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Record W4318819450 · doi:10.1177/1476718x221149376

Teacher perspectives and approaches toward promoting inclusion in play-based learning for children with developmental disabilities

2023· article· en· W4318819450 on OpenAlexaffabout
Erica Danniels, Angela Pyle

Bibliographic record

VenueJournal of Early Childhood Research · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsInclusion (mineral)PsychologyCurriculumPedagogyDevelopmental psychologyEarly childhood educationFocus groupSocial isolationQualitative researchSpecial educationSocial psychologySociology

Abstract

fetched live from OpenAlex

As school authorities strive toward inclusive models of education for children with neurodevelopmental delay and disability (NDD), many kindergarten curricula have mandated pedagogy centered on learning through play. Children with NDD tend to experience greater social isolation and lower rates of social play engagement compared to typically developing peers. Consequently, issues related to social participation and inclusion may be particularly salient in play-based kindergarten classrooms. The current qualitative study explored how eight kindergarten teachers in Ontario, Canada conceptualized and promoted inclusion in play for children with NDD. Classroom observation and teacher interviews were conducted with a focus on the teacher’s role in play. Teachers endorsed the use of several indirect (i.e., environmental) strategies to promote social participation, alongside proactive teacher support in play. Teachers who shared multiple aspects of an interventionist viewpoint toward disability, and identified the social benefits of inclusion in play for children with NDD, tended to provide more proactive support to all children in play. Teachers also provided reactive support in play to address emerging social conflict. Implications for fostering the meaningful inclusion of children with NDD in play-based learning are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.674

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.124
GPT teacher head0.379
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2023
Admission routes2
Has abstractyes

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