The Theory and Practice Divide in Relation to Teacher Professional Development
Bibliographic record
Abstract
The 21st century is a time of rapid change and increasing accountability within education contexts and teacher professional development (TPD) is frequently perceived to be crucial in instituting reforms. This chapter explores the divide between theories of effective TPD and the realities of practice within educational contexts. Two case studies, one from Australia and the other from Canada are presented to illustrate the positives and negatives inherent within professional development approaches in these contexts. A number of key dimensions are identified, which when coalesced inform the establishment and sustainability of effective programmes. Online technologies present innovative ways to overcome the impediments to effective professional development. Online communities of practice utilising socialnetworking technologies provide new opportunities for initiating “webs of enhanced practice’ (Scott, 2009), where individuals around the globe can engage in collegial collaborations that enhance the passion of teaching.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.035 |
| Scholarly communication | 0.018 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".