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Plugins: Duplicate Questions

Дата публикации: 26-10-2026 19:10:06

von Marketplace Web Service.  Find exact, near-textual and semantic duplicate questions using local candidate reduction before any AI comparison.

Основное содержимое страницы с новостью.

Duplicate detection at scaleMoodle 4.5+

Duplicate Questions

Detect likely duplicate questions without sending every possible pair to AI and without deleting anything from the question bank automatically.

Supported scope

Latest visible question versions

Design focus

Avoid N x N AI comparisons

Built as a Moodle plugin first: permissions, native APIs and human review remain part of the workflow instead of being replaced by an external black box.

Practical results

Production-minded

✓

Cheap local indexes

Normalize text, hash content, compare answer signatures and use keywords plus MinHash/LSH to build candidate buckets.

✓

Bounded AI comparison

Only pairs that survive local filters reach semantic comparison, with per-question and per-scan limits.

✓

Human decision

Teachers can inspect pairs, mark them as not duplicate or ignore them; no question is deleted automatically.

Cache invalidation

Question lifecycle changes invalidate comparisons when source hashes change.

Persistent ignore

An explicitly ignored pair stays suppressed even if its questions later change.

No learner data

Student attempts, answers, grades and enrolment information are outside the AI payload.

What this plugin does

Duplicate Questions is designed for real question banks where brute-force pair comparison becomes expensive very quickly. Exact hashes and local similarity techniques narrow the search before AI is even considered.

Semantic results classify pairs as the same question, strongly overlapping, related but distinct or unrelated. Confidence, explanation and evidence are shown to the teacher, while Moodle capabilities and category scope remain authoritative.

Features you get

Exact duplicate clustering

Collapse obvious duplicate groups without generating every possible pair.

MinHash/LSH candidates

Find near-textual candidates efficiently in larger banks.

Bounded background processing

Use adhoc tasks to process candidate pairs in controlled batches.

Strict semantic classes

Accept only known classifications and confidence ranges.

Teacher dispositions

Mark a pair not duplicate or ignore it without mutating questions.

Safety valves

Configure bucket size, candidate limits, AI-pair limits and task batch size.

Contributors Awards

Privacy friendly

Automated testing support

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