Deciding Whether to Respond: A Latent Class Analysis of Nonresponse on Ontario’s Grade 9 Assessment of Mathematics
Bibliographic record
Abstract
This study investigates nonresponse on Ontario’s Grade 9 Assessment of Mathematics – in particular, whether or not students responded to all multiple-choice or all open-response items in two test booklets. Whether students responded to all items of one type (multiple-choice or open-response) by booklet (for the first or second day of testing) was modeled, with and without proportion correct scores by item type as covariates, using latent class analysis. Both a 3-class model without the covariates and a 4-class model with the covariates but without direct effects distinguished among students who responded to all items, students who left both multiple-choice and open-response items blank, and students who left only open-response items blank. The results suggest that deciding to respond to all open-response items is distinct from deciding to respond to all multiple-choice items. Attitudes toward mathematics were also more related to the decision to respond to all open-response items than to the decision to respond to all multiple-choice items. Cette étude porte sur l’absence de réponse au test de mathématiques pour la 9e année en Ontario –nous cherchions notamment à savoir si les élèves avaient répondu à toutes les questions à choix multiples ou bien à toutes les questions ouvertes dans deux livrets d’examen. Une analyse de structure latente a permis la modélisation du comportement des élèves, à savoir s’ils avaient répondu à tous les items d’un type (questions à choix multiples ou questions ouvertes) dans un livret (lors du premier ou deuxième jour des tests) avec et sans des scores reflétant la proportion de bonnes réponses par type d’items comme covariables. Un modèle de classe 3 sans les covariables ainsi qu’un modèle de classe 4 avec les covariables mais sans effets directs ont tous les deux fait la distinction entre les élèves qui avaient répondu à tous le items, les élèves qui n’avaient ni répondu à certaines questions à choix multiples ni à certaines questions ouvertes et les élèves qui n’avaient pas répondu à certaines questions seulement dans le cas des questions ouvertes. Les attitudes face aux mathématiques ont également joué un plus grand rôle dans la décision de répondre à toutes les questions ouvertes que dans celle de répondre à toutes les questions à choix multiples.
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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 | 0.016 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".