Balancing disciplinary and integrated learning: How exemplary <scp>STEM</scp> teachers negotiate tensions of practice
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 Integrated STEM education within North America has become a popular pedagogy; however, teachers identify challenges that arise when planning for and implementing integrated STEM education. These challenges may threaten STEM teachers' capacity to balance disciplinary and integrated learning, a core feature of effective STEM education. The purpose of this study was to investigate how exemplary STEM teachers navigate tensions of practice to balance disciplinary and integrated learning. Through an in‐depth qualitative methodology, drawing on interview and artifact data from 14 purposefully selected exemplary secondary and elementary integrated STEM teachers, this study identified tensions that teachers faced as they navigated planning for and implementing integrated STEM education: (a) curriculum content versus skills; (b) guided instruction versus inquiry and play; (c) process versus task completion; and (d) collaboration versus individual needs. In line with a Worldly Perspective (Rennie et al., 2020), balancing these tensions leads to enhanced integration.
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 | 0.008 |
| 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 | 0.001 |
| 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 it