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Enregistrement W2615739150 · doi:10.18260/1-2--6713

North American Engineering Education & Academic Exchange: Canada, Mexico, The United States

2020· article· en· W2615739150 sur OpenAlexaboutno aff
Thomas R. Phillips

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueHigher Education and Sustainability
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCurriculumSession (web analytics)Engineering educationLibrary sciencePolitical scienceSociologyComputer scienceLawWorld Wide Web

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 3260 North American Engineering Education & Academic Exchange: -- Canada, Mexico, the United States -- Thomas R Phillips, ABET/FlPSE Project Consultant Managing Director, Collegeways Associates (USA) From 1993 to 1996 the author served as ‘External Evaluator’ for the Regional Academic Mobility Program (RAMP), a multilateral exchange program run by the Institute of International Education (IIE). RAMP has brought together 26 institutions in Canada, Mexico, and the United States, moving over 200 students in its first three years. However, only about 12% of the exchanges have involved U.S. students. One of the impediments to recruitment has been a lack of timely, consistent, and useful information on programs. The author obtained a FIPSE/USDE grant to develop a guide, consisting of institutional and program profiles, curriculum tables, and selected course descriptions. French and Spanish materials were translated and converted to a standard format. The resulting Guide contains examples of over 100 Canadian and Mexican engineering programs across seven disciplines. The observations in this paper are based primarily upon information from the RAMP institutions. Engineering Education in North America I wanted to determine how a U.S. engineering student could benefit from studies in Canada or Mexico. Was there a professional rationale to support a marketing concept and strategy for the RAMP program? I soon found similarities among the course descriptions and curriculum charts. The topics listed in the standard engineering courses were much like ours - not surprising with the use of standard textbooks and software. Not so apparent is an emphasis on applied engineering skills that increases as you go from Canada to Mexico. In fact, Mexican universities feel that one of their strengths is a comparatively high percentage of faculty members who teach and work in industry. This is viewed as a positive feature in the preparation of graduates for jobs in Mexico’s “productive sector.” While this approach favors industry, it slows faculty development in Mexican universities. Even some of the larger engineering schools have a comparatively small core of full-time faculty with advanced degrees, and relatively small graduate engineering programs. Mexican mechanical and electrical engineering courses often include topics on design for manufacturing, manufacturing process design and control, fabrication, and applications of computers and electronics to manufacturing. Mexican civil engineering programs emphasize competency in construction, while chemical engineering programs serve the processing industries in chemicals, food, and materials. Mexican programs usually have an “industrial engineering” component, focusing more on the practical problems of industrial plants, facilities, and production management, and less on quantitative methods. Courses in labor law and personnel management are standard requirements. Mexican engineering students are taught design, but- also learn to “install, operate, and maintain” electronic, mechanical, and industrial equipment. Given Mexico’s growing manufacturing base, emphasis on infrastructure development, and the number of U.S. employers with operations in Mexico, a U.S. exchange student could create a valuable, marketable learning experience. In both Canada and Mexico, I saw opportunities for student projects and practical experience that would enhance a resume. 1

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 enseignants0,422
Score d'incertitude au seuil0,400

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
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 Opus0,022
Tête enseignante GPT0,316
Écart entre enseignants0,294 · 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

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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