Learning how to coach: the different learning situations reported by youth ice hockey coaches
Notice bibliographique
Résumé
Background: Large-scale coach education programs have been developed in many countries around the world to help prepare coaches for their important role. Coaches have said that they also learn to coach from experience, starting from when they were young athletes until their current coaching positions. Finally, in the last decade, Internet resources have begun to be promoted as valuable tools for learning. Most of the studies on coaches' development have focused on only one of these three ways of learning how to coach. Purpose: To explore the different learning situations in which youth ice hockey coaches learn to coach. Participants: 35 volunteer youth ice hockey coaches from five minor hockey associations in the province of Ontario, Canada. Data collection: Coaches were interviewed individually using a semi-structured interview guide. The questions asked to coaches were about their learning through formal large-scale coach education programs, their learning experiences outside of these programs starting when they were young athletes until their actual head coaching positions, and their use of the Internet. Data analysis: The first part of the interview consisted of specific questions regarding the number of years coaches had played and/or coached hockey and their level of coaching certification. The answers to these questions were entered directly on a form and entered later into Microsoft Excel to perform descriptive statistical tests. The second part of the interview involved more in-depth questions regarding what learning opportunities contributed to their development as a coach. Finally, questions were asked regarding how they use the Internet in their coaching. The content of this second part of the interview was transcribed verbatim into Microsoft Word rich text format for further data analysis using Nvivo software (Qualitative Solution Research, 2002). Findings: The results revealed seven different learning situations including (a) large-scale coach education programs, (b) coaching clinics/seminars, (c) formal mentoring, (d) books/videotapes, (e) personal experiences related to sport, family, and work, (f) face-to-face interactions with other coaches, and (g) the Internet. Conclusion: Considering that coaches learn to coach through many learning situations, it would be inappropriate to discriminate against any of these situations, since each situation seems to have a unique role in the development of a coach. Therefore, it may be concluded that coach education should include a combination of all seven learning situations, instead of focusing on one. Future research should concentrate on investigating the complementary potential of these situations and what can be done to make each of these situations more appealing to coaches.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».