Resampling methods achieve near-perfect utility (TSTR 0.997) but fail privacy (DCR ~0), while VAEs balance 83.3% utility with full privacy protection for synthetic educational data.
arXiv preprint arXiv:2408.14559 (2024)
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Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models
Resampling methods achieve near-perfect utility (TSTR 0.997) but fail privacy (DCR ~0), while VAEs balance 83.3% utility with full privacy protection for synthetic educational data.