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Turnitin AI

We use state-of-the-art artificial intelligence to help students, educators, and institutions advance integrity and learning outcomes, at scale.

We believe in human-centered AI

Our guiding principles for AI

AI is only as good as the principles on which it is built.
Turnitin is steadfast in its commitment to responsible and transparent AI.

AI should help improve learning outcomes and promote and protect academic integrity.

AI should be designed to adhere to high standards of privacy and data ownership.

AI should be intentionally designed to mitigate the impact of unintended biases.

AI should be built with rigorous and peer-reviewed statistical and machine learning standards.

AI should be designed, developed, and tested by a wide and diverse range of learners and educators, not only engineers and AI scientists.

AI should be continuously improved to make it more accessible, fair, and beneficial to learners and educators.

How we use AI

AI is used across our suite of assessment and integrity products

Answer-grouping

AI-assistance helps make grading easier, more efficient, and more fair by allowing instructors to score and give feedback on groups of similar responses at once. Read more.

Handwriting recognition

Some assignments and exams include handwritten calculations, codes, diagrams, proofs, and more. Turnitin AI technology identifies and transcribes these responses to take the administrative work out of grading. Read more.

Authorship verification

Advanced forms of plagiarism are difficult to identify from contract cheating to word spinning and bot writing. Using AI to compare writing styles, Turnitin insights help indicate authorship. Authorship profiles use forensic linguistics and bot writing identification uses detectors built from models such as GPT-3.

Document analysis

With AI, written and hardcopies of exam templates can be converted into electronic tests, helping streamline assessment. We combine vision-based machine learning with PDF parsing techniques to perform document understanding tasks, which are used to create an electronic version of the exam.

Essay analysis

Whether an essay is in draft-mode or in review, Turnitin AI flags areas for improvement and guides students through feedback. Essay analysis is performed with a suite of deep learning models, from BERT-based language models to CNNs, with advanced NLP tooling and statistical modeling.

Why we use AI

Students, educators, and institutions rely on Turnitin AI

Learning

Gain course insights to inform instruction

Fairness

Ensure consistency across evaluations

Efficiency

Cut redundant work and grading time in half

Scalability

Reach more students while upholding course quality

Published research

Analysis of grading times of short answer questions
Michael Yen, Sergey Karayev, Eric Wang
Read more

Formative essay feedback using predictive scoring models
Bronwyn Woods, David Adamson, Shayne Miel, Elijah Mayfield
Read more

Beyond automated essay scoring: forecasting and improving outcomes in middle and high school writing
Elijah Mayfield, David Adamson, Bronwyn Woods, Shayne Miel, Stephanie Butler, Jill Crivelli
Read more

Full page handwriting recognition via image to sequence extraction
Sumeet S. Singh, Sergey Karayev
Read more

Turnitin AI in the news

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