Integrating the Molecular Basis of Sustainability into General Chemistry through Systems Thinking
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The flow of materials and energy through society is an integral but poorly visible element of global sustainability agendas such as the Planetary Boundaries Framework and the UN Sustainable Development Goals (UNSDG). Given that the primary activities of chemistry are to analyze, synthesize, and transform matter, the practice of chemistry has a great deal to contribute to sustainability science, which in turn should play an increasingly important role in reshaping the practice of chemistry. Success in integrating sustainability considerations into the practice of chemistry implies a substantial role for chemistry education to better equip students to address the sustainability of earth and societal systems. Building on the framework of the IUPAC Systems Thinking in Chemistry Education (STICE) project, we develop approaches to using systems thinking to educate students about the molecular basis of sustainability, to assist chemistry to contribute meaningfully and visibly toward the attainment of global sustainability agendas. A detailed exemplar shows how ubiquitous coverage in general chemistry courses of the Haber–Bosch process for the synthesis of ammonia could be extended using systems thinking to consider the complex interplay of this industrial process with scientific, societal, and environmental systems. Systems thinking tools such as systems thinking concept map extension (SOCME) visualizations assist in highlighting inputs, outputs, and societal consequences of this large-scale industrial process, including both intended and unintended alterations to the planetary cycle of nitrogenous compounds. Strategies for using systems thinking in chemistry education and addressing the challenges its use may bring to educators and students are discussed, and suggestions are offered for general chemistry instructors using systems thinking to educate about the molecular basis of sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".