Using systems thinking to connect green principles and United Nations Sustainable Development Goals in a reaction stoichiometry module
Bibliographic record
Abstract
To help students address problems related to climate change, chemistry fundamentals are taught using sustainable principles. The principles of green chemistry and United Nations Sustainable Development Goals (SDGs) are guides to help us reach a sustainable future. Educators use these to create resources to connect green principles and sustainability goals. Systems thinking provides the method for creating relevant lectures, meaningful activities, and cohesive assessments in an educational module. A week-long stoichiometry module for introductory chemistry is described. Students tackle multiple learning outcomes to answer complex questions such as ‘what makes an reaction efficient?’. This module relates SDGs #7 and #13, clean energy and climate action, to the green principle of atom economy, which evaluates the efficiency of chemical transformations. The process of backward design is used with systems thinking to map learning outcomes across the module. Students demonstrate skills related to individual outcomes and use their knowledge to evaluate chemical systems from multiple perspectives across outcomes. Incorporating real-world examples the module explores how incomplete combustion impacts human health and the environment while exploring the material efficiency of making different fuels. The context and practice of sustainable science can be used to teach chemistry in a systematic way.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".