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Record W4361987706 · doi:10.1344/ridas2022.14.6

El aprendizaje-servicio universitario: valor pedagógico y valor social

2022· article· es· W4361987706 on OpenAlexaff
Ana Ayuste, Mireia Esparza, Montserrat Payá, Victoria Morín

Bibliographic record

VenueRIDAS Revista Iberoamericana de Aprendizaje y Servicio · 2022
Typearticle
Languagees
FieldSocial Sciences
TopicService-Learning and Community Engagement
Canadian institutionsAdidas (Canada)
Fundersnot available
KeywordsHumanitiesPersonaCartographyPolitical sciencePhilosophyGeography

Abstract

fetched live from OpenAlex

Gracias a la labor y esfuerzos de numerosas personas en diferentes países, entre quienes se encontraba la profesora Laura Rubio Serrano de la Universitat de Barcelona, la presencia del aprendizaje-servicio (ApS) en la docencia universitaria es una constante en la actualidad. El ApS destaca por unir a su valor pedagógico, el social y solidario. Se presentas tres experiencias de implementación, diversas en cuanto a grados, cursos y carácter de las asignaturas, y ofrece indicadores del valor pedagógico y del valor social del ApS en la educación superior, que se extienden a los tres agentes implicados (estudiantes, profesionales de las entidades participantes y profesorado universitario). De esta manera, se consigue cumplir con las tres misiones de las universidades: formación de futuros profesionales, construcción de conocimiento y responsabilidad social. Ofrecer, desde las universidades, una formación situada en la práctica profesional y que intenta dar respuesta a necesidades sentidas por la sociedad quizá no sea posible solamente a través de la participación en proyectos de ApS, pero no cabe duda de que hacerlo mediante esta metodología es garantía de consecución y de calidad

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.711
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.005
Science and technology studies0.0110.001
Scholarly communication0.0010.001
Open science0.0060.004
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0120.001

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 head0.023
GPT teacher head0.302
Teacher spread0.279 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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