Pısa 2006 Fen Başarı Testinin Madde Yanlılığının Kültür ve Dil Açısından İncelenmesi
Why this work is in the frame
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Bibliographic record
Abstract
In comparability investigations, the presence of differential item functioning (DIF) is considered to be an indication of possible bias. In this study, differential item functioning (DIF) analyses of Science items of PISA 2006 tests were carried out between different samplings in respect to language and culture.. Mantel Haenszel (MH), logistic regression(LR) and signed - unsigned area indexes methods were used for DIF \ndetection analyses. The research group of this study consists of the Australia sample comprising 1124 \nstudents, the Canada sample comprising 1744 students; the England sample comprising \n1008 students, the Turkey sample comprising 377 students; took the fifth booklets and the England sample comprising 1430 students, the Turkey sample comprising 380 students; took the first booklets. These countries were selected due to the differences in cultural relevance and linguistic are the possible main reasons for differential item functioning (DIF). In order to investigate the sources of DIF field specialist opinions were consulted. In the study, ın Canadien sampling, DIF was found in three items at B level and three items at negligible level according to the MH technique and in three item at negligible level according to LR technique, in five items according to each fo signed - unsigned area indexes methods. In Australia- England sampling DIF was found in one item at B level and C level, four items at negligible level according to the MH technique and in \nfour items at negligible level according to LR technique, in two items according to each \nfo signed - unsigned area indexes methods. In England- Turkey sampling for the first \nbooklet; ten items included DIF according to MH results; five of them were at A level, two of them were at B level and three of them were at C level according to the MH technique those of the items eight of them favored English form, where two of them \nfavored Turkish form. DIF was found in five items at negligible level and one item at B level according to LR technique, in six items according to each for signed-unsigned area indexes methods. In England-Turkey sampling for the fifth booklet; in two items at A \nlevel and in four items at B level and in five items at C level according to the MH technique and infour item at negligible level and two items at B level according to LR technique, in six items according to each fo signed-unsigned area indexes methods had \nDIF. It is observed that as the linguistic and cultural differences increased between countries, \nthe number of DIF items increased. The number of DIF items varied significantly according to the procedure used. The correlation coefficients for the same culturedifferent language between LR and MH were significant, Non‐signed area indexes and \nSigned area indexes were significant at α =0,01. The correlation coefficients for the different culture-same language between LR and MH were significant at α =0,05, For the different culture and language LR and MH were significant at α =0,01for the first \nbooklet and Non‐signed area indexes and Signed area indexes were significant at α=0,01for the fifth booklet. Generally; results of bias researchs indicated that the main possible reasons for DIF is due to differences in cultural relevance, linguistic differences and differences in curriculum.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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 it