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Enregistrement W87388477

Effects of Cooperative Education on Community College Employment Outcomes at the School to Work Transition

2009· article· en· W87388477 sur OpenAlexaboutno aff
James Goho, David A. Rew

Notice bibliographique

RevueJournal of applied research in the community college · 2009
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueEntrepreneurship Studies and Influences
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCooperative educationEarningsDescriptive statisticsHuman capitalWork (physics)PsychologyHigher educationMathematics educationMedical educationSociologyPedagogyVocational educationBusinessEconomicsEconomic growthEngineeringAccountingMathematicsMedicine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The major purpose of cooperative education is to prepare students for the workplace by combining academic education with practical experience to develop employment competencies. This research compared employment outcomes and employment earnings for graduates from cooperative education programs with graduates from non-cooperative programs at a large comprehensive community college. Two major sources of data were used in the analysis. Four years of data from an annual survey of recent graduates were merged with institutional data on the characteristics of respondents. After descriptive statistics suggested there were differences between the two groups of graduates, regression techniques were employed to isolate the effects of other possible explanatory variables. Findings indicated that recent cooperative program graduates were more likely to be employed, to be employed in positions related to their education, and to have somewhat higher earnings than non-cooperative program graduates. This suggests cooperative education may signal to the employing community that cooperative education program graduates bring enhanced human capital to the job. Introduction to Cooperative Education The major purpose of cooperative education is to prepare students for the workplace by combining academic education with practical experience to develop specific as well as generic competencies (Rainsbury, Hodges, Burchell, & Lay, 2002). The point is to link the world of academic learning more closely to the world of employment earning and learning. There are two predominant models for cooperative education (Grubb & Villeneuve, 1995), and both involve classroom-based and work-based learning. One model has students divide their daily activities between school and work, while the second uses alternating time periods (usually semesters) of paid employment and academic study. Both models also use connecting activities such as co-op coordinator visits to job sites and employer attendance at orientation or selection sessions. Cooperative education models are used at post-secondary education institutions in the United States (Kerka, 1999) and in Canada (Marquardt, 1996). Such programs are found in many fields of academic study (Thiel & Hartley, 1997). Benefits of Cooperative Education Many benefits are ascribed to flow from cooperative education to the employing community as well as to students. For employers, the benefits include superior labor force flexibility, reduced costs of recruitment and training, and input into curricula development at community colleges and universities. The benefits for students include work experience, hands-on application of classroom learning, a network of contacts, and perhaps improved employment outcomes after graduation (Grubb & Villeneuve, 1995; Darch, 1995). In addition, students may achieve enhanced earnings while learning. This income is important for students and for the economy at a period in an individual's life generally associated with educational costs rather than earning an income. For example, during the 2000-01 school year at the community college under study, 618 co-op student placements were created, generating $4.4 million (Canadian) dollars of labor income for these students while they pursued a post-secondary education (on average, approximately $7,100 per student). A student's overall cost for education comprises not only direct costs such as tuition, books, accommodation, and meals, but also the opportunity cost of student time, measured usually in terms of income foregone because of studying rather than working. This forgone income is also considered to be a loss of potential output and is a resource cost to the economy as a whole (Jones, 1995). The income foregone is often partially offset by work obtained while attending school. At the study community college, a survey of a random sample of 396 full-time certificate and diploma students indicated that about 50 % work while studying. …

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,007
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,020
Score d'incertitude au seuil0,040

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,007
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,003
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,060
Tête enseignante GPT0,346
Écart entre enseignants0,287 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations4
Publié2009
Routes d'admission1
Résumé présentoui

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