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Enregistrement W2741050295 · doi:10.18260/p.25530

Impact of an Extracurricular Activity Funding Program in Engineering Education

2016· article· en· W2741050295 sur OpenAlexaff
Emily Marasco, R. Paul, Stephanie Hladik, Marcela Rodriguez, Laleh Behjat, Lynne Cowe Falls

Notice bibliographique

Revuenon disponible
Typearticle
Langueen
DomaineEngineering
ThématiqueEngineering Education and Curriculum Development
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésTRIPS architectureExperiential learningMedical educationVariety (cybernetics)Engineering educationPublic relationsPsychologyPolitical sciencePedagogyEngineeringComputer scienceEngineering managementMedicine

Résumé

récupéré en direct d'OpenAlex

Abstract Participation in extracurricular activities improves engineering students’ professional and leadership skills, civic-engagement and engineering abilities. These activities provide students with cultural and scientific immersion, and are an excellent complement to a technical engineering degree. However, students can be restricted in their ability to participate due to limited finances and due to lack of awareness on opportunities. To minimize this challenge, the *name* Student Activity Fund (SSAF) was developed to promote participation in activities that enhance engineering education and leadership development through a variety of activities. This paper will discuss the details of the SSAF, and provide insight into the levels of impact seen from the program. Annually, students apply to the fund competition as either individuals or groups. The applications must include proposed budgets, detailed itineraries, and a clear description of how the activity will contribute to their leadership, professional, and personal development. In addition, the students must report back to the fund indicating how the moneys were spent and how they brought their experience and knowledge back to campus. A wide range of activities are eligible, however all activities should be experiential in nature and highly participatory. Some examples of successful applications in the past include the solar car team, educational trips to major cities, group studies abroad, and academic conferences. Activities should complement and enhance classroom learning and the engineering graduate attributes. Applications are evaluated by a committee of students, alumni and faculty. When the evaluation committee reviews applications they are looking for students who have clearly demonstrated how the activity will enhance their engineering education. Successful applicants must also submit a final report afterwards describing the impact on their learning experience, a reflection on their personal and leadership development goals, and a description of their contribution. The paper will discuss the evolution of the fund since its inception ten years ago. Data to be presented includes the number of funded students and groups, percentage of applications compared to activities funded, and trends in the funding applications activity types over the years. When discussing the impact of these activities, we will look at three factors. Firstly, the factor of time will investigate immediate, short term and long term impacts. The second factor, culture, will compare the impact on the individual to the impact brought back to the University community. And lastly, the factor of depth will gain insight into whether the impact is on the surface or if the impact has a much deeper change. All of these will consider both personal and academic growth for the students, their peers, the faculty and faculty members. The SSAF provides a model for encouraging extra-curricular activities for other schools as it reduces the barrier to these experiences while building student leadership through the application and competition. The paper will also recommend how to further increase the success and impact of an extracurricular activity funding program in 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: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,904
Score d'incertitude au seuil0,359

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 GPT0,281
Écart entre enseignants0,272 · 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'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

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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