A qualitative analysis to identify the elements that support department level change in the life sciences: The PULSE Vision & Change Recognition Program
Bibliographic record
Abstract
The 2011 report, Vision and Change in Undergraduate Biology Education: A Call to Action, provided the impetus to mobilize the undergraduate life sciences education community to affect change in order to enhance the educational experiences of life sciences majors. The work of the appointed Partnership for Undergraduate Life Sciences Education (PULSE) Vision and Change (V&C) Leadership Fellows has focused on the development of programs and resources to support departmental change. In this report, we present a qualitative assessment of several documents generated from the PULSE V&C Leadership Fellow Recognition Team. The Recognition Team developed two initiatives to provide departments with feedback on their change process. The first initiative, the validated PULSE V&C Rubrics, enables departments to collaboratively self-assess their progress in enacting change. The second initiative, the PULSE Recognition Program, involves completion of the aforementioned Rubrics and a site-visit by two Recognition Team members to provide external insights and suggestions to foster a department's change process. Eight departments participated in the Recognition Program in 2014. An evaluation of the documents yielded from the Recognition Program review of seven of the eight departments and a comparison of Rubric scores from before and three years following the site-visits uncovered several common elements required for successful department level change. These elements include an institutional culture that values and supports excellence in teaching and learning with resources and infrastructure, a departmental emphasis on program and course level assessment, and, most importantly, a departmental champion who actively supports endeavors that enhance teaching excellence.
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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 | 0.027 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.005 |
| 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".