Science, technology, engineering, & mathematics, curricular integration, and the story form
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract As science, technology, engineering, and mathematics (STEM) education continues to increase in popularity, it becomes imperative that generalist preservice teachers (PT) have both strong concept knowledge and pedagogical skills to properly support its integration. However, generalist PTs do not have enough knowledge or skills possessed by those in STEM's respective disciplines, impacting their perceptions of how the framework is disseminated. The finger, then, is pointed at PT education to provide the necessary education and training that would allow for high‐quality STEM education beginning at the elementary level. One novel approach to mitigate this problem is to introduce Kieran Egan's education theory on imagination (mythic understanding) and the theory of integrated curricula to PT. Throughout this philosophical inquiry, we explore integrated curriculum models, imagination (mythic understanding) and storytelling, illustrating how they may appear in a STEM‐oriented lesson within an elementary science PT course, and attend to the need for approachable, evidence‐based interventions regarding generalist PT STEM education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it