Stages of teaching expertise from routine to adaptive: A model for advancing teaching effectiveness
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
This cross-sectional study evaluated the implementation of a professional practice standard for teaching over four years in a top-performing Canadian education system with 62 school districts and approximately 35,000 teachers in the system. Using a convergent mixed methods research design, quantitative data were generated from online surveys with 5536 teachers and qualitative data were gathered through focus group interviews with teachers ( n = 193). Results from the study have been used to inform an update to the Teaching Effectiveness Framework (Friesen, 2009) and provide insights into a model for advancing teaching effectiveness. Conceptual stages were developed to illustrate teacher progression from routine to adaptive expertise, measured on a four-point scale. The scale is introduced as a resource to support the integration of policy initiatives into actionable practices and professional learning. Results underscore the value of integrating research literature with teacher and student perspectives to conceptualize and advance teaching effectiveness principles. • Results provide a model for advancing teaching effectiveness. • Framework charts conceptual stages from routine to adaptive expertise. • Study provides a system-oriented perspective for the conceptualization of teaching effectiveness.
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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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