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Record W2611977109 · doi:10.1002/rev3.3097

A scoping review of research on play‐based pedagogies in kindergarten education

2017· review· en· W2611977109 on OpenAlexaff
Angela Pyle, Christopher DeLuca, Erica Danniels

Bibliographic record

VenueReview of Education · 2017
Typereview
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsQueen's UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychologyValue (mathematics)CurriculumPedagogyMathematics education

Abstract

fetched live from OpenAlex

Across a number of countries, play‐based learning is the mandated pedagogy in early years’ curricula. However, a lack of consensus remains both in research and practice regarding the value and role of play in children's learning. This scoping review analyses 168 articles addressing play‐based learning for 4–5 year old children divided into three categories: research on play for developmental learning, research on play for academic learning and factors influencing play in kindergarten classrooms. Much of the research endorsed play as fulfilling an important role in early learning. However, two disparate perspectives concerning the role of play for developmental versus academic learning demonstrate different orientations towards the value and potential benefits of play. Research focused on developmental learning endorsed the use of free play and a passive teacher role, while research focused on academic learning endorsed teacher‐directed and mutually directed play where the teacher fulfills an active play role. A similar lack of consensus was found among research with educators regarding the role and benefits of play. These findings indicate a need to move away from a binary stance regarding play and towards an integration of perspectives and practices, with different types of play perceived as complementary rather than incompatible.

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)0.006
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.021
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0150.017
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.468
GPT teacher head0.633
Teacher spread0.165 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations183
Published2017
Admission routes1
Has abstractyes

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