Soil science education for Grades K–12 in Canada
Bibliographic record
Abstract
Soil scientists who interact with K–12 students or teachers may benefit from knowing what the provincial curricula say, what a typical classroom teacher knows, and what resources, programs, and opportunities are available regarding soil education. Many provinces have a soil science unit at the Grade 2–4 level in their curriculum. In all provincial curricula, soil science concepts are found in units on living things, plants, and ecosystems, from Grades 1–12. Even in Kindergarten, hands-on soil programs effectively address many skills and attitudes’ expectations in the provincial curricula. What is the use of having soil science in the curriculum, however, if the teachers responsible for student learning do not understand the key concepts? Preliminary results using a 25-item soil questionnaire show that incoming preservice teachers do have some initial understanding of soil, scoring 50% on a pretest application, when a random score would be 25%. After engaging in several hours of hands-on learning, followed by a wait time of several months, they then scored at 68%, thus gaining one third of what was lacking in their understanding. This may encourage those involved with soil education outreach to teachers. Resources for teaching hands-on soil science to elementary students will be noted, including an integrated science-language method called “Soil Science through Stories”. At the secondary level, we have the national “Soil 4 Youth” program, which integrates soil science into school programs across Canada and is supported by the Canadian Society for Soil Science. New STEM (science, technology, engineering, and mathematics) approaches to education also offer opportunities for innovative teaching of soil science to Canadian students.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.002 |
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".