Opportunities and Barriers for Ontario Teachers in their Delivery of Environmental Education using Information and Communication Technologies
Notice bibliographique
Résumé
<div>Teaching and learning about the environment in the present day is filled with possibility, challenge, and urgency. Government-mandated environmental curriculum, where it exists, can provide important pedagogical and content guidance. However, bottom-up and teacher-initiated approaches to the timely delivery of relevant and contemporary environmental education are required. This research identifies and describes barriers and opportunities to the delivery of environmental education in Ontario, Canada. It also explores the receptivity of teachers to the use of information and communication technologies (ICTs) as tools to complement existing instructional methods, and proposes refocusing on local geographies to exemplify human-environment interactions. Two methods of data collection were used: an online survey (n=54), a semi-structured focus group (n=18). Both approaches engaged teachers within the Toronto District School Board (TDSB), Canada’s largest school board. Three-quarters of study participants (76%) identified that teaching about the environment with hands-on assignments (e.g., data collection, field observations, experiments) was beneficial to student learning. A similar majority of teachers (74%) agreed that environmental education was an afterthought in the Ontario curriculum. A strong positive response from teachers was solicited when they were asked if ICTs were useful teaching tools. Using a Mantel-Haenszel test of trend, teachers’ perception of student enjoyment in, and engagement with, subject matter was shown to be significantly positively associated with the frequency of environmental content included in their lessons (p<0.000). NVivo software was used with content arising from the focus group discussion, and a content analysis was run to identify the frequency with which educators described current environment-related teaching, providing both new details and offering greater context to the online survey responses. While highlighting systemic weaknesses in the delivery of environmental education in Ontario, this study identified tangible avenues that teachers and schools can pursue in order to bridge the gap between environmental rhetoric and action-oriented practice.</div><div><br></div><div>Keywords: environmental education, place-based learning, Ontario, information and communication technology (ICTs), policy, mixed methods </div>
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 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 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 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 ».