Development of an Item Bank of Order and Graph by Applying Multidimensional Item Response Theory
Bibliographic record
Abstract
This study aimed to develop an item bank of Order and Graph of Mattayomsuksa 1 level (grade 7). The samples were 4,800 lower secondary students from 34 schools in northeastern area of Thailand, academic year 2011 chosen through multi-stage random sampling. The research tool used in the study was a multiple choicetest of an Order and Graph lesson by applying multidimensional item response theory. Parameter were analyzed by confi rmatory factor analysis by applying multidimensional normalogive model with guessing of the program normalogive harmonic analysis robust method (NOHARM). Discrimination power and Easiness intercept were equated through non–orthogonal procrustes method. The study results indicated that there were 59 items out of 140 passed the test standard. Key words: Item bank; Cognitive process; Multidimensional item response theory (MIRT)
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".