EduGen-Dataset

The EduGen Curated Student Performance Dataset (v1.0) is a harmonized and feature-engineered dataset constructed to support research in adaptive assessment, learner profiling, and AI-driven educational analytics. The dataset was curated by integrating and preprocessing two publicly available Kaggle datasets: (1) Students Grading Dataset and (2) Student Performance and Clustering Dataset. The original datasets provide learner-level academic records, including quiz scores, attendance metrics, behavioral indicators, and performance attributes. To ensure consistency and suitability for adaptive modeling, the datasets were aligned in schema, normalized, and enriched with engineered features such as Consistency Index (quiz score variability), Top_9_Sum (best-score aggregation), normalized final scores, and categorical Performance_Class labels (High/Medium/Low). No original labels were modified; additional variables were derived solely for modeling and evaluation purposes. This curated dataset contains 1,053 learner records and is intended for reproducible research in adaptive learning systems, psychometric modeling, and retrieval-augmented assessment generation frameworks.