A machine learning model using 105 predictors predicts next-year standardized math achievement with out-of-sample prediction R-squared of .70–.78¶
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q3 i? The best machine learning model predicted future achievement scores well, with prediction R-squared values of .70, .73, .78, and .77 for the Year 5→6 through Year 8→9 transitions. → Lavelle-Hill 2024
Evidence¶
Lavelle-Hill 2024¶
Lavelle-Hill, R., Frenzel, A. C., Goetz, T., Lichtenfeld, S., Marsh, H. W., Pekrun, R., Sakaki, M., Smith, G., & Murayama, K. (2024). How the Predictors of Math Achievement Change Over Time: A Longitudinal Machine Learning Approach. Journal of Educational Psychology, 116(8), 1383–1403. https://doi.org/10.1037/edu0000863
q3 · i? · associational · r3
Next-year prediction analysis of PALMA data: Elastic Net and Random Forest models trained on 80% of each data set with five-fold cross-validation and evaluated on a 20% hold-out test set. The best model's out-of-sample prediction R-squared ranged from .70 to .78 across the four transitions.
"We found that the best machine learning model could predict future achievement scores well, with the prediction R-squared values: Year 5 → 6 = .70 (mean absolute error [MAE]9 = 34.99), Year 6 → 7 = .73 (MAE = 34.44), Year 7 → 8 = .78 (MAE = 32.74), and Year 8 → 9 = .77 (MAE = 35.97)."
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Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
ml-model-predicts-next-year-math-achievement-r2-70-78 |
title |
A machine learning model using 105 predictors predicts next-year standardized math achievement with out-of-sample prediction R-squared of .70–.78 |
description |
A machine learning model using 105 predictors predicts next-year standardized math achievement with out-of-sample prediction R-squared of .70–.78 |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2024 |
generated |
by process:wiki-ingest on 2026-10-25 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — lavelle-hill-2024 |
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