Item Equivalence Verification according to Test Information Media of the Optician National Licensing Examination: Focused on the Smart Device Based and Paper Based Tests Including Multimedia Items
Bibliographic record
Abstract
This study conducts the validity of the pen-and-paper and smart-device-based tests on optician’s examination. The developed questions for each media were based on the national optician’s simulation test. The subjects of this study were 60 students enrolled in E University. The data analysis was performed to verify the equivalence of the two evaluation methods, specifically, through split-plot factorial design of the evaluation method as a partition variable. As a result of the statistical significance test for the difference in achievement for each type of test information medium, indicating that there was no difference in achievement according to the type of test information medium at the significance level of .05. Although the validity of the smart device-based test and the paper-and-pencil test was verified through this study. To develop and set multimedia items in the optician national licensing examination, it is necessary to establish guidelines for how to develop the items.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".