Preparing teachers for professional learning: is there a future for teacher education in new teacher induction?
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
Today the quality of teachers is held to be increasingly important yet there continue to be doubts about whether teacher education programs graduate teachers ready to meet the challenges of their initial years of teaching. In some jurisdictions, other agencies (Ministries of Education, school districts, and private providers) are supplementing the work of teacher education through the introduction of new teacher induction programs which have become favoured policy initiatives to enhance new teacher transition, retention and quality. Evidence suggests that induction and mentoring increase teacher retention and ensure more effective socialisation of new teachers into the school culture. In spite of their growing popularity, the degree to which induction programs complement teacher education and/or impact new teacher professional learning remains unclear. In this paper the authors report a secondary analysis of data from an evaluation of the New Teacher Induction Program in Ontario, Canada to consider the implications for the future of teacher education by asking: What are the challenges facing new teachers? In what ways does the induction program support new teacher professional learning? What are the major implications for the future of teacher education?
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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