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Record W4387343373 · doi:10.1080/13664530.2023.2260353

Changes in the practices in make-believe play situations of one kindergarten teacher participating in an activity-oriented professional development program

2023· article· en· W4387343373 on OpenAlexaff
Amélie Desmeules, Christine Hamel, Anabelle Viau‐Guay, Caroline Bouchard

Bibliographic record

VenueTeacher Development · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychologyAction (physics)Professional developmentMathematics educationAction researchFaculty developmentPedagogyMedical educationMedicine

Abstract

fetched live from OpenAlex

Make-believe play (MBP) provides kindergarteners with an authentic form of engagement that is particularly favourable to the development of oral and written language.As part of an action research study, an activity-oriented professional development (PD) program incorporating video was established to provide kindergarten teachers with guidance on their teaching practices in MBP situations.The findings show changes in the participant's PD trajectories.These findings provide direction as to how teachers who wish to implement more MBP practices in the classroom to promote language development in children can be supported within the framework of such a program.For instance, the results match those of previous research as regards whether a program that uses evidence such as videos would be more effective in leading a participant to effect changes in their PD.The results also indicate that PD programs cannot be exclusively collective or individual, but benefit from combining the two approaches.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.003
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.153
GPT teacher head0.427
Teacher spread0.274 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2023
Admission routes1
Has abstractyes

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