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Enregistrement W7044316293

Workforce Adaptation: Employer Assessment of Graduates of the Industrial Distribution Program at Texas A&M University

2015· dissertation· en· W7044316293 sur OpenAlexaff

Notice bibliographique

RevueOakTrust (Texas A&M University Libraries) · 2015
Typedissertation
Langueen
DomaineSocial Sciences
ThématiqueHigher Education and Employability
Établissements canadiensBarrick Gold (Canada)
Organismes subventionnairesnon disponible
Mots-clésWorkforceDistribution (mathematics)CurriculumWork (physics)Focus groupQualitative propertyFocus (optics)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The purpose of this study was twofold: to determine if the Industrial Distribution Program at Texas A&M University is producing graduates whom employers consider highly adaptable to the workplace and who quickly become productive in their organizations, and if this is true, to understand what characteristics employers perceive these graduates having that makes them successful.\n\nThis was a mixed methods study. The quantitative portion of the study used a 36 question survey instrument to gather responses from employers who hire recent graduates from the Industrial Distribution Program at Texas A&M University concerning the characteristics that made these graduates successful. The qualitative portion of the study utilized two focus groups in which employers of graduates of the Industrial Distribution Program at Texas A&M University discussed why they felt that these graduates adapted quickly and performed well in the workplace. An education model was developed from the findings.\n\nEmployers responding to the survey attributed the success of these graduates to their technical skills, in conjunction with their character and interpersonal skills. Employers also cited job knowledge, an understanding of cultural adaptation, and realistic expectations of the kind of work they would be doing upon entering the workplace as influencing their ability to adapt quickly and to become highly productive employees.\n\nThe findings from comments made by employers in the focus groups, in addition to being consistent with the findings of the survey, identified three key areas beyond the interdisciplinary curriculum that influence the ability of graduates from the Industrial Distribution program to adapt quickly and to become highly productive employees upon entering the workplace. The first area was the characteristics of the student attracted to the program. Beyond the intelligence required by the rigorous academic requirements for admittance to Texas A&M University, employers identified integrity, a strong work ethic, and a competitive desire to do well. The second area is the interaction that the faculty has with industry. Many of the members of the faculty have worked for companies in industry; others are connected to industry through research and class projects and the delivery of professional development programs to individuals who work in industries that hire graduates from the Industrial Distribution Program. The third area focused on how the companies that hire the graduates of the Industrial Distribution Program influence and support the program. By providing funding and equipment for labs, financial support for endowments, research and scholarships, and summer internships for students these companies not only hire graduates of the program, they help to educate the students. The study found that collectively these factors work in conjunction to provide the experiential learning opportunities that expose students to applications for what they are learning and foster realistic expectations concerning what it will take to adapt and perform well once they enter the workplace.

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)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,747
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0010,001
Communication savante0,0000,001
Science ouverte0,0010,000
Intégrité de la recherche0,0010,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,078
Tête enseignante GPT0,325
Écart entre enseignants0,247 · 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.

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
Publié2015
Routes d'admission1
Résumé présentoui

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