GOAL Master Dataset 2024-2025
Description
The GOAL Master Dataset (2024-2025) is a high-fidelity synthetic large-scale dataset designed to validate the technical and mathematical claims of the G.O.A.L. framework. It simulates a dynamic higher-education environment involving 250,000 learners over a two-year academic cycle. Core Data Characteristics Volume: 250,000+ rows and 13+ technical columns. Temporal Scope: Continuous timestamps ranging from January 2024 to December 2025, allowing for longitudinal analysis of student growth. The dataset is specifically structured to perform Ablation Studies (comparing traditional vs. GOAL-based grading) and Sensitivity Analysis (testing the stability of the Global Aggregator Formula against exam outliers). It provides the empirical evidence required to prove that the "Andragogical Clock" and "Multi-Track Routing" result in higher cognitive growth compared to uniform pedagogical models.
Files
Institutions
- Christ UniversityKarnataka, Bengaluru