Seeding long-term, sustainable change in teacher preparation programs: the case of PhysTEC
Bibliographic record
Abstract
BACKGROUND: The continuation of teacher preparation activities after a 3-year Physics Teacher Education Coalition (PhysTEC) grant is used as a case study to examine multi-faceted aspects of sustainable change in higher education. Since teacher preparation is outside typical physics departmental activities, success is highly dependent on finding a department and institution who values this cause. Throughout the history of providing grants, PhysTEC has identified ten components of successful sites that they consider during the selection process. In this paper, we retrospectively analyze characteristics of six comprehensive PhysTEC sites, to see how department histories, values, and activities affect long-term sustainability as sites moved from grant funding to matched institutional funding and beyond. RESULTS: The most important components required to sustain these programs were (1) institutional commitment-both financial support as well as intellectual and cultural support for potential teachers-(2) champion, a respected change agent at the university who ensures program success through advocacy and support, and (3) activities that enhance not only the production of teachers but also the undergraduate education activities of the department. Of the six PhysTEC sites, three sites were able to institutionalize the majority of PhysTEC activities into departmental routine. These three sites have departmental leadership and administrators who valued and invested in physics teacher preparation. At these sites, PhysTEC symbiotically supported typical departmental activities including increasing majors, improving courses, and involving undergraduates to support teaching. Two sites were sustaining activities at the time of study but attitudes toward teaching as a profession were mixed so continued sustainability is precarious and reliant on external funding. One site discontinued the majority of PhysTEC activities because of a lack of alignment with a different physics teacher initiative on campus. CONCLUSIONS: Because physics teacher preparation is not often prioritized as a part of undergraduate departmental activities, success emerges when departmental and institutional value systems align with this goal. PhysTEC funding is not enough to create this culture; it must exist prior to funding. Sustaining PhysTEC activities is easier when they are seen as enhancing the undergraduate experience as a whole. The PhysTEC grant helped bring physics teacher preparation to the forefront, and a well-respected champion in a leadership position can help set this tone and advance departmental activities accordingly. This study has implications for sustaining reforms of typically undervalued activities in higher education or secondary teacher preparation programs in any discipline.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".