Adaptive GPA Aggregation Engine – Weighted Academic Performance Index
This analytical GPA computation module constructs a weighted performance index by pairing each course’s credit load with its grade intensity coefficient. It’s designed for fast semester diagnostics, cumulative trajectory tracking, and scholarship threshold monitoring.
Computation Model
- Map letter grade → numeric factor (institutional 4.0 reference set with extended A+ = 4.3 where applicable).
- Multiply factor × credit load for each course to derive weighted contribution.
- Aggregate contributions; divide by total attempted credits → normalized GPA output.
Reference Mapping (Sample Set)
| Letter | Value | Band |
|---|
| A+ | 4.3 | Exemplary |
| A | 4.0 | Superior |
| A- | 3.7 | Strong |
| B+ | 3.3 | High Proficiency |
| B | 3.0 | Proficient |
| B- | 2.7 | Developing+ |
| C+ | 2.3 | Developing |
| C | 2.0 | Baseline |
| C- | 1.7 | Marginal |
| D+ | 1.3 | Low Pass |
| D | 1.0 | Minimal |
| D- | 0.7 | Deficient |
| F | 0.0 | No Credit |
Scenario Illustration
- Course A (4cr, A+): 4 × 4.3 = 17.2
- Course B (2cr, B): 2 × 3.0 = 6.0
- Course C (3cr, A): 3 × 4.0 = 12.0
- Total credits = 9; Weighted sum = 35.2 → GPA ≈ 3.91
Optimization Guidance
- Prioritize recovery in high‑credit underperforming segments (largest marginal impact).
- Model hypothetical retake replacements before committing schedule changes.
- Track cumulative slope (ΔGPA per term) to validate scholarship or honors trajectory.