Integrated School-Based Teacher Education: From Apprenticeship to a Complex Learning System
Bibliographic record
Abstract
This article differentiates approaches to school-based teacher education. It contrasts the pervasive apprenticeship model, to a "naturally integrated" school-based teacher education program that we describe as a complex learning system. Rather than view teacher education as fragmented by separating educational theory (physically based on a university campus) and teaching practice (based in a school and resembling an apprenticeship), we favor an approach where all coursework is integrated with practice in a host school while maintaining close connections to the university. The latter model highlights learning as contextualized in school, focussed on the whole school, yet also informed by progressive educational thought. All participants in the school environment (not just university students) are at once both learners and teachers. Just as university-based aspects of teacher education suffer from a lack of practical relevance, we anticipate that any model of school-based teacher education will have to address the effects of context overwhelming theoretical learning, philosophical understandings, and generalization to other contexts. We claim that a complex learning system model is better able to mitigate these contextual effects. We propose an approach to address this issue through both "reduction" and "complexity".
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.
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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".