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Enregistrement W2068558342 · doi:10.1126/science.333.6047.1221

Response—Education Research: Set a High Bar

2011· article· en· W2068558342 sur OpenAlex

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.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueScience · 2011
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueInnovative Teaching Methods
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésAttritionAttendanceContext (archaeology)Test (biology)Mathematics educationSet (abstract data type)Class (philosophy)PsychologyConfoundingComputer scienceMathematicsStatisticsMedicinePolitical scienceHistory

Résumé

récupéré en direct d'OpenAlex

Torgerson and Derting et al. 's concerns may be the result of the difference in publication styles between hard sciences and education research literature. Education publications are largely self-contained, whereas research papers in hard science journals present results in a condensed form, requiring readers to be familiar with the relevant literature to fully appreciate the paper. Torgerson and Derting et al. would like to apply experimental design expectations for research in K-12 classes to research in introductory science classes at large universities. However, these practices often are neither necessary nor useful in this context. It is well documented that the student characteristics in a large introductory university science course are remarkably consistent over time [e.g., ([ 1 ][1], [ 2 ][2])]. Barring a change in admissions standards, an introductory science course will have the same very limited and well-characterized slice of the population each year. The teacher content mastery is also uniformly high. The large class sizes further reduce the variability across sections. The number and influence of confounding variables is therefore low relative to the K-12 setting. This makes randomized control trials unnecessary in this setting, particularly if there are relevant pretreatment measures of student performance (as in Table 1). Torgerson raises the possibility of attrition bias. To clarify, the numbers did not reflect attrition, but rather a continuation of the attendance patterns displayed in the previous weeks. The number of students who took the test was consistent with data on previous attendance; in both sections students who took the test had higher overall attendance and higher average midterm scores than those who did not take the test. Both Letters raise concerns that we did not consider how the “teacher effect” might affect our results. References 1, 2, 5, and 10 in our Report show that the characteristics of teachers, other than the pedagogy they use, have little impact on the amount of learning in introductory physics courses. The pretreatment data on the two sections (Table 1) further supports this assertion. Derting et al. argue that well-designed studies must use “validated assessment tools.” Although there is value in using such instruments where possible, we strongly disagree with such a sweeping assertion. First, this would constrain science education research to an extremely small number of topics for which such instruments exist. Second, there is great value in research that demonstrates to faculty members that, by teaching differently, they can help their students perform better on the tests they already use. Finally, we are troubled by the lack of concern with ethical issues in the calls for this study to be replicated in other classrooms before the results can be accepted. This experiment involved real students in a real course. Given the results, we concluded that any student in the control group of such a replication experiment would suffer very real harm to their education. 1. [↵][3]1. E. F. Redish, 2. P. J. Cooney 1. C. Crouch, 2. J. Watkins, 3. A. P. Fagen, 4. E. Mazur , in Research-Based Reform of University Physics, Vol. 1, E. F. Redish, P. J. Cooney , Eds. (American Association of Physics Teachers, College Park, MD, 2007); [www.compadre.org/Repository/document/ServeFile.cfm?ID=4990&DocID=241][4]. 2. [↵][5]1. L. Ding, 2. N. W. Reay, 3. A. Lee, 4. L. Bao , Phys. Rev. ST Phys. Educ. Res. 4, 010112 (2008). [OpenUrl][6][CrossRef][7] [1]: #ref-1 [2]: #ref-2 [3]: #xref-ref-1-1 View reference 1 in text [4]: http://www.compadre.org/Repository/document/ServeFile.cfm?ID=4990&DocID=241 [5]: #xref-ref-2-1 View reference 2 in text [6]: {openurl}?query=rft.jtitle%253DPhys.%2BRev.%2BST%2BPhys.%2BEduc.%2BRes.%26rft.volume%253D4%26rft.spage%253D010112%26rft_id%253Dinfo%253Adoi%252F10.1103%252FPhysRevSTPER.4.010112%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [7]: /lookup/external-ref?access_num=10.1103/PhysRevSTPER.4.010112&link_type=DOI

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,056
score de la tête « metaresearch » (Gemma)0,013
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Études des sciences et des technologies
Catégories consensuellesMétarecherche, Études des sciences et des technologies
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,540
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0560,013
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,003
Études des sciences et des technologies0,0020,004
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,487
Tête enseignante GPT0,568
Écart entre enseignants0,082 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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