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Record W2072169127 · doi:10.1080/17408980701282019

Learning how to coach: the different learning situations reported by youth ice hockey coaches

2007· article· en· W2072169127 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePhysical Education and Sport Pedagogy · 2007
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoachingPsychologyAthletesThe InternetIce hockeyMedical educationCertificationScale (ratio)Applied psychologyPedagogyComputer scienceManagementMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.144
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.385
Teacher spread0.340 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it