QuestionBankToolkit

QuestionBankToolkit turns readable YAML question banks into QTI 1.2 packages that can be imported into Canvas. It can validate authored YAML, inspect generated QTI packages, and recover supported questions from QTI into YAML.

The current question model supports single-answer multiple-choice questions with plain text or authored HTML, grading points, feedback, assessment eligibility, and optional choice shuffling. You can use the command-line tool without understanding Python, XML, or the QTI specification.

Begin here

Follow the getting-started guide to install the package, create a complete question bank, validate it, build the Canvas archive, and review the generated files. Use the YAML schema when you need the exact field and validation rules.

python -m pip install QuestionBankToolkit
coursebanks validate questions.yaml
coursebanks build questions.yaml --out build

User guide

• Getting started
  • 1. Install Python
  • 2. Install QuestionBankToolkit
  • 3. Create a YAML bank
  • 4. Validate before building
  • 5. Build the Canvas package
  • 6. Import and review in Canvas
  • Optional workflows
• Question-bank YAML schema (v1)
  • Validation rules
  • Sample item
  • Migrating existing banks
• Command reference and troubleshooting
  • Exit status and output
  • Primary conversion commands
  • Rotation commands
  • Troubleshooting
• Importing the generated package into Canvas
  • Classic Quizzes and question banks
  • A new New Quiz
  • A New Quizzes item bank
  • Post-import review
• Importing QTI into YAML
  • Archive safety limits
  • Compatibility table
  • Metadata CSV overrides
  • Supported item structure
• QTI 1.2 export and import contract
  • 1. Purpose and scope
  • 2. Normative standards and interoperability references
  • 3. Supported feature matrix
  • 4. ZIP package layout
  • 5. Question representation
  • 6. Choice shuffling
  • 7. Import and round-trip boundaries
  • 8. Validation levels
  • 9. Development and release checklist
  • 10. Deliberate exclusions and possible future work
  • 11. Relevant code

Contributors

• Development and typed data
  • Setup and checks
  • Documentation site
  • Distribution checks
  • Release tooling
  • Continuous integration
  • Untrusted and validated banks
  • Shared types
  • External archive and XML parsing
• Python API
  • Question banks and reports
  • YAML validation and QTI export
  • QTI import
  • Assessment eligibility and rotation
• Preparing a release
  • Record changes during development
  • Prepare the release candidate
  • Commit and tag after review
  • Publish the documentation site
  • Publish to PyPI