Novice‐Service Language Teacher Development: Bridging the Gap Between Preservice and In‐Service Education and Development
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
One reason for teacher attrition is that a gap exists between pre‐service teacher preparation and in‐service teacher development, in that most novice teachers suddenly have no further contact with their teacher educators, and from the very first day on the job, must face the same challenges as their more experienced colleagues, often without much guidance from the new school/institution. These challenges include lesson planning, lesson delivery, classroom management, and identity development. In this introductory paper to introduce the special issue on Novice Professionals in TESOL , I also outline practical suggestions that can help bridge the gap between pre‐service and in‐service education, with the idea that novice teachers can experience the transition from teacher preparation to the first years of teaching, less like “hazing” and more like professional development. I call this bridging period novice‐service language teacher development .
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 | 0.000 |
| 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