Curiosity-Driven, Inquiry-Based Science Projects Bridge Face-to-Face and Online Learning Formats During COVID-19: A Teachers
Bibliographic record
Abstract
The mass closure of schools as a result of the Covid-19 pandemic paralyzed many children’s education. Teachers across the globe did their best to engage students and help support their learning through online educational formats. However, teachers and parents indicated that students' struggled with these approaches. This study aims to build on successes some science teachers had using curiosity as a starting point in inquiry-based science projects that bridged face-to-face and online learning formats. This year-long qualitative, participatory action research study brings together fourteen teachers (seven elementary and seven secondary) and four university faculty using an online community of inquiry framework. This work is in its early stages. Through two cycles of planning, implementation and reflection, the community of inquiry will ultimately develop a model for best practices and resources that respond to the educational challenges faced during the pandemic and help prepare teachers for future crises. These materials will be shared with other teachers as open education resources, that are freely accessible, digital, re-mixable and revisable. This work will also contribute to theory regarding best practices for curiosity-driven, inquiry-based science education in blended learning spaces.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".