‘If things were simple . . .’: complexity in 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
RATIONALE, AIMS AND OBJECTIVES: In this speculative essay, we explore some of the implications and possibilities of complexity thinking for formal education. METHODS: We begin by developing the working definition that complexity research is the study of learning systems. Drawing on hard (rigorously empirical) complexity research, we critique some of the untenable assumptions and constructs that are typically used to frame those social enterprises that are attentive to adaptive, learning forms--including education, social work and health care. Looking to soft (holistic and more action-oriented) complexity research, we review some of the insights and advice that have arisen among educational researchers. This part of the discussion is framed by a brief description of an ongoing study of teachers' disciplinary knowledge of mathematics--specifically how complexity theory compels and enables us to grapple with the unique qualities of our 'object' of study, its emergence, its relationship to student understanding, and how it is implicated in such grander systems as culture and global ecology. CONCLUSIONS: We conclude by arguing that complexity theory might be properly construed as a theory of education, in contrast to the many theories that have been imported into and imposed on discussions of education over the past few centuries.
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 | 0.025 | 0.034 |
| 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 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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