Comparative Analysis of Transformed Continuous Assessment Scores across Southwest States Nigeria
Bibliographic record
Abstract
This study investigated the extent to which transformed continuous assessment scores are comparable across states in South West Nigeria. The study employed survey and cross-sectional design. The sample consisted of 2520 JSS III students selected from 36 secondary schools in 18 Local Government Areas based on multistage, stratified and random sampling techniques. Data were collected directly from the Ministries of Education, continuous assessment Units with a proforma titled Continuous Assessment Retrieval Format. The data collected were subjected to inferential statistics. ANOVA was used to test null hypothesis at 0.05 level of significance. There was a significant difference in transformed continuous assessment scores in selected school subjects when true score, predictive true score and derived true score were used across the sampled states. Based on the findings, it was recommended that secondary school teachers should be acquainted with the techniques of generating reliable and valid continuous assessment scores. Teachers should be trained the procedure to moderate (transform) continuous assessment scores in schools across the states.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".