Uphold Academic Integrity with Accurate, Evidence-Based Reports
Save grading hours while maintaining rigorous standards. Review seminar submissions, term papers, and final-year dissertations with transparent similarity and AI attribution analysis.
Built for Modern Tertiary Classroom Challenges
Address copy-pasting, unaccredited paraphrasing, and uncritical AI generation with balanced, defendable evidence.
Cross-Student Collusion
Scan multiple student assignments together. CiteRight automatically compares papers across the cohort to highlight identical sections, swapped synonyms, and shared datasets.
Defendable AI Evidence
Never accuse a student based on a single opaque percentage. CiteRight provides sentence-level perplexity metrics and structural variance scores to support academic review boards.
Automated Citation Audits
Quickly verify whether citations in Chapter 2 actually correspond to references at the back. Instantly identify phantom or unreferenced sources in student literature reviews.
Recommended 3-Tier Integrity Review Framework
How forward-thinking Nigerian departments use CiteRight reports constructively.
Clear for Defense
Expected similarity consisting of discipline-standard terminology, standard headings, and properly cited quotes. The manuscript proceeds directly to defense or grading.
Revision Required
Indicates patchy paraphrasing or missing quotation marks around secondary sources. The student is issued the PDF report and granted 7 days to synthesize literature before re-check.
Panel Review & Oral Interview
Signifies extensive verbatim replication or wholesale AI synthesis. The supervisor convenes an in-person meeting where the candidate explains their research methodology and draft notes.
Lecturer Frequently Asked Questions
Practical guidance for incorporating CiteRight into your departmental workflow.
Can CiteRight detect peer-to-peer collusion between students in the same course?
Yes. CiteRight can compare student submissions within the same assignment batch or institutional repository, catching instances where classmates share code, literature review sections, or data analysis without authorization.
How should lecturers interpret AI probability scores responsibly?
CiteRight emphasizes that AI writing detection is probabilistic rather than forensic proof. A high probability score indicates linguistic uniformity, low perplexity, and mechanical cadence characteristic of generative LLMs. It should serve as an investigative signal to prompt an oral discussion or request draft version histories, rather than an automatic punitive sanction.
Does CiteRight exclude bibliographies and quotations automatically?
Yes. Our extraction pipeline identifies properly formatted reference lists (Works Cited, References, Bibliography) and block quotations, allowing lecturers to filter them out of the overall similarity percentage to assess genuine original prose.
Can I annotate reports and share feedback directly with students?
Yes. Lecturers can generate annotated PDF reports with source highlights and shareable view-only audit links that allow students to see exact matching references and learn proper paraphrasing techniques.
Equip Your Department with CiteRight
Sign up today to begin reviewing student papers, or contact our team for department-wide shared billing.