Using Brief Teacher Interviews to Assess the Extent of Inquiry in Classrooms
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
Inquiry-based instruction is common to nearly every model of gifted education. Six teachers of 14 secondary classes were briefly interviewed about their teaching and learning methods, use of inquiry-based strategies, classroom descriptions, a typical day, student expectations, and inquiry-instruction outcomes. A criterion-referenced checklist of 25 qualities of inquiry classrooms was used in a protocol analysis of the transcribed interviews. The classes were previously categorized as Most, Middle, and Least Inquiry with a modification of Llewellyn’s simplified rubric for inquiry teaching complemented by teacher and student interviews and a teacher questionnaire. Extent of inquiry was well identified using only the teacher interviews and checklist. Teachers of Most Inquiry classrooms mentioned 21 or 25 of the 25 inquiry items. Middle Inquiry teachers mentioned 17 and 18 items. Least Inquiry teachers noted 6 and 9. Brief teacher interviews with a relatively straightforward coding system can assess the extent of classroom inquiry students experience.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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