Conceptualising and (re)modelling ESE teaching quality
Notice bibliographique
Résumé
Building on symposia at the ECER network 30 in 2023 (Lysgaard & Gericke, 2023) and 2024 (Lysgaard & Tryggvason, 2024) this presentation attempts to synthesize findings and conceptualize and model the qualities of green transition teaching within the broader field of ESE, ESD and eco-literacy research. The point of departure is an elaboration of prior research and policy work on ESE/ESD teaching quality frameworks (Mogensen, Breiting, & Mayer, 2005; UN, 2015) and their imagined and real practical implications for local school systems across the globe. We critically discuss whether one universal model for ESE teaching could be established (Laugesen & Elf, 2023; Lysgaard & Bengtsson, 2020) and argue that a more situated and pluralistic understanding of ESE teaching sensitive to local school traditions, potentials and constraints is probably more viable. Based on a large-scale empirical research project in Northern Europe (Laugesen & Elf, 2023) as well as a range of smaller, linked international case studies, the presentation, focuses on how different concepts and practices of environmental and sustainability education (ESE) can be identified, understood and further developed in schools and in and across school subjects while also considering ecosystemic aspects. A key feature of this presentation is that it focuses on exploring qualities in actual teaching in an empirical sense (i.e. drawing on substantial qualitative and quantitative data) in conversation with what is and has been considered both historically and theoretically ‘good’ quality teaching, in a more normative sense. Throughout the development of the field of Environmental and Sustainability Education (ESE) there has been a steady influx of implicit and explicit understandings of quality as a way of deliberate on the core, emphases and parameters of associated education and teaching (Poeck & Lysgaard, 2016; Poeck, Öhman, & Östman, 2019). From the foregrounding of ‘facts, knowledge and behavior’ via critiques drawing on a German-Nordic Bildung-infused focus on critical thinking and democratic participation (Mogensen et al., 2005) to more recent post-anthropocentric perspectives (Lysgaard, Bengtsson, & Laugesen, 2019; Paulsen, 2021), ESE theory and practice continue to be both highly contextualized and contested in relation to local and national educational structures and environmental and sustainability concerns (Greer, Walshe, Kitson, & Dillon, 2024). Equally, the ongoing mainstreaming tendencies within the field, particularly within the context of the Sustainable Development Goals, including SDG4 on Quality Education (United Nations, 2015), highlight the importance of developing a more nuanced language of which notions of quality are relevant and prioritized, how these might imperil or strengthen policy, practice and research-based understandings of the field, and how they could be taken up in by practitioners and resonate with practice. The presentation focuses on how a diversity of concepts and practices of quality in teaching and education within the field of ESE can be identified, understood and developed further. This presentation builds on the earlier ECER NW 30 symposia in order to explore the key question of: How can we understand quality education and, more specifically, quality teaching in light of environmental and sustainability education, and what might be the qualities of green transition teaching in educational practice?
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 | 0,011 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,002 | 0,019 |
| Communication savante | 0,014 | 0,015 |
| Science ouverte | 0,002 | 0,006 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 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 ».