Bibliographic record
Abstract
Educational outcomes are mostly studied in the short term (i.e. during the same phase of schooling). This paper focuses on the longitudinal monitoring of the mathematical knowledge of the same generation of pupils. At the school level, this can be performed by teachers, and at the state level by relevant institutions or experts in the field. Monitoring the progress in pupils’ attainments is one way of determining and assuring the school’s quality educational work. At the state level, pupils in Slovenia take National Assessments of Knowledge which can be used to monitor progress within the same generation of pupils. The introduction explains the difference between internal and external assessment and presents studies that focus on comparing the attainments in both types of assessment. This study focuses on the same generation of pupils, monitoring their attainments in mathematics in the 6th and the 9th year of schooling. The aim was to determine whether there was a gap between internal and external assessment. The research into external assessment was based on the attainments on the National Assessment of Knowledge in Mathematics, while the research into internal assessment was based on the pupils’ final school grades in the same subject. It has been determined that more than half of the pupils would have the same final grade in the internal and external assessment; less than a fifth of the pupils would have received a lower grade in the external assessment, and just over a quarter would have received a higher grade in the external assessment, compared to the internal assessment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".