Proposal: Student History and Data Management in PROMPT

[Mtze]

1. Student History for Instructors

Students may apply to multiple courses managed by PROMPT, potentially across different semesters. To support informed decisions during the application process, PROMPT should provide instructors with a comprehensive student history view. This view should include:

• A list of previous courses the student participated in.
• The latest course phase reached in each of those courses.
• Whether the student successfully completed the course or withdrew/failed.
• Visibility of parallel enrollments, if applicable.
• We need to think about which courses should be shown (e.g. do we show courses that the instructor was not part of? should we only show that they were part of but no details...)

This functionality would significantly enhance the transparency of a student’s academic engagement and support fair admission decisions for limited-capacity courses.

2. Instructor Notes on Students

Instructors should also be able to attach explicit notes to individual students. These notes might include:

• Recommendations for future course participation or project work.
• Documentation of incidents or concerns relevant to a student’s conduct or performance.

These notes should be:

• Private to instructors and admins, not visible to the student.
• Auditable and attributable to the author for accountability.
• Optionally time-stamped and categorized for structured reporting.

3. Student Data Portability and Deletion

From a data privacy and compliance perspective, PROMPT must support the following student rights:

• Data Export (Self-Service): Students should be able to export their personal data at any time through the user interface. The exported dataset must include only information that is legally and ethically safe to disclose (e.g., profile data, application history, submissions owned by the student).
• Data Deletion (Admin-Only): PROMPT administrators must have the ability to permanently delete all stored personal data for a student upon request, in compliance with data protection regulations (e.g., GDPR). To enable this:
  • The data model must tag which data is eligible for deletion/export
  • Grading-related information must be explicitly excluded from deletion to comply with legal retention requirements.
  • All deletion operations must be auditable, and protected against accidental erasure of critical records.

[rappm]

Related Issues

[rappm]

#495

[JGStyle]

#1015

[JGStyle]

#1019