This feature provides graders with anonymized historical performance data to support fair grade calibration across different student cohorts. By offering aggregated statistics of students’ academic history (e.g., grade distributions, performance in prerequisite courses), graders can better contextualize current exam performance and adjust grading curves appropriately. The system ensures student privacy by:
- Only showing aggregated statistics, never individual records
- Anonymizing all data before presentation
- Restricting access to authorized graders
- Limiting the granularity of available information
This approach helps address the challenge of varying cohort strength across semesters while maintaining strict data protection standards.
Prerequisites
- Statistics for data aggregation
- Anonymity for privacy protection
In use
Similar concepts are used in learning analytics systems.