Building Community in Triads Involved in Science Teacher Education: An Innovative Professional Development Model
Bibliographic record
Abstract
This article describes a pre-service and in-service science teacher joint professional development pilot project. It is intended to strengthen the community and facilitate professional growth for triad members involved in the professional development of pre-service science teachers. Through a summer workshop and follow-up monthly meetings, this project connected the clinical experiences of the pre-service teachers with the joint professional development of both the pre- and in-service teachers. A mixed-methods research design was used to investigate the impact of this project. Results indicated that this model was successful in aligning with characteristics of effective professional development derived from national standards documents and professional development literature. Additionally, through engaging pre- and in-service teachers in the co-creation of modules, which were subsequently enacted in classrooms, collaborative positioning occurred whereby the pre- and in-service teachers were found more equally sharing and co-negotiating responsibilities in the classroom. This article describes the need for this project and provides an in-depth description of each component of the project enacted, as well as additional findings supportive of its effectiveness.
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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".