Developing a Theory of Change: How Are Teacher Educators Preparing Pre‐ and In‐Service Teachers of Multilingual Learners?
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
ABSTRACT This research brief describes a collaborative and culturally responsive evaluation process employed in developing an evolving Theory of Change (ToC) for the Department of Education NPD grant, the English Learners' Educational Excellence Capitol Teacher Training Project (Project ELEECT). The brief outlines the framework for understanding how change is anticipated among pre‐ and in‐service English Second Language (ESL) teachers of multilingual learners (MLs) engaged with culturally sustaining ESL pedagogies. We document the various phases involved in developing data collection instruments over the first 3 years of the grant, including the use of mixed method approaches such as pre‐ and post‐surveys and participant interviews. These instruments were carefully aligned with the ToC to provide a basis for evaluating the implementation and impact of the program. The data collection and analysis processes described in this brief were integral to refining the ToC framework, which in turn guided the development of the evaluation instruments. The evolving ToC served as a foundational tool to connect program activities and outputs with intended outcomes, thereby supporting a structured evaluation of the program's implementation and its expected impact on teacher preparation practices.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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