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Enregistrement W1926629023 · doi:10.24908/pceea.v0i0.4902

Engineering Education Research and Development at Queen’s University

2013· article· en· W1926629023 sur OpenAlexvenueaboutno aff
David Strong, Brian Frank

Notice bibliographique

RevueProceedings of the Canadian Engineering Education Association (CEEA) · 2013
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Education and Curriculum Development
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOutreachEngineering educationMultidisciplinary approachHigher educationProcess (computing)EngineeringEngineering ethicsPedagogyMedical educationEngineering managementPsychologySociologyComputer sciencePolitical scienceMedicine

Résumé

récupéré en direct d'OpenAlex

Research and development in engineering education has been prominent at Queen’s University since the early 1990’s. Initially focused on evolving improved methods to encompass theoretical, practical, industrial, and multidisciplinary aspects into undergraduate engineering programs, the outcome of those early endeavours became what is now known as “Integrated Learning” at Queen’s. This effort also recognized the need for a new and different facility to accommodate evolving pedagogical approaches and enhanced team-based activities, and in 2005, the 6,000 m2 Integrated Learning Centre was opened. Both the Integrated Learning philosophy and the corresponding facility have been a tremendous success. With the establishment of Integrated Learning , engineering education research began to expand both in breadth and depth. Research studies and publications have included topics such as optimized assessment of both students and pedagogical activities, understanding student attitudes towards learning, evaluating engineering practitioners’ needs and expectations of engineering graduates, defining needs for outreach activities, developing and assessing measurements for graduate attributes, and using web-based classroom response systems for quality student feedback. Graduate students have been engaged in engineering education research topics for nearly a decade, with the first Master’s student with a full- fledged engineering education research topic graduating in 2006, and the first post-doctoral researcher hired in 2011. Additional graduate students have been engaged in engineering education research since, producing four more Master’s graduates to date, and two more in process. The outcomes from this research, combined with collaborative efforts across the faculty, have resulted in new and innovative pedagogy, including the Multidisciplinary Design Stream and the recently introduced Engineering Design & Professional Practice sequence. Both of these programs include a combination of proven and innovative pedagogy, and through multiple assessment techniques, themselves become the subject of ongoing research and development. Further research studies are underway. One is exploring how critical thinking develops in first year engineering, and whether the use of complex authentic engineering problems assists in developing critical thinking. Queen’s is also part of a learning outcomes consortium project with Toronto, Guelph, and University of Kansas, and three Ontario colleges, to develop procedures for assessing learning outcomes at an institutional level. In addition, Queen’s is part of a collaboration with 7 Canadian and US schools on research into sustaining change in institutions and influencing adoption of evidence-based practices. The panel presentation will provide more detail on our past, present, and future research in this field. The engineering education research community in Canada is dynamic but under-represented, and it is hoped that this session will encourage more engineering academics to venture into this field.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,309
Score d'incertitude au seuil0,997

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,007
Tête enseignante GPT0,194
Écart entre enseignants0,187 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2013
Routes d'admission2
Résumé présentoui

Explorer davantage

Même revueProceedings of the Canadian Engineering Education Association (CEEA)Même sujetEngineering Education and Curriculum DevelopmentTravaux en français237 207