Investigating the Longer-Term Impact of a Professional Development Program: A Five-Year Follow-Up Qualitative Study
Bibliographic record
Abstract
Do changes in perspectives on teaching and learning that teachers experience in a professional development (PD) program persist over time? How might they evolve? In this article the author first summarizes the results of her original two-year qualitative study of Quebec CEGEP (college) teachers’ perspectives on teaching and learning within a PD program. She then describes the results of a follow-up qualitative study that she conducted with the same teachers five years later. Teacher interviews were coded using the constant comparative method (Maykut & Morehouse, 1994). Three major conceptual themes emerged: teachers reported engaging (outside of teaching), innovating (within teaching) and evolving (professionally and personally). Threads that appeared in the original study re-emerged in the follow-up data. Monitoring the longer-term impact of PD programs can shed valuable light on the on-going process of teacher development.
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How this classification was reachedexpand
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 | 0.013 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".