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Enregistrement W2600346797 · doi:10.18260/1-2--9220

Enhancing Technology Development Through Lifelong Education Of Engineers And Technologists As Creative Professionals

2020· article· en· W2600346797 sur OpenAlexaffabout
Thomas Stanford, Michael Aherne, Duane Dunlap, Mel I. Mendelson, Donald Keating

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Education and Curriculum Development
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésLifelong learningEngineering educationProcess (computing)Engineering managementGraduate educationEngineeringEngineering ethicsHigher educationManagementSociologyComputer sciencePedagogyPolitical science

Résumé

récupéré en direct d'OpenAlex

Abstract NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 2793 Enhancing U.S. Technology Development Through Lifelong Education of Engineers and Technologists as Creative Professionals D. A. Keating, 1 T. G. Stanford, 1 D. D. Dunlap, 2 M. J. Aherne, 3 M. I. Mendelson 4 University of South Carolina 1/ Purdue University 2/ University of Alberta 3 Loyola Marymount University 4 Abstract There is growing recognition worldwide that traditional graduate engineering education neither fits the engineering innovation process necessary for competitiveness in the global economy nor reflects the way that graduate engineers and technologists learn and develop as professionals, innovators, entrepreneurs and leaders in industry. In today’s global economy, engineering innovation is recognized as a continuous, systematic needs-driven process, which is highly dependent upon the provision for lifelong learning, growth, and development of the nation’s graduate engineers and technologists in industry beyond their entry-level undergraduate baccalaureate preparation. Because of profound changes in engineering practice for real-world innovation, a transformation is underway in the U.S. Science and Engineering (S&E) innovation system. A concurrent, nonlinear model of needs-driven systematic engineering innovation, which is supported by directed scientific research, is replacing the sequential, linear research-driven model of engineering innovation. Graduate education must be responsive to this change and must build a new type model of in-service graduate professional education which reflects the substantial changes and characteristics of the engineering innovation process itself, and the stages of lifelong growth, professional dimensions, and leadership responsibilities associated with the modern practice of creative engineering in a knowledge-based, innovation-driven economy. Whereas traditional research-based graduate engineering education and teaching have resulted during the last three decades as a byproduct of the linear research-driven model of innovation, a new model of graduate professional education has been developed which focuses on lifelong professional education for emerging and experienced engineering leaders in industry as creative problem-solvers, technical program makers, technology policy makers, and leaders in the modern context of engineering practice for creative technology development and innovation. 1. Introduction More than ever, science, engineering, and technology are key to economic performance and social well being of industrialized nations. The ability to continuously create, develop, and innovate new and improved technology is rapidly becoming the major source of competitive advantage, worldwide, for sustained economic growth. The United States faces stiff competition in the global arena as other nations are also recognizing that growth performance in the new economy is dependent upon technological innovation. There is growing awareness, however, that fundamental changes have occurred in the 1990s with regard to the technological innovation process itself, and a new model of engineering innovation has emerged. Proceedings of the 2001 American Society for Engineering Education Annual Conference & Exposition Copyright ‹ 2001, American Society for Engineering Education

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: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,662
Score d'incertitude au seuil0,546

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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 Opus0,008
Tête enseignante GPT0,248
Écart entre enseignants0,241 · 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'étudeExpérimental (laboratoire)
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

Citations0
Publié2020
Routes d'admission2
Résumé présentoui

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