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Record W3163450512 · doi:10.1344/ridas2021.11.1

Aprendizaje-servicio y formación inicial docente. Factores que determinan el desarrollo de habilidades transversales

2021· article· es· W3163450512 on OpenAlexaff
Maria Isabel Marques, Luis Alberto Cáceres

Bibliographic record

VenueRIDAS Revista Iberoamericana de Aprendizaje y Servicio · 2021
Typearticle
Languagees
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsPsychologyService-learningContext (archaeology)PedagogyFocus groupSociology

Abstract

fetched live from OpenAlex

Service-learning experiences bolster the acquisition of disciplinary knowledge and promote the development of transversal skills such as confidence, leadership, commitment and social justice. This study investigates the development of transversal skills through courses using the service-learning methodology. The qualitative research designed and validated a semi-structured interview and a focus group, involving 20 and 8 student teachers respectively, who were selected by accidental non-probabilistic sampling. Open coding was used to analyse the information collected. The findings show that the factors that bolster the development of skills during service-learning experiences are linked to the students' prior knowledge and the way in which they connect this knowledge to the experience; the opportunities presented to the students depending on the length of the experience, the characteristics of the context and the pedagogical support received, as well as the processes the students engaged with during the service, together with the spaces for participation and involvement that the practical experience included. The paper discusses and draw conclusions on how the presence or absence of any of these elements will affect the development of skills during the service-learning experience.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.321
Teacher spread0.301 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2021
Admission routes1
Has abstractyes

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