United Nations Sustainable Development Goals as a Thematic Framework for an Introductory Chemistry Curriculum
Bibliographic record
Abstract
As part of a revision to the content and delivery of first-year chemistry instruction at the University of British Columbia’s Okanagan campus, we have employed the United Nations Sustainable Development Goals (UN SDGs) as a thematic framework. This framework was introduced to promote the achievement of affective learning outcomes, including a systems thinking approach to exploring the relevance of first-year chemistry content and concepts to societal and global challenges. Through this framework, sets of course concepts, which are traditionally limited in their application to isolated textbook chapters, are demonstrated, through various in-class group activities, to have collective applications to the environmental and societal systems embodied by specific SDGs. Student attitudes to this framework and its associated activities were examined via a course-end survey and in-depth semistructured interviews. Student responses were generally positive, indicating an appreciation for the relevance of course concepts to the global challenges described by the SDGs, and for many students, the SDG-framed learning activities aided in their understanding of course concepts.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".