The state of introductory biology following 16 years of pedagogical reform since <i>Vision and Change for Biology Undergraduate Education</i>
Bibliographic record
Abstract
ABSTRACT Nearly two decades ago, over 500 biology educators from across North America contributed to the creation of the Vision and Change for Undergraduate Biology Education: A Call to Action report, with recommendations for the development of a deep understanding of core biological ideas and practices in undergraduate students and the integration of evidence-based practices into biology classrooms. Introductory biology courses provide a conceptual foundation in biology while also developing skills essential to both the transition from high school to university and general scientific literacy. Thus, alignment of introductory biology classrooms to Vision and Change is important for fostering biological and scientific literacy in all students, even those whose only exposure to biology is introductory courses. Following the dissemination of Vision and Change were numerous frameworks, resources, and instruments that support the implementation of these recommendations in undergraduate biology programs. Here, we synthesize the tools, evidence-based practices, and structural transformations that have been used to align introductory biology courses to Vision and Change with the aim of providing both an overview of the current landscape of introductory biology education and a starting point for institutions, who, like us, are evaluating their progress toward alignment with Vision and Change .
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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 | 0.016 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".