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Desafíos en la práctica de co-docencia en educación intercultural para la enseñanza de la lengua y cultura mapuche en Chile

2024· article· es· W4396576176 on OpenAlexaff
Katerin Arias-Ortega, Carlo Prévil, Viviana Villarroel Cárdenas

Bibliographic record

VenueRevista Electrónica de Investigación Educativa · 2024
Typearticle
Languagees
FieldSocial Sciences
TopicCollaborative Teaching and Inclusion
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

El artículo discute los desafíos interpersonales y profesionales que emergen en las prácticas de co-docencia entre los profesionales encargados de enseñar la lengua y cultura mapuche en Chile. La metodología considera un enfoque cualitativo, mediante la aplicación de entrevistas semidirigidas a profesores y sabios mapuches que implementan la educación intercultural en la educación escolar monocultural. Los resultados dan cuenta de la necesidad de establecer lineamientos para el desarrollo profesional de ambos actores educativos, lo que permita abordar las problemáticas interpersonales y profesionales que inciden en las prácticas de co-docencia, para favorecer una educación en perspectiva intercultural. Concluimos que en la relación de co-docencia es urgente establecer un modelo de acompañamiento que favorezca sus prácticas profesionales en perspectiva intercultural. En esto, el reconocimiento y la colaboración mutua se constituyen como un marco orientador, para favorecer la enseñanza de la lengua y la cultura indígena en la educación escolar, fortaleciendo así la identidad sociocultural y territorial de los estudiantes. La contribución del artículo es aportar con pistas de acción para favorecer la implementación de la co-docencia en la educación intercultural, lo que posibilitará procesos de enseñanza y aprendizaje interculturales basados en una relación dialógica del saber mapuche y escolar de forma simétrica.

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)0.007
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.007
Scholarly communication0.0090.004
Open science0.0010.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.014
GPT teacher head0.375
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

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 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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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