We are all downstream: Teaching middle years science from a sustainability perspective
Bibliographic record
Abstract
The 21st century has emerged with Canadians experiencing great concern about how we do things in the world. The degrading environment preys greatly on the minds of Canadians while our actions may not match our thoughts. How do we educate our students as future leaders about sustainability and help them understand that our individual actions make a difference? The intent of this study was to make a difference in students’ and teachers’ lives. It needed to be determined if teachers felt that there was a gap in the current way that we are teaching about sustainability. The results of a Manitoba teacher survey and a literature review identified several different risk and protective factors: those that either constrain or support the teaching of sustainability in a science classroom. The three risks that were discovered to be the strongest were preparation time, availability of resources and that sustainability issues are often highly complex. These concerns became the foundation for informing the implementation phase of this study. From this information a resource that met all of the specific learning outcomes (SLOs) as mandated by Manitoba Education, Citizenship, and Youth (MECY) for the grade 8 Water Systems cluster was designed and piloted. Bronfenbrenner’s Bioecological theory (1979) and The Natural Step’s Four Systems Conditions were used as a foundation. There was a significant difference between the pilot groups and the control groups in three of the four areas tested. Teachers reported enjoying using the resource, and finding it helpful. They also reported that their students were engaged by the use of the resource. The thesis summation suggests how the resource might be shared and improved upon with and by teachers around the province and beyond, and hope that it provides a framework for future lessons or units related to sustainability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.011 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".