Bibliographic record
Abstract
This longitudinal quantitative study compared literacy achievement of students from second through sixth grade based on two organizational systems: graded (traditional) and nongraded (multiage) classrooms. The California Standards Test (CST) scaled and proficiency scores for English-Language Arts (ELA) were used as the study's independent variable to measure student performance. A matched control was utilized in which nongraded students were compared with graded students based on gender, ethnicity, and date of birth. Data analysis included independent samples t-test, analysis of variance (ANOVA), and effect size. Results showed that nongraded students had a significant advantage over their graded counterparts in literacy achievement (p=0.000). Effect size for the matched group increased with length of exposure in the nongraded program from Cohen's d=0.49 to d=0.99. It is difficult to determine if significant outcomes were the result of classroom structure or instructional strategies used in the nongraded setting. However, a unique quality of this study involves the rare conditions and matched control design that allowed for variables to be controlled, which have yet to be simultaneously accounted for in multiage studies to date. Based on the results, this study suggested that nongraded education, by responding to the developmental nature of children in the classroom, may offer a viable alternative to the graded system. In nations such as Australia, New Zealand, Netherlands, Finland, and Canada with the highest literacy rates in the world, nongraded classrooms are common educational practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".