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Record W4378532416 · doi:10.1080/23752696.2023.2216190

Assessing the development of global competence in teacher education programmes: internal consistency and reliability of a set of rubrics

2023· article· en· W4378532416 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHigher Education Pedagogies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of WinnipegSt. Thomas University
FundersErasmus+European Commission
KeywordsRubricCompetence (human resources)Internal consistencyPsychologyConfirmatory factor analysisExploratory factor analysisMathematics educationComputer scienceSocial psychologyStructural equation modelingPsychometricsDevelopmental psychology

Abstract

fetched live from OpenAlex

Global competence is a complex concept as it is multifaceted, composite, multi-layered, multidimensional, and can be viewed from several perspectives. A previous study validated a set of rubrics designed to assess pre-service teachers’ development of global competence. The research presented in this paper tested the internal consistency and reliability of the set of rubrics in order to create an instrument validated within the international context that was robust and consistent from a methodological point of view. The set of rubrics was self-administered online by 729 pre-service teachers studying in 12 teacher education programmes across 10 different countries around the world. The data analysis showed a high level of reliability and internal consistency of the rubrics, indicating their ability to assess pre-service teachers’ global competence. The exploratory and confirmatory factor analysis suggested changes to two areas of the rubrics.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.097
GPT teacher head0.458
Teacher spread0.361 · 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