Notice bibliographique
Résumé
Even those who agree with the idea of creating a monitoring system might still need to be convinced that what students have to say should be considered valuable input in the effort to improve schools, whether it pertains to raising academic performance or to safety, security, and behavior. Some argue that students are so disinterested in surveys that they answer randomly or give the first answer that comes to mind. Others are concerned that students respond deliberately in ways intended to harm staff members they do not like. Still others are not sure that students really understand the true meaning of the questions and, therefore, that their answers are not usable. Students, however, are often the best sources of providing detailed information on what is happening in schools and may even provide realistic suggestions on how adults can intervene. Looking at the ways students’ perceptions are already being used in schools can help policymakers and educators see how they can be part of improving school climate. This issue, for example, has been debated in recent years as some states and school districts have moved to include students’ opinions on their experiences in the classroom as one component of new teacher evaluation systems. For example, the Tripod survey,1 developed by Harvard University’s Ron Ferguson, asks students how much they agree with statements such as “My teacher explains diffcult things clearly” and “Our class stays busy and doesn’t waste time.” The Tripod was used as part of the Bill and Melinda Gates Foundation’s Measures of Effective Teaching project and is being used in districts across the United States, in Canada, and in China. In a 2013 report, Hanover Research reviewed the literature on using student perception surveys in teacher evaluation and professional development: “Given the consistent findings of the research reviewed for this report, it is reasonable to conclude that student perception surveys can provide accurate measures of teacher effectiveness,” they write. “When the proper instrument, or survey, is utilized, student feedback can be more accurate than alternative, more widely- used instruments at predicting achievement gains.
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.
Comment cette classification a été obtenuedéplier
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».