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Enregistrement W2505115249 · doi:10.1111/1471-3802.4_12347

4. EFFECTS OF THE THREE‐BLOCK MODEL OF UDL ON INCLUSIVE TEACHING

2016· article· en· W2505115249 sur OpenAlexaff
Jennifer Katz

Notice bibliographique

RevueJournal of Research in Special Educational Needs · 2016
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueEducational Assessment and Pedagogy
Établissements canadiensUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésPsychologyMathematics educationProfessional developmentScale (ratio)Inclusion (mineral)Intervention (counseling)Faculty developmentPedagogyMedical educationMedicineSocial psychology

Résumé

récupéré en direct d'OpenAlex

These two studies examined the effects of professional development (PD) in the Three-Block Model of Universal Design for Learning (TBM of UDL) (Katz, 2013) for in-service teachers of students from kindergarten to grade 12, on teachers’ practices, efficacy and concerns about inclusive teaching. Effective PD requires intensive training that is delivered by experienced teachers, supports collegial dialogue, connects theory and practice and facilitates implementation in classrooms (Yoon, Duncan, Lee, et al., 2007). Some research indicates teachers’ attitudes and efficacy are impacted by education (Desimone, 2009), while Guskey (2003) suggested that ‘flow through’ is important – teachers observe that their changed practice increases student achievement, and then ‘buy in’ to the training increases. Total sample in the two studies included 103 teachers. Training involved a 5-day programme: introduction to the model followed by collaborative time planning, observing and problem solving. Data were collected using scales of teacher self-efficacy and concerns (Sharma, Loreman and Forlin, 2012) and the TBM Teacher Self-Assessment scale (Katz, 2014). Open-ended questions included: ‘What would help you to further develop your Inclusive Instructional Practice?’; ‘Tell us about your experience with UDL’; ‘What were the outcomes for you, your students, colleagues and families?”; and ‘What were the challenges?’ There were no significant differences before and after the intervention in teachers’ total concern scores, F(2,21) = .398, P = .534, or in their efficacy scores, F(2,21) = .192, P = .666. There were significant differences in teachers’ perceptions of their use of inclusive instructional practices [F (1,5) = 5.726, P < .05, η = .342], which was corroborated by classroom observations and student outcomes (Katz, 2013, 2014). Qualitatively, in subsequent interviews teachers indicated that the model improved their practice and self-efficacy related to inclusive education, reduced their workload and improved job satisfaction (Katz, 2014). Teachers indicated that their practices of differentiation, groupings and inclusivity of students with significant disabilities changed. Treatment group teachers reported that students with significant disabilities ‘engage in the same academic tasks as their peers’, while Control group teachers reported that ‘students with significant disabilities are “modified” academically – i.e. have a separate academic programme from the rest of their class’. This is an important finding, as research has shown that teachers view inclusion of children with significant disabilities as especially challenging (Smith, 2000). Thus, while quantitative data suggested teachers' concerns had not yet changed, their practices had, and they reported greater efficacy in interviews. Although research with pre-service teachers has shown that education enhances self-efficacy for inclusive teaching (Loreman, Sharma and Forlin, 2013), in-service teachers appear to differ. Enhanced efficacy for inclusion was not developed with teachers’ initial education or implementation. In the case of these studies, the practice changes and elevated student achievement preceded changes to teachers’ beliefs in the forms of efficacy beliefs and concerns. This fits with Guskey's flow through concept (2003). Qualitative analysis appeared to confirm this, as responses included such comments as ‘UDL and all of the related concepts we explored have left me with confidence and direction as a teacher’, reflecting teachers’ increasing self-efficacy related to inclusive education. The author reports no conflict of interest.

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)0,006
score de la tête « metaresearch » (Gemma)0,017
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,037

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0060,017
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,000
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0110,001

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 Opus0,092
Tête enseignante GPT0,495
Écart entre enseignants0,403 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
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

Citations2
Publié2016
Routes d'admission1
Résumé présentoui

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