writer context for EAL and younger writers, highlighted passages you can quote exactly, and a place to record what you d…
Similarity Scoring Every marked rubric and automarking submission can enter your organisation's private similarity bank. See a similarity %, flag work at 50% o…
Learner profiles and progress reports Marking history, integrity summaries, writing fingerprints, calendar notes and AI progress reports live on a single profile — so the next co…
Students and classes Open the full page for this tool.
FAQ

Questions about authorship checker

Writing fingerprints compare a new submission with the learner's own authentic portfolio using stylometric signals. Most departments keep a short note on who may release authorship checker results and how parents are informed. Keep copies of key exports in your usual shared drive structure for sampling.

No. It compares a learner with their own earlier work. Use Similarity Scoring for copying between learners in your organisation. Export packs usually sit alongside your normal moderation or IQA evidence for authorship checker. Keep copies of key exports in your usual shared drive structure for sampling.

Several authentic samples of a similar writing type (for example analytical essays together). New staff can learn authorship checker via Training Centre lessons and the guides linked on this page.

Yes. Batch Style Comparison accepts a ZIP with one folder per student. Always leave a trained person in the loop before learners see authorship checker outcomes.

No. It flags divergence for a professional conversation. If you are unsure whether authorship checker fits, compare the related tools listed below and pick by assessment type.

When AI generation is a concern, combining both signals is stronger than either alone. Credit use and retention follow your Feedback Flows account settings when you run authorship checker.

Collusion/similarity compares learners with each other. Authorship checking compares a learner with themselves. Sample a handful of outputs in the first week so team norms for authorship checker stay consistent.

Yes. Evolving style is normal — interpret shifts with process evidence and teacher knowledge. Keep policy language plain: what authorship checker drafts, what humans decide, and what is stored.

On the learner profile alongside other integrity and marking history. Escalate only with evidence — quotes, pairs or reports — never with a score alone from authorship checker.
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Explore the tool with sample work, or start free with welcome credits on your own account.

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