Bibliographic record
Abstract
STEM education is an approach to teaching and learning that integrates the content and skills of science, technology, engineering, and mathematics; which promotes critical thinking, higher-order thinking, and problem solving (NSTA, 2020). This research was conducted with the purpose of identifying the influence of this PD on improving teacher librarians’ knowledge, skills, and abilities to support STEM education efforts in their schools. This study utilized a pre/post-test quasi- experimental design to determine the influence of the PD on teacher librarians’ knowledge, skills, and abilities to support STEM education (Creswell, 2013). The pre-test data confirms previous research, that there is a significant gap in the knowledge, skills, and abilities of school librarians when it comes to supporting STEM education efforts in their schools. Additionally, school librarians aren’t being offered many professional growth opportunities to further their knowledge in this area. Post-test data provides information on the influence that the PD had on the participants' knowledge, skills, and perceived abilities in supporting STEM education.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".