Complexity Science and Cohorts in Teacher Education
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
In this paper we examine the nature of our self-study practices in an elementary teacher education cohort called CITE (Community and Inquiry in Teacher Education). We argue that self-study is not only important to our continued work in CITE but also a critical feature of professional practice in general. Two general questions frame our analysis: (1) What is significant about cohorts in teacher education? (2) How might complexity science inform our understanding of cohorts in particular and of teacher education programs in general? We argue in the paper that the use of a cohort-type structure in a teacher education program provided us with flexibility and potential for improvisation to address the perennial problems of program fragmentation. To better understand our own teaching and learning practices in this community setting, we sought an analytic framework that emphasized the importance of the learning potential of the collective as opposed to just the learning potential of the individual. We argue that complexity science, with its ecological emphasis on learning systems, is such an analytical framework. We generate six propositions about the role and value of cohorts in teacher education that arise from self-study of our own practice.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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