Supplementary Materials for "Beyond grades: multi-target deep learning for early academic risk detection"

This repository contains the supplementary materials associated with the article:

“Beyond Grades: Multi-Target Deep Learning for Early Academic Risk Detection”

The materials support the transparency, reproducibility, interpretability, and pedagogical analysis of the leakage-free multi-output modeling framework reported in the manuscript.

Contents:

Supplementary Appendix A:
Systematic review coding matrix used to summarize the prevalence of variable categories across 55 empirical studies on academic-performance prediction in higher education. This appendix supports Figure 2 in the manuscript.

Supplementary Appendix A1:
Dataset variable dictionary, including formulas, units, source platforms, target/predictor roles, and leakage classification for the originally engineered variables and the final leakage-free predictor set.

Supplementary Appendix B:
Literature benchmark of reported models, prediction targets, and performance metrics from prior studies, used to contextualize the comparative analysis in the manuscript.

Supplementary Appendix C:
Extended SHAP interpretability visualizations, leakage-free behavioral clustering results, and per-cutoff SHAP summaries for early prediction analyses.

These materials complement the main manuscript and provide additional transparency for the reported findings, including the data-leakage audit, feature construction decisions, model interpretation, and supplementary analyses.