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Enregistrement W2726034347 · doi:10.18260/1-2--14217

Freshman Engineering & Computer Science Program At Wright State University

2020· article· en· W2726034347 sur OpenAlexaboutno aff
Tom Bazzoli, Blair A. Rowley

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Education and Pedagogy
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésWrightQuarter (Canadian coin)CurriculumEngineering educationState (computer science)Science and engineeringMathematics educationEngineeringComputer scienceMedical educationPsychologyEngineering managementPedagogyMedicineEngineering ethicsHistory

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 Freshman Engineering & Computer Science Program At Wright State University Blair A. Rowley and Tom L. Bazzoli College of Engineering & Computer Science Wright State University Dayton, OH 45435 Abstract The freshman program is designed to introduce engineering principles through hands-on experience, establish a sense of community, develop an understanding of how to be successful in studying engineering, and to foster collaboration among students through cooperative teaming. This paper presents an overview of the program that has evolved over the past six years. Introduction Six years ago the college committed to developing a freshman experience which would help in recruitment and retention. Initially it was designed on Drexel University’s freshman program 1. During the first two years enrollment was limited to approximately 60 students who exhibited high achievement in GPA and test scores. This was a three-quarter course taught by a number of professors from various college departments. Using this experience as a base, a full time director was appointed and the program was expanded the third year to include all entering freshmen except for those in the Biomedical Engineering Premedical Program. They were exempt as the freshman program could not be worked into their crowded curriculum. For the next two years the program was a three hour per quarter, two quarter course. It had a fall- winter, winter-spring structure. Each first quarter had one 2-hour lecture and two, 1-hour laboratories per week. The curriculum the first quarter had two teaming events, basics of engineering drawing, an introduction to instrumentation, resistive circuits involving Ohms and Kirchoff’s laws, and integrated circuits used for timers, flip-flops, counters, and an introduction to two of the college programs. In addition the students learned to use HTML to design their own web sites and MatLab and Excel to solve statistical problems involving normal distributions. The second quarter had one, 2-hour lecture and one, 1-hour laboratory, and one teaming event. The students were introduced to ethics and five more college programs with the labs designed and taught by the departments. The teaming event involved the construction and flying of a radio controlled, electrically powered, slow flying airplane. In addition they were introduced to the engineering use of mathematics involving algebra, calculus, and differential equations. The biggest surprise came from the engineering mathematics effort the second quarter. Our college mathematics committee had postulated that the students were capable of handling higher mathematics earlier than programmed using the normal sequence taught by the mathematics department. They encouraged the freshman program to introduce over a four week period enough mathematics to enable the students to work an oscillatory motion problem using differential equations. This was accomplished starting with static pressure and beam problems, then projectile motion and finally mass on a spring motion. The outcome was so positive that the Proceedings of the 2005 American Society for Engineering Educational Annual Conference & Exposition Copyright © 2005, 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: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,536
Score d'incertitude au seuil0,466

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 Opus0,017
Tête enseignante GPT0,223
Écart entre enseignants0,206 · 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'étudeSimulation ou modélisation
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
Publié2020
Routes d'admission1
Résumé présentoui

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