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Record W3136485385 · doi:10.1590/s1413-24782021260012

Situation of study (SoS) on health education implemented in a co-creation (CoC) process

2021· article· en· W3136485385 on OpenAlexfundno aff
Graça Simões de Carvalho, Eva Teresinha de Oliveira Boff, María Cristina Pansera de Araújo

Bibliographic record

VenueRevista Brasileira de Educação · 2021
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsnot available
FundersFundação para a Ciência e a TecnologiaUniversidade do MinhoInternational Council for Canadian Studies
KeywordsReflexivityProcess (computing)Subject (documents)Health educationMathematics educationMedical educationPsychologyPedagogyMedicineSociologyComputer sciencePublic healthNursing

Abstract

fetched live from OpenAlex

ABSTRACT Situation of study (SoS) has been reported as an excellent strategy to promote students’ significant learning. This work intended to demonstrate how a SoS on health education (“Knowing cancer: a way to life”) can be implemented within the co-creation (CoC) framework. The study was carried out in a middle school, with the participation of five groups: students (14-15 years old), teachers, future teachers, university teacher trainers and health professionals. The 10 activities were carried out in school and outdoors for five months, undergoing a process of self-reflexive cycle: “reflecting and planning”, “acting and observing”, and “analyzing and reflecting”. Transcripts of debates and of students’ and teachers’ texts were subject to content analysis. This study on a topic of health education demonstrated that the Situation of Study implemented in a co-creation process was very efficient for students to develop significant learning.

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)0.012
metaresearch head score (Gemma)0.021
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 score0.012
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0040.005
Scholarly communication0.0040.002
Open science0.0010.006
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.393
Teacher spread0.363 · 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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueRevista Brasileira de EducaçãoSame topicE-Learning and Knowledge ManagementFrench-language works237,207