How students conceptualize grade‐based acceleration in inclusive settings
Bibliographic record
Abstract
Abstract Despite extensive research supporting educational acceleration for students with high academic ability, some psychologists, counselors, and educators express concerns about accelerative interventions. Such concerns often hinge on uncertainty about social acceptance, even in inclusive education settings. Research on acceleration has consistently shown benefits for students with high ability; however, there is a lack of research about grade‐based acceleration in inclusive schools. This study engaged two groups of students in group concept mapping processes to examine how they conceptualized beliefs about grade‐based acceleration in inclusive schools. First, 26 students in inclusive classes generated beliefs about grade‐based acceleration. Then they, and a group of 14 students with high ability, structured the data by sorting and rating a synthesized list of the generated beliefs. We analyzed the sorted data using multidimensional scaling and hierarchical cluster analysis. The resultant cluster maps revealed some differences and some similarities in the ways that the two groups of students conceptualized beliefs about educational acceleration. Practical implications are discussed.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".