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Record W4388295318 · doi:10.1177/17454999231212548

Cross-cultural research on early childhood teacher education curriculum design

2023· article· en· W4388295318 on OpenAlexaff
Yuan He, Ting Li, Azra Fanoos

Bibliographic record

VenueResearch in Comparative and International Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsCurriculumVariety (cybernetics)PedagogyCurriculum developmentTeacher educationProfessional developmentCurriculum mappingMathematics educationSociologyEarly childhood educationCurriculum theoryPsychology

Abstract

fetched live from OpenAlex

This study was an attempt to compare the distinctive features in current Early Childhood Teacher Education (ECTE) curricula conducted at two universities, one in China, and one in the US. Document reviews, interviews, and questionnaires shed light on the two different approaches to curriculum design. Two program directors and 25 participants, viewed as “cultural outsiders,” were recruited. Results showed that the US model could be viewed as “deep” learning while the Chinese model was seen as “broad” learning. The US ECTE curriculum focused on a robust connection between general education and professional courses, strong standards, content-centered professional courses, multiple cultures, and more credit for field experience. The ECTE curriculum at the Chinese university provided a wide variety of general education and professional courses, arts-related professional courses, national cultures, and more modalities for field experience. This study also examined the impact of culture and society on the ECTE curriculum design.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.612
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.402
GPT teacher head0.598
Teacher spread0.196 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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