The causal effects of increased learning intensity on student achievement: Evidence from a natural experiment
Bibliographic record
Abstract
I exploit a unique educational policy - implemented in most German states between 2001 \nand 2007 - that reduced high school duration by one year while keeping its curriculum \nunaltered to investigate how the resulting increase in learning intensity affected student \nachievement. Using 2000-2009 PISA data and a difference-in-differences approach, I find \nrobust evidence that the reform significantly improved the reading, mathematics, and \nscience literacy skills acquired by academic-track high school students upon treatment. A \nmore direct estimate of the effects of the increased learning intensity - as measured by the \ncumulative weekly number of instructional hours delivered in high school grades - \ncorroborates the latter finding. Furthermore, there is some evidence that the effects of the \nreform differ by gender and grade retention. Finally, I find no evidence of a significant \naverage effect of the reform on high school grade retention, although I do find that the \nlatter increased significantly for boys and for students with a migration background.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".