Identifying chemistry students’ baseline systems thinking skills when constructing systems for a topic on climate change
Notice bibliographique
Résumé
Recently, increased attention towards systems thinking (ST) in chemistry education has aimed to bridge disciplines and equip citizens and scientists with skills needed to address global challenges such as sustainability and climate change. As a result, new resources have emerged for educators to implement systems thinking in chemistry education (STICE), including a proposed set of ST skills. While these efforts aim to make ST implementation easier, little is known about how to assess these skills in a chemistry context. Additionally, there are no studies that have investigated how chemistry students naturally engage with ST learning activities; such information would guide educators about where to place emphasis when teaching ST skills. In this study, we investigated ST skills employed by students who constructed visual representations (systems) of a topic related to climate change. Eighteen undergraduate chemistry students from first- to third-year participated in this study. We designed and implemented a ST intervention to capture how students engaged with three ST tasks, performed individually and collaboratively. In our analysis, we assessed eleven ST skills that aligned with the five characteristics of STICE proposed by York and Orgill. We found that most participants demonstrated these ST skills when assessing ST skills exactly as articulated in the literature. When further investigating the extent that participants demonstrated these skills, we identified aspects of these skills that participants did and did not demonstrate. We found that (1) participants’ systems lacked concepts and connections at the submicroscopic level, (2) participants’ systems included multiple types of connections in their systems but few circular loops and causal connections, (3) participants predicted how their systems changed over time but lacked multicomponent causal reasoning, and (4) participants’ systems demonstrated the breadth of connections but did not consider human connections to the underlying chemistry of climate change topics. These findings identify aspects of ST where chemistry educators need to place emphasis when teaching ST skills to chemistry students and when guiding learning activities and other assessments. Using our findings, we created a ST rubric for the chemistry community as a tool for assessing ST skills.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».