GOAL Master Dataset 2024-2025
收藏NIAID Data Ecosystem2026-05-10 收录
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https://data.mendeley.com/datasets/ddmhjf6rd2
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资源简介：
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.
创建时间：
2026-03-28
