Item Consistency Index: An Item-Fit Index for Cognitive Diagnostic Assessment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An item-fit index is a measure of how accurately a set of item responses can be predicted using the test design model. In a diagnostic assessment where items are used to evaluate student mastery on a set of cognitive skills, this index helps determine the alignment between the item responses and skills that each item is designed to measure. In this study, we introduce the Item Consistency Index (ICI), a modification of an existing person-model fit index, for diagnostic assessments. The ICI can be used to evaluate item-model fit on assessments designed with a Q-matrix. Results from both a simulation and real data study are presented. In the simulation study, the ICI identified poor-fitting items under three manipulated conditions: sample size, test length, and proportion of poor-fitting items. In the real-data study, the ICI detected three poor-fitting items for an operational diagnostic assessment in Grade 3 mathematics. Practical implications and future research directions for the ICI are also discussed.
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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 | 0.008 | 0.544 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it