“Students are Once Again ‘Numbers’ Instead of Actual Human Beings”: Teacher Performance Assessment and The Governing of Curriculum and 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
This paper will examine the educational experiences of teacher candidates and the use of teacher performance assessment (edTPA) to measure their quality, competence, and impact. It will situate edTPA within the national, politically-charged debate between the defenders and reformers of teacher education who advocate for the professionalization versus deregulation of the field, respectively. Their positions converge, however, in the collective belief and reliance on testing to measure educational inputs and outputs. Even the defenders are caught in a reactive stance to show through testing data the value and relevance of teacher preparation. The paper will also investigate the perspectives on edTPA of teacher candidates at a medium-sized, public university in the US Midwest. Using a survey of candidates who completed edTPA during the 2014-15 academic year, it will highlight candidate resistance to edTPA, even though they have been disciplined and immersed in a culture of testing throughout their K-12 and university education. Their resistance foregrounds three themes: (a) time and stress; (b) outsourcing of teacher evaluation; and (c) contradictions between curriculum and assessment in teacher education. Moreover, it will mobilize Michel Foucault’s concepts of governmentality and critique to analyze the ruling logic and practices in education and the candidates’ resistance under difficult conditions.
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 | 0.004 | 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 | 0.001 | 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