WISEflow ORIGINALITY
Safeguard academic integrity with AI powered semantic similarity detection, embedded in your marking workflow, ready for LMS integration.
- Administration, Oversight & Governance
- Assessor Workflow & Report Interpretation
- Source Coverage, Paraphrasing & Collusion
- Interoperability & Deployment
- Value, Evidence & Procurement Fit
FROM EVERYDAY CHALLENGES TO PRACTICAL SOLUTIONS
What you may be experiencing
- Governance pressure to prove fair, consistent misconduct handling, yet originality checks and policy evidence sit in separate systems, making oversight hard.
- Privacy and GDPR concerns around where data lives, how sources are shared, and whether staff can control inclusion/exclusion transparently.
- Limited tools to curate the institutional source pool (archives, URLs, ad‑hoc documents), so administrators struggle to keep checks relevant to local programmes.
How WISEflow Originality responds in practice
- Administrator‑level oversight with a dashboard to manage users and sources, upload ad‑hoc material, and audit activity, keeping control with the license team.
- Privacy‑by‑design with sharing groups and EU‑centric data handling (DPIA) that let institutions decide exactly what is scanned and shared, and with whom.
- Simple curation of sources: add institutional archives or specific web URLs; index them for screening and generate reports. All controlled in one place.
FROM EVERYDAY CHALLENGES TO PRACTICAL SOLUTIONS
What you may be experiencing
- Opaque percentage scores and long reports slow marking; assessors need clear match signals and contextual guidance, not just raw numbers.
- Constant context‑switching between platforms to view similarity undermines efficiency and increases error risk in high‑volume marking windows.
- False positives and noise (references, bibliographies, boilerplate) make it hard to judge significance confidently and fairly.
How WISEflow Originality responds in practice
- Embedded report overlay inside WISEflow’s marking tool, toggle on/off, navigate matches alongside the submission, no tab‑hopping required.
- Intuitive match categories (Exact, Strong, Potential) and quick guides that summarise sources, highlight sentence‑level evidence, and support faster, consistent judgement.
- Sensible exclusions and traceability: references/bibliographies can be excluded, with full IDs and metadata for auditing decisions.
FROM EVERYDAY CHALLENGES TO PRACTICAL SOLUTIONS
What you may be experiencing
- Traditional text‑matching misses common misconduct patterns such as paraphrasing or “translate‑and‑submit”, especially across languages.
- Student‑to‑student copying (within or across cohorts) is hard to detect if repositories don’t include prior submissions or cross‑institutional sharing.
- Reports can be biased when two papers submitted around the same time only flag one as “original” and the other as “copied”.
How WISEflow Originality responds in practice
- Semantic similarity powered by AI flags paraphrase and nuanced similarity, with cross‑language capability across 50+ languages.
- Rich source pools: institutional archives, open internet and sharing groups to surface student‑to‑student overlap across flows and institutions.
- Parallel analysis and dynamic two‑way checks designed to avoid “who‑submitted‑first” bias in same‑day submissions.
FROM EVERYDAY CHALLENGES TO PRACTICAL SOLUTIONS
What you may be experiencing
- Originality tools outside the assessment platform add setup friction and complicate authentication, user management and support.
- LMS/VLE workflows need originality checks without rebuilding institutional integrations or processes.
- Administrators want an onboarding path with clear roles, test environments and staged enablement across existing flows.
How WISEflow Originality responds in practice
- Works embedded in WISEflow or stand‑alone via public API and dashboards, SSO and role‑based access align with your existing identity strategy.
- API‑first and LTI‑friendly approach enables connectors to LMS/VLEs; institutions choose direct integration or a central ESB pattern.
- Proven onboarding plan with enablement steps, staging/tests and guidance on module activation across new and legacy marking tools.
FROM EVERYDAY CHALLENGES TO PRACTICAL SOLUTIONS
What you may be experiencing
- Market concentration and high licence costs make value hard to justify, especially when staff time is lost to context switching.
- Committees want current, local evidence (not historic claims) that functionality and price stand up in public tenders.
- Budget models vary across segments; buyers need transparent pricing and to understand total cost vs alternatives.
How WISEflow Originality responds in practice
- Integrated marking + in‑app reporting reduce overhead; a buyer’s guide articulates total cost and the criteria that matter beyond raw index size.
- Selected via competitive tenders on combined functionality and price - evidence you can cite.
- Transparent pricing models (frameworks and institutional tiers) to match segments, with clear per‑student and annual components.
“The focus was on functionality rather than the product’s age. What truly mattered was selecting a solution that could meet both the university’s immediate needs and its long‑term ambitions.
With WISEflow Originality, we secured a plagiarism detection tool that already delivers advanced similarity and paraphrasing detection, seamless integration, and clear, customisable reporting.”
DETECTS PARAPHRASING & MEANINGFUL SIMILARITY
WISEflow Originality detects paraphrasing and meaningful similarity across large, diverse sources and presents clear, navigable reports directly where assessors work. No context switching. No extra logins.
The similarity report appears as an overlay on the submission inside WISEflow, so staff stay in context and move faster.
The service is interoperable by design and can be used within WISEflow or embedded in leading LMS/VLE platforms through an API-first approach.
CASE: UNIVERSITY OF COPENHAGEN
University of Copenhagen selects WISEflow as its digital assessment platform and WISEflow Originality for plagiarism detection
HOW TO CHOOSE A PLAGIARISM DETECTION TOOL
Plagiarism detection is no longer a simple matter of matching strings of text. As universities grapple with the dual challenges of AI-generated content and ever-more sophisticated paraphrasing, the tools and policies we choose matter more than ever.
ORIGINALITY WHITE PAPERS
HISTRORIC TRENDS
Historic trends in academic misconduct, specifically, plagiarism
READ IT NOWUNDERSTANDING MISCONDUCT
Understanding the reasons behind the rise of academic misconduct.
READ IT NOWWHY PLAGIARISM
The reason why students turn to plagiarism.
READ IT NOW
WAYS TO PALAGIARISE
Ways in which students plagiarise.
READ IT NOW