Archive

Data sources that might contain useful input device data:

• Identifying potential cheaters by tracking their behaviors through mouse activities
• https://data.mendeley.com/datasets/r9zwb4tvg5/1
• https://zenodo.org/record/3479756
• https://data.mendeley.com/datasets/vznyfcx9xk/2
• https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/H4UQ2R
• https://www.impactcybertrust.org/dataset_view?idDataset=950
• continue google dataset search: key=mouse dynamics

Outline of models for input device data:

Fields in common: quiz_id, student_id, attempt_id, question_id, timestamp Models and their respective fields:

1. Blur: x-y coordinate
2. Focus: x-y coordinate
3. Copy: content
4. Paste: content, location pasted
5. Left-click
6. Right-click
7. Double-click

Archived To-Do List

• Heroku: connect to postgres by setting heroku.yml job's env to use secret postgres uri
• Cleaning/ refactoring
  • Update question and quiz endpoints to use the new Dependency functions
  • branch get-results-teacher > rapid-dev
    • pull main
    • test GET "/quizzes/": crud.quiz.get_multi_by_participant: answers pulled doesn't come from the latest attempt'
    • review and refactor crud methods for each model
  • review and merge rapid-dev
  • run https://pypi.org/project/black/ on main to clean the codebase
• add documentation to readme (either screenshot or convert interactive doc to html)
• gitignore logs
• Add initial-data option to get real-world quiz data from available APIs (and note to user that it requires internet connection)