Exploring the Use of Lesson Study with Six Canadian Middle-School Science Teachers
Notice bibliographique
Résumé
This qualitative case study explores the use of lesson study over a ten-week period with six Ontario middle school science teachers.The research questions guiding this study were: (1) How does participation in science-based lesson study influence these teachers': (a) science subject matter knowledge (science SMK), (b) science pedagogical content knowledge (science PCK), and (c) confidence in teaching science?, and (2) What benefits and challenges do they associate with lesson study?Data sources for this study were: teacher questionnaires, surveys, reflections, preand post-interviews, and follow-up emails; researcher field notes and reflections; preand post-administration of the Science Teaching Efficacy Belief Instrument; and audio recordings of group meetings.The teachers demonstrated limited gains in science SMK.There was evidence for an overall improvement in teacher knowledge of forces and simple machines, and two teachers demonstrated improvement in over half of the five scenarios assessing teacher science SMK.Modest gains in teacher science PCK were found.One teacher expressed more accurate understanding of students' knowledge of forces and a better knowledge of effective science teaching strategies.The majority of teachers reported that they would be using three-part lessons and hands-on activities more in their science teaching.Gains in teacher pedagogical knowledge (PK) were found in four areas: greater emphasis on anticipation of student thinking and responses, recognition of the importance of observing students, more intentional teaching, and anticipated future use of student video data.Most teachers reported feeling more confident in teaching structures and mechanisms, and iii attributed this increase in confidence to collaboration and seeing evidence of student learning and engagement during the lesson teachings.Teacher benefits included: learning how to increase student engagement and collaboration, observing students, including video data, observing colleagues teach, time to collaborate, plan, and reflect, teaching the same lesson to two classes, more intentional teaching, and increasing social interactions.Teacher challenges included: teacher unfamiliarity with the students being taught, time spent taking part in lesson study, teachers in the role of observers, and impact of observers and videotaping on students and teachers during lesson enactments.Next, I must acknowledge what a wonderful supervisor Azza Sharkawy has been.Despite being very busy herself, Azza has always made time to meet with me and to carefully read all the many words that I have written.Azza has been especially awesome in the final pushes to submission and completion of corrections.She has always been positive, enthusiastic, and very supportive.At the same time she has not been afraid to push me when needed, and this dissertation
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,004 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».