Prevalence of Gender DIF in Mixed Format High School Exit Examinations.
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
The primary purpose of this study was to identify potential sources of gender differential item bias (DIF) in a high school exit examination composed of both selected-response and constructed-response items in the content areas of English, social studies, mathematics, and biology. A secondary purpose was to determine the agreement between the polytomous differential item functioning (DIF) detection methods, the Generalized Mantel-Haenszel (GMH) approach and Poly-Simultaneous Item Bias (Poly-SIB), and their counterparts, the Mantel-Haenszel procedure (MH) and SIB. Data were from four different Alberta Education Diploma Examinations for June and January 1998. The numbers of students that completed each form ranged from 2,328 to 3,386. Results indicate that both GMH and Poly-SIB were comparable to their dichotomous counterparts, MH and SIB, although there were slight differences between MH and GMH. Results about gender DIF support some hypotheses and not others. Males did not outperform females on geometry and mathematical problem solving items. Although more than 50 mathematics items were analyzed, only 8 dichotomous items were flagged. None of the gridded response items were flagged for DIF, and references to stereotypical male or female activities were not identified as DIF items or did not consistently favor one group or the other. While the majority of the dichotomous items favored males, all of the polytomous items favored females. These findings suggest that there may be an item-by-format interaction where females perform better on constructed response items even in measures of quantitative ability. The paper discusses some areas for future research. (Contains 10 tables, 1 figure, and 34 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION /17 CENTER (ERIC) This document has been reproduced as received from the person or organization originating it. 0 Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. 1 PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,068 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle