Preparing Teachers for Assessment within Diverse Classrooms: An Analysis of Teacher Candidates' Conceptualizations.
Notice bibliographique
Résumé
Under the current standards-based framework of public education in the US, and in other parts of the world, teachers are required to purposefully use assessments to individualize instruction for students with diverse learning needs (Darling-Hammond & Bransford, 2005; Ryan & Feller, 2009). This standards-based framework was initiated through the No Child Left Behind legislation (NCLB, 2002) and more recently reinscribed through the Blueprint for Reform act (USDOE, 2010). Underlying these public policies is the belief that every student can achieve state educational standards when provided with sufficient instructional support and, if necessary, provisions for accommodation. Teachers are currently expected to use data from student assessments, both classroom-based and large-scale, to inform instruction for diverse students. Across these policy directives, diversity is primarily understood as differences in student ability (i.e., disability or giftedness), culture and race, and English language proficiency as well as considerations of other student characteristics including learning styles, gender, socio-economic status, sexual orientation, religious affiliation, body image, and interests. For many school districts, data-informed instruction has been enacted, in part, through a Response to Intervention (RTI) approach that emphasizes tracking of learner progress in relation to tiered interventions of instructional supports and learning environments for students working below grade level standards (Barnes & Wade-Woolley, 2007; Batsche et al., 2007). Inclusive, standards-based mandates and RTI is also a prevalent component of other educational systems including those in UK, Canada, Australia, and New Zealand (Armstrong & Cheryl, 2011; Hutchinson, 2009; Miles & Singal, 2010). Underpinning teacher effectiveness within a standards-based framework and, more specifically within a RTI approach, is teachers' ability to integrate knowledge of both educational assessment and student diversity as related to cognitive development, learning abilities, and students' social and behavioral backgrounds. Not only are teachers expected to assess student learning to satisfy accountability concerns, but they are also expected to engage in both summative and formative assessment practices to gather ongoing information about learner progress in relation to students' individual learning profiles. Accordingly, effective preparation of teachers for an inclusive, standards-based context of education must not only prepare teacher candidates with competence in the areas of student assessment and student diversity, but more importantly, in the intersection of these two aspects of teaching. However, to date, the majority of research on pre-service and early-career teachers has addressed these competencies in isolation (Cochran-Smith, Davis, & Fries, 2003; Crocker & Dibbon, 2008; Hollins & Guzman, 2005). This bifurcation in research is not surprising as teacher candidates typically learn about topics in assessment and student diversity within separate pre-service courses, that is, under a discrete course delivery model (Crocker & Dibbon, 2008; DeLuca, 2012a, 2012b; DeLuca & Klinger, 2010). Aside from their teaching placements, which are highly variable learning contexts (Darling-Hammond, 2006), there are few opportunities for teacher candidates to consolidate knowledge from these two areas, both theoretically and practically, making it difficult for teacher candidates to integrate these competencies in their teaching practice. As a basis for an integrated approach to preservice education, the purpose of this research was to begin to explore beginning teachers' conceptions on the linkages between student assessment and teaching within diversity classrooms upon completion of their preservice program. This research contributes to continued calls for enhancing the preparation of teachers in the areas of assessment and diversity (Ball & Tyson, 2011; Popham, 2004, 2011; Shepard, Hammerness, Darling-Hammond, & Rust, 2005; Zeichner & Conklin, 2008). …
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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».