Improving Access to Hands-On STEM Education using a Mobile Laboratory
Bibliographic record
Abstract
Schools often have limited resources to devote to science education, which can impact student interest in and preparedness for careers in STEM. Seattle Children’s Research Institute created the Science Adventure Lab, a mo¬bile laboratory program, to support and enrich science education at low-resource schools and stimulate interest in science and pursuing a career in STEM. The mobile laboratory provides students with the unique opportunity to fully immerse themselves in authentic, hands-on science learning with scientists. This limits the burden on school resources and reduces disruptions to daily schedules since students do not leave their schools. These positive science experiences at an early age allow students to learn important science concepts and have the potential to significantly impact students’ interest in pursuing STEM careers. In this report we describe our mobile laboratory, operating model, and curriculum, as well as the positive impacts, strengths, and challenges of the approach as a resource for other groups who may wish to use a similar strategy for STEM education outreach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".