The Influence of Hands-On Experimentation and Inquiry-Based Learning in Elementary Science and Technology (S&T) Education
Bibliographic record
Abstract
To investigate how elementary science and technology (S&T) education experiences with hands-on experimentation and inquiry-based learning impact pre-service teachers’ attitudes and confidence to teach S&T, we used a cross-sectional survey. Our participants were twenty-seven pre-service teachers enrolled in an Ontario elementary S&T teacher education methods course. Those who were taught S&T through hands-on experimentation considered themselves more S&T literate and were statistically more confident to read, understand, and critically evaluate common S&T media reports; they were also more confident to teach S&T through hands-on experimentation and inquiry-based learning. In almost all cases, participants valued learning S&T by doing S&T (i.e. actively participating/interacting), which influenced their confidence, interest, and desire to embrace hands-on experimentation as future elementary teachers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".