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Record W3192501225

Intercultural competence in teacher preparation programs in the United States and Canada: A meta-synthesis study

2021· book· en· W3192501225 on OpenAlexaboutno aff
Sandra Silva-Enos

Bibliographic record

VenueDigital Commons - University of South Florida (University of South Florida) · 2021
Typebook
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsTeacher preparationCompetence (human resources)PedagogyMedical educationPolitical sciencePsychologyTeacher educationMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

With a growing linguistically and culturally diverse population among our student demographics, it has become a necessity for teachers to create culturally responsive and sustaining classroom environments that can value and leverage students funds of knowledge. Teacher preparation programs are tasked with helping pre-service teachers develop intercultural understanding and competence as a means to aid in preparing them for culturally responsive and sustaining teaching. This meta-synthesis systematic review explores how pre-service teachers enrolled in teacher preparation programs in the United States and Canada progressively develop their intercultural competence skills. The findings highlight a progression of seven stages, across eight studies, that pre-service teachers experience when interacting and working with those that are linguistically and culturally different from themselves. Although many of the pre-service teachers progressed through these stages in study abroad programs, others were able to follow similar progression stages in their local communities, thus pointing to the need of teacher education programs reevaluating a dependency on study abroad programs as mechanisms for intercultural competence development.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.057
GPT teacher head0.241
Teacher spread0.184 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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