Pangram is an AI detection and plagiarism detection tool that identifies potential AI-generated content and plagiarism in text. It analyzes text patterns to distinguish between human writing, fully AI-generated content, and human writing that has been edited or enhanced using AI tools. Pangram is not intended to be used on non-text documents like problem sets including math, chemical formulas, or on image, diagram, or graph-heavy work. For more about Pangram, see How does Pangram work?
The University has an enterprise license for Pangram and has secured the University’s data privacy and security. The data submitted to Pangram is not used to train their model, the data can be deleted on demand, and any student data submitted is FERPA-protected. For more details, review the Frequently Asked Questions.
There are two ways of using Pangram within Canvas. In both cases, SpeedGrader will display a report of the likelihood that the student's submission is AI-generated. However, the range of tools available to you in SpeedGrader will vary depending on the route you choose.
For a step-by-step explanation of each method, please click on the appropriate link.
To create a Pangram Assignment with annotation capabilities in SpeedGrader:
To create a Pangram Assignment without annotation capabilities in SpeedGrader:
If you have a document not submitted through Canvas, you can upload it directly at pangram.com. Supported formats: PDF, DOCX, RTF. For more information on how to use the pangram.com website, see Check for AI Use or Plagiarism with the Pangram Web Tool.
| Score | Interpretation |
|---|---|
| 0-20% | Likely human-written |
| 21-59% | Uncertain — review highlighted segments before drawing conclusions |
| 60-100% | High likelihood of AI-generated or AI-assisted content |
Important: Pangram scores are one data point, not a verdict. Before taking any action, review the flagged segments, consider the context (e.g., a non-native English speaker's writing may read differently), and speak with the student directly. Do not use a Pangram result alone as the basis for an academic integrity referral.
The CCTL provides guidance on Navigating Academic Integrity in the AI Landscape on their website, addressing issues such as assessment design and communicating expectations, in addition to Pangram.
Pangram supports detection in multiple languages. Please see their page What languages does Pangram work on? for details on which languages are currently supported. To learn about how they tested, review their language testing methodology on their blog.
| Resource | Link |
|---|---|
| UChicago IT Help Desk | uchicago.edu/ithelp |
| Canvas at UChicago | canvas.uchicago.edu |
| Academic Technology Solutions | academictech.uchicago.edu |
| Academic Integrity Office | college.uchicago.edu/student-services/academic-integrity-policies |
For technical support, integration issues, or training requests, please contact the Academic Technology Solutions (ATS) team or submit a ticket through academictech@uchicago.edu.