The Use of One-, Two-, and Three-Parameter and Nominal Item Response Scoring in Place of Number-Right Scoring in the Presence of Test-Wiseness
Bibliographic record
Abstract
Ability estimates yielded by the one- (1PL), two- (2PL), and three-parameter (3PL) models and the nominal response model (NRM) were compared with the number-right (NR) scoring model using items not susceptible to test-wiseness (NTW) and items susceptible to the ID1 test-wiseness strategy. These items were contained in grade 12 diploma examinations for social studies and chemistry. The results were compared for high-, middle-, and low-ability examinees. Differences were found between pairs of ability estimates obtained when 2PL, 3PL, and NRM scores were used in place of NR scores. The differences tended to be greater for chemistry than for social studies, and with the exception of high-ability students in social studies, for the subtest containing items with absurd options than for the subtest containing nonsusceptible test-wise items. It appears at least for the two subject areas considered in the present study, that the scoring models cannot be used interchangeably to obtain estimates of examinees’ abilities, particularly when a test contains test-wise susceptible items.
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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 | 0.122 | 0.324 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".