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Enregistrement W2142173279 · doi:10.1034/j.1600-0579.6.s3.3.x

1.1 Student selection and the influence of their clinical and academic environment on learning

2002· article· en· W2142173279 sur OpenAlex
Peter Gaengler, Johann de Vries, Llze Akota, Irena Balčiūnienė, Peter Berthold, Maria Gajewska, David C. Johnsen, Ilga Urtâne, Laurence J. Walsh, Alies Zijlstra

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Notice bibliographique

RevueEuropean Journal Of Dental Education · 2002
Typearticle
Langueen
DomaineMedicine
ThématiqueMedical Education and Admissions
Établissements canadiensUniversity of Manitoba
Organismes subventionnairesnon disponible
Mots-clésSelection (genetic algorithm)BenchmarkingVariety (cybernetics)Process (computing)Medical educationDental educationValue (mathematics)PsychologyOutcome (game theory)Higher educationMathematics educationPedagogyMedicinePolitical scienceComputer scienceBusinessMarketing

Résumé

récupéré en direct d'OpenAlex

Student selection and recruitment play a vital role in the successful outcome of dental education. To identify key issues and practices in selection and recruitment, the group assessed current processes, philosophies and practices from a range of different educational systems, although it was not possible to gather data from all countries or continents within the timeframe provided. Furthermore, the group explored the effect of the educational learning environment on the successful outcome of teaching dental students. It is clear that a wide variety of practices and philosophies exist and are used in different parts of the world. Measuring the success of any given process used for student selection remains a challenge. In some parts of the world, certain practices have become an integral part of the tertiary educational system, and have been applied in a similar way by many or all of the dental schools in that country. In other countries, methods vary from one dental school to another, often reflecting differences in the structure and philosophy of the educational system. There was great variation in the combinations of selection criteria used and in student recruitment strategies. However, it was clear that there was much to be gained by learning from the experiences of other dental schools in student selection. Lessons learned, best practices and philosophies used and supporting value systems proved to be very helpful for benchmarking the processes used. In the discussion of student selection, a number of important questions were raised which deserve further thought and reflection both in the ongoing debate and as part of the ever-changing world of dental education. Important new matters that require more debate and research include: a) ethical issues, including the nature of funding from the student perspective, and the concern that in some regions dentistry may become a profession only for the elite or wealthy students. b) Health standards of students entering dental school. c) How realistic is the applicant's sense of dentistry as a profession? d) How accurate is the students' sense of their career opportunities and the employment market upon graduation? Finally, the over-arching question remains, how valid, reliable and predictable are existing selection practices? Will it be practical and meaningful to standardize methods used, or will exchanging ideas as part of this global debate assist the thought process of dental leaders to improve selection practices by learning from the experiences of other schools in different parts of the world? The processes of open debate, sharing ideas and opinions and identifying sound practices across the globe is a powerful catalyst for developing innovative answers to the complex problems posed by student selection and recruitment. A 'virtual' global process with wide input from as many dental schools as possible should improve the efficacy of student selection, and allow dental educators to identify the 'potential' of prospective students and predict more accurately dental student outcomes. The debate that we have started will certainly contribute to providing a knowledge base which dental educators will be able to draw on when reviewing selection processes in their own schools.

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.

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)0,001
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: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,452
Score d'incertitude au seuil0,218

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
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 recherche0,0000,001
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 Opus0,037
Tête enseignante GPT0,361
Écart entre enseignants0,324 · 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