Review of <i>Teaching Children Science: Hands-on Nature Study in North America, 1890-1930</i> by Sally Kohlstedt
Bibliographic record
Abstract
Many scientists and educators agree that the goal of science education is to prepare students "to know, use and interpret scientific explanations of the natural world," as cited in the National Research Council publication, Taking Science to School: Learning and Teaching Science in Grades K-8 (DuschI et al. 2007). Yet, many science instructors of K-12 and post-secondary students often rely on teacher-telling modes of pedagogy and neglect to engage their students in natural inquiry and scientific study that model the research methods used by scientists. As a result, many young people are not aware of how scientists make discoveries about the natural world. Moreover, some critics argue that our children are so out of touch with the natural world that they prefer to be "plugged in" to electronic games rather than discovering the outdoors, a phenomenon coined as "nature deficit disorder" by Louv (2006). In response to the realization that our students need more meaningful science instruction, scientists and educators actively proposed reforms and have been studying the effects of various instructional and assessment strategies. As I read about the nature study movement in the late 1800s and early 1900s, I realized that for the past 100 years, North American educators have been passionate about the same things--trying. To find ways to improve science instruction by making It more relevant and interesting to students. We know that when people are passionate about topics, they are more motivated to learn, and this is exactly the sentiment that educators drew upon at the start of the nature study movement in the United States and Canada.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".