Soil Science Education Practices Used in Canadian Postsecondary, K-12, and Informal Settings
Bibliographic record
Abstract
Core Ideas The general public is not aware of soil's importance. Integration of soil science into K–12 curricula will help raise soil awareness. Various activities can be used to educate students and the general public. Field-based, hands-on activities are the most popular type of educational activity. This study explored practices that Canadian soil scientists use to educate postsecondary students, K–12 students, and the general public. The most commonly used type of educational activities described by survey respondents, regardless of the settings and the type of target audience, were field-based hands-on activities. The other two commonly used educational activities were lectures and laboratory activities; and they were predominantly implemented at the postsecondary institutions. Educational activities in K–12, outreach, and professional development settings were generally delivered through one-time events (e.g., workshops, school visits, field days), offering less opportunities for a greater variety of practices relative to the postsecondary settings. At postsecondary institutions, where soil science education is delivered in a more structured manner, there are more opportunities for educators to implement a range of educational practices (e.g., lectures, laboratory activities, games, case studies, quizzes). The learning objectives of the field-based hands-on activities and lectures were to describe specific soil properties or to describe and classify soils, whereas for laboratory activities, the learning objectives focused more on the application of those concepts. The insights offered by this study on educational practices used by Canadian soil scientists to encourage more students to study soil science and raise awareness about the importance of soil are valuable teaching resources for both new and seasoned educators within Canada and abroad.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".