EFL Professional Development: Discussion of Effective Models in Literature
Bibliographic record
Abstract
This paper explores the professional development literature in the educational setting. The different literature pieces are aligned to a framework that requires effective professional development to focus on three concepts: content, context, and process. The content focuses on the “what” question in the programs while the context aims to align the content with “where” question. The third component is the focus on the process variables that professional development should follow. This paper tries to add to the English as a Foreign Language (EFL) and English as a Second Language (ESL) fields’ literature by presenting categorized overview of relevant works. The different theories include adult learning theory, functional theory, multiple intelligences, twenty-one learning styles, the Australian Government Quality Teaching Program (AGQTP) model and model of teacher change.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.023 | 0.020 |
| Science and technology studies | 0.009 | 0.022 |
| Scholarly communication | 0.025 | 0.032 |
| Open science | 0.005 | 0.010 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".