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Record W4401931884 · doi:10.6115/her.2024.039

Effects of an Inclusive Childcare Capacity Building Program on In-service Teachers’ Teaching Efficacy and Attitudes towards Inclusion

2024· article· en· W4401931884 on OpenAlexaff
Minkyung Suh

Bibliographic record

VenueHuman Ecology Research · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicInclusion and Disability in Education and Sport
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsInclusion (mineral)Professional developmentPsychologyMedical educationControl (management)Capacity buildingService (business)PedagogyMedicinePolitical scienceComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

An inclusive childcare capacity building program was designed to enhance teacher efficacy and attitudes toward the inclusion of childcare teachers. A total of 36 teachers working in childcare facilities in Gyeonggi-do participated in this study. Nineteen teachers were assigned to the treatment condition and 17 teachers were assigned to the control condition. The program explicitly addressed 15 topics, including screening and diagnosis, early development, characteristics of disability, family support and related services, IEP, and online site observation. The program was primarily delivered by field professionals using adult learning techniques such as small group activities, reflective journal writings, and online consultation. Teachers in the treatment group outperformed teachers in the control group on three measures of teacher efficacy, teacher play efficacy, and attitudes toward inclusion. The results were statistically significant. The increase in teacher efficacy, play efficacy, and attitudes toward inclusion of teachers was attributed to the well-designed program, encompassing early development, disability characteristics, small group discussions, and online support. The results highlight the importance of providing and disseminating a capacity building program for in-service teachers.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.075
GPT teacher head0.501
Teacher spread0.426 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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