Professional Learning of K-6 Teachers in Science Through Collaborative Action Research: An Activity Theory Analysis
Bibliographic record
Abstract
Primary/elementary teachers are uniquely positioned in terms of their need for ongoing, science-focused professional development. They are usually generalists, having limited preparation for teaching science, and often do not feel prepared or comfortable in teaching science. In this case study, CHAT or cultural–historical activity theory is used as a lens to examine primary/elementary teachers’ activity system as they engaged in a teacher-driven professional development initiative. Teachers engaged in collaborative action research to change their practice, with the objective of making their science teaching more engaging and hands-on for students. A range of qualitative methods and sources such as teacher interviews and reflections, teacher-created artifacts, and researcher observational notes were adopted to gain insight into teacher learning. Outcomes report on how the teachers’ activity system changed as they participated in two cycles of collaborative action research and how the contradictions that arose in their activity system became sources of professional growth. Furthermore, this research shows how the framework of activity theory may be used to garner insight into the activity and learning of teachers as both their professional activities and the context change over time.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".