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Record W4385693353 · doi:10.22533/at.ed.55832823070810

The preparation in the direction of learning in a multigrade group in students of the Bachelor of Primary Education

2023· article· en· W4385693353 on OpenAlexaff
Juan Rojas Leguén, Ceila Matos Columbié, Zulema de la Caridad Matos Columbié

Bibliographic record

VenueInternational Journal of Human Sciences Research · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicForeign Language Teaching Methods
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsBachelorPrimary (astronomy)Mathematics educationGroup (periodic table)PsychologyPedagogyChemistryGeographyPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The objective of the article is to provide a content system structured in a program that modifies the study plan incorporating the subject "Work in multigrades", which is located in the Own Curriculum of the 3rd year of the Bachelor of Primary Education career, its methodological orientations, as well as actions to be developed in the groups of years, disciplines and subjects for the preparation of teachers.Definitions and principles are systematized, extracted from research by other Cuban authors, themes are grouped according to the characteristics of the teaching practice, which are: multigrade group or unitary school, work variants in a multigrade group, methodological preparation for multigrade, the plan of single class, the control and evaluation of learning in a multigrade group and the direction of learning in a multigrade group is defined.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.163
GPT teacher head0.584
Teacher spread0.421 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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