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Record W1954643222 · doi:10.33524/cjar.v14i3.100

INDIGENIZING TEACHER EDUCATION: AN ACTION RESEARCH PROJECT

2015· article· en· W1954643222 on OpenAlexaffvenueabout
Julian Kitchen, Margaret Raynor

Bibliographic record

VenueThe Canadian Journal of Action Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsBrock University
Fundersnot available
KeywordsIndigenousMainstreamAction researchCurriculumPedagogyTeacher educationIndigenous educationExperiential learningSociologyTraditional knowledgeCurriculum developmentPolitical science

Abstract

fetched live from OpenAlex

This action research report focuses on a new elective course entitled “Indigenizing Education: Education for/about Aboriginal Peoples” that was developed and taught by two teacher educators—one Euro-Canadian and the other Métis. The purpose of the course was to increase understanding of Indigenous peoples and of the impact of colonization on Aboriginal communities. The course had an experiential orientation: participation by an Aboriginal Elder, educators working in Aboriginal settings, and educators who incorporate Indigenous knowledge and pedagogy into mainstream classrooms. Action research was conducted to determine the degree to which the course achieved its purpose with a view to enhancing future iterations of this course and contributing to teacher educator knowledge about effective teacher education approaches to including Aboriginal content and ways of knowing in teacher education. In particular, the authors were interested in the degree to which teacher candidates were responsive to Indigenous elements in the curriculum and teaching. Given the Aboriginal focus of this research, the Medicine Wheel is employed as an Indigenous framework for presenting and analyzing the findings.

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)0.023
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.189
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.864
GPT teacher head0.646
Teacher spread0.217 · 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 designNot applicable
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

Citations25
Published2015
Admission routes3
Has abstractyes

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