MétaCan
Menu
Retour à la cohorte
Enregistrement W146577395

How Do Other Countries Evaluate Teachers? Countries Known to Outpace the U.S. in Student Achievement Use a Variety of Educational and Organizational Methods, but Rarely Use the Approaches to Education Reform That We Are Promoting

2012· article· en· W146577395 sur OpenAlexaboutno aff
James H. Williams, Laura Engel

Notice bibliographique

RevuePhi Delta Kappan · 2012
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueTeacher Education and Leadership Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAccountabilityVariety (cybernetics)Academic achievementTest (biology)Standardized testMathematics educationScale (ratio)Achievement testTeacher educationEducational assessmentPedagogyPolitical sciencePsychologyPublic relationsComputer science
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Given the primary role of teachers in affecting student achievement, U.S. policy makers and reformers have increasingly focused on monitoring and evaluating teacher effectiveness by emphasizing the links to student learning outcomes. Large-scale international assessments are frequently used as base examples to justify reform. But, relatively little is known about what other countries actually do. We wonder: How do other countries evaluate teachers? We have set out on a broad research effort, looking at whether top-performing countries use educational practices and reform initiatives in vogue in the U.S. We've compared Finland, Korea, Japan, Ontario in Canada, and Singapore, exploring in each system the role of high-stakes testing, policies used to motivate schools and teachers to improve student learning, and the organization of accountability for learning. We use Ontario because Canadian education policy is substantially decentralized to the provinces. In each area, we looked at the role of teachers and systems of teacher evaluation. Perhaps not surprisingly, we have learned: 1. Teacher evaluation is used for both accountability and instructional improvement in most school systems. However, teacher evaluation systems are organized differently depending on the model of accountability. 2. There is a growing trend to use student test results and metrics to inform accountability for schools, principals, and teachers, instructional improvement in classrooms and schools, and reform at the system level. 3. In particular, standardized testing of students, a primary and growing component of teacher evaluation in the U.S., is generally administered and used differently in other countries. How is teacher evaluation linked with accountability and instructional improvement? Looking across systems, we see four primary approaches to accountability: professional, organizational, market, and parental/community. Each approach has strong implications for teacher evaluation and its use in instructional improvement. Professional accountability results from practitioner identification with the profession and a corresponding internalized obligation to uphold, even advance, its standards. Professional accountability is enhanced by social recognition and prestige (Scribner, Cockrell, K., Cockrell, D., & Valentine, 1999). In a professional accountability mode, teacher evaluation is closely linked with professional norms and peer assessments. Finland's teacher evaluation system is based almost entirely on professional accountability, in which teachers are accountable to each other, the school, the children, and their parents. In the early 1990s, Finland abolished the school inspection system that was in place to evaluate teachers and provide external feedback. Now, teacher evaluation is more group-based, reflective, and participatory, with the aim of creating professional learning communities among teachers and administrators (Sahlberg, 2011). Evaluation is ultimately a consultative and formative process. Principals often use their own knowledge and experience as teachers to assist teachers and help them recognize areas of strengths and improve areas of weakness. Organizational accountability exists, but its primary purpose is to coordinate and lead the professional activities of teachers rather than command and control. Poor performance in relation to professional norms violates the trust that is said to characterize the system. Another example of professional accountability is Japan's practice of lesson study, in which teachers, new and seasoned, take turns presenting lessons that are practiced and critiqued in a group setting. This system, while certainly not the only mechanism of accountability in Japanese schools, reinforces teachers' accountability to each other according to norms of good teaching. Organizational accountability refers to the structures, norms, incentives, and sanctions of the formal institution. …

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,026
score de la tête « metaresearch » (Gemma)0,071
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Évaluation · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,974
Score d'incertitude au seuil0,432

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0260,071
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0050,010
Études des sciences et des technologies0,0060,005
Communication savante0,0150,012
Science ouverte0,0010,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,002

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 Opus0,294
Tête enseignante GPT0,409
Écart entre enseignants0,115 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeObservationnel
DomaineÉvaluation
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revuePhi Delta KappanMême sujetTeacher Education and Leadership StudiesTravaux en français237 207