MétaCan
Menu
Back to cohort
Record W2990844269

INNOVACIÓN PEDAGÓGICA INTERDISCIPLINAR ENTRE INGENIERÍA BIOMÉDICA Y CIENCIAS DE LA SALUD

2019· article· es· W2990844269 on OpenAlexaff
William Ricardo Rodríguez Dueñas, Adriana Ríos Rincón

Bibliographic record

VenueEncuentro Internacional de Educación en Ingeniería 2019 · 2019
Typearticle
Languagees
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHumanitiesSociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

La ingenieria biomedica es un campo interdisciplinar que requiere de profesionales que sepan resolver problemas en equipos multidisciplinares de manera eficiente. Sin embargo, en la universidad, los estudiantes de ingenieria biomedica tienen pocos escenarios en donde puedan adquirir y consolidar estas competencias con estudiantes de otras areas, por ejemplo, estudiantes de ciencias de la salud. Una forma de abordar este problema es ofrecer cursos interdisciplinarios en donde se apliquen tecnicas de aprendizaje activo y colaborativo que permitan esta adquisicion y consolidacion de competencias y que a su vez se resuelvan problemas de contextos profesionales reales. Este trabajo muestra los resultados de un estudio de dos anos en donde se implementaron tecnicas de aprendizaje activo y colaborativo para promover entornos de aprendizaje significativos en estudiantes de ciencias de la salud e ingenieria biomedica. Las tecnicas incluyeron: Aprendizaje basado en proyectos, Juego de roles y Hackathons. Los resultados muestran una fuerte correlacion entre la satisfaccion del aprendizaje y la comunidad de practica creada en los estudiantes. Ellos estuvieron satisfechos con la oportunidad de resolver problemas a traves del trabajo en equipos interdisciplinarios y ahora dan mas relevancia a la opinion de estudiantes de otras profesiones.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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 score0.532
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.003

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 head0.003
GPT teacher head0.254
Teacher spread0.251 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueEncuentro Internacional de Educación en Ingeniería 2019Same topicBiomedical and Engineering EducationFrench-language works237,207