Notice bibliographique
Résumé
My introduction to action research (AR) began in 2004 when I was selected to complete a 6month professional development AR course with my school board.At the time, I was an early career teacher trying to survive one of my Nirst teaching placements.My project title was Nitting: Why Do Junior Students Dislike French?The research process changed my teaching practice.I realized that research-based evidence was critical for guiding educational practice.Over the years as a public school teacher and now as a higher education teacher, I have completed several AR projects; each one has helped me gain more self-autonomy in my professional practice.I continue to pass along my belief and passion that AR is a self-changing process.For the past 4 years, I have taught an introductory research course to teacher candidates where they learn how to conduct their own "mini" AR projects based on problems of practice during their teaching practicum.Last term, my own AR project was to track my students' learning and responses to their AR processes and Nindings.I was pleased to discover that their responses mirrored how I felt in 2004: Many commented that they were pleasantly surprised at the amount they learned and how relevant AR could be to their teaching.Action research is an intentional and systematic investigation process (Stringer, 2014) that can help educators Nind solutions, based on evidence, to everyday issues and problems of practice.This special issue is designed to not only highlight the beneNits of AR but to also encourage educators to use AR to Nind solutions to the challenges created by the COVID-19 global pandemic.As we have all experienced, the pandemic created challenges, chaos, and many unknowns, such as the isolation of online learning, the rigid structures imposed in classrooms, and the extreme hurdles placed on researchers seeking ethical approval, to name a few.Like myself, educators, groups of educators, and educational system leaders were recognizing the powerful autonomy of conducting their own research on issues they were facing during the pandemic and determining links between effective professional practice and learning (Parsons et al., 2013).Out of necessity, partnerships were formed between teacher educators, teacher-mentors, and pre-service and/or novice teachers to Nind solutions to the many challenges created by the pandemic.Action research provided a method for "looking at one's practice or work
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 | 0,036 | 0,126 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,004 | 0,003 |
| Bibliométrie | 0,006 | 0,004 |
| Études des sciences et des technologies | 0,009 | 0,013 |
| Communication savante | 0,024 | 0,010 |
| Science ouverte | 0,005 | 0,005 |
| Intégrité de la recherche | 0,028 | 0,037 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,006 |
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 ».