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Record W7033746384

Repensando la Formación de los Formadores en Chile

2013· article· en· W7033746384 on OpenAlexaboutno aff

Bibliographic record

VenueDialnet (Universidad de la Rioja) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)Process (computing)Quality (philosophy)Strengths and weaknessesWork (physics)Value (mathematics)Training (meteorology)
DOInot available

Abstract

fetched live from OpenAlex

The INICIA Test is a National Diagnostic Evaluation for graduate students of the Teaching Career. One of its main objectives is to provide diagnostic information to High School Students about the quality of training of their graduates of the Pedagogy career. Besides of this, it provides information about their learning process during the pre-graduate studies and it identifies strengths and weaknesses of the teaching training process. This aims at providing orientation on the design of public politics that might improve the initial training process of Teachers in Chile. Furthermore, this test provides information that enhances the value of teachers within the professional and social contours. The INICIA Test will be mandatory and enabiling for teachers in Chile in the short run, as it has happened in South Korea, Germany and a province in Canada. The main question proposed in this article is whether the IES should introduce strict forms of evaluation of the theoretical and practical work of students of Pedagogy which would accurately certify their training formation and the standard learning levels desired. It specifically intends to determine whether the graduate students should be evaluated upon their knowledge of contents as well as their ability to teach the required curriculum.

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)0.003
metaresearch head score (Gemma)0.008
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.126

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.011
GPT teacher head0.337
Teacher spread0.326 · 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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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Same venueDialnet (Universidad de la Rioja)Same topicHigher Education Research StudiesFrench-language works237,207