Developing principles of physical education teacher education practice through self-study
Notice bibliographique
Résumé
Background: The articulation of specific principles of teacher education practice allows teacher educators to make explicit the beliefs, values, and actions that shape their practice. Engaging in processes to articulate the principles that guide practice is beneficial not only for teacher educators and their colleagues but also for students. There are, however, few examples of principles that guide physical education teacher educators' practices. Self-study of teacher education practice (S-STEP) methodology offers one way of examining and articulating principles of practice. In this study, I make connections across several S-STEP research projects I have conducted individually and with colleagues, and share the principles that guide my practice with the physical education teacher education (PETE) community.Purpose: The purpose of this paper is to articulate my principles of practice using S-STEP. Specifically, I ask: (a) How can the articulation of my principles of practice reflect broad understandings of PETE? and (b) How can sharing principles of practice encourage debate and discussion amongst members of the PETE community? To what extent do the principles articulated have resonance for others?Participants and data collection: Six published self-studies as well as the raw data from those studies provided the data for this research. The raw data used in those studies consisted of self-generated data and data generated by others. Self-generated data consisted of written reflective journal entries gathered over five years and recorded audio conversations with two critical friends. Data generated by others consisted of semi-structured interviews conducted with two cohorts of pre-service teacher candidates: one consisting of 10 pre-service primary generalist teachers the other of 9 pre-service physical education specialists. Three interviews were conducted with each participant. Exit slips (informal evaluations) were also gathered from the specialist cohort.Data analysis: First, elements of the previously conducted self-studies were synthesised to identify general themes and outcomes that represented principles of practice. Second, in several instances, the raw data were revisited to verify and contextualise quotes and excerpts, and consider the extent to which the data captured the principles that were being articulated.Findings: Three central principles were identified that shape my understanding of a pedagogy of PETE: (a) building community is the foundation of practice, (b) not just modelling – explaining and reflecting upon modelling, and (c) identity matters. Identifying these principles has enabled me to better enact social constructivist approaches to learning, make explicit my personal and professional knowledge to myself, students, and colleagues; find meaning in my practice, and; begin sharing my partial understanding of practice with others in the teacher education community to generate debate and discussion.Conclusions: Self-study encourages teacher educators to share their knowledge so that it may be discussed, challenged, and critiqued to further collective understandings of teacher education practice. In this spirit, these principles are not offered as an exhaustive list of all that guides PETE practice, but as suggestive of possibilities that might reflect shared understandings of teacher education and thus have the potential to influence policy.
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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 | 0,049 | 0,044 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,021 |
| Communication savante | 0,007 | 0,005 |
| Science ouverte | 0,002 | 0,008 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
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 ».