A Large, First-Year, Introductory, Multi-Sectional Biological Concepts of Health Course Designed to Develop Skills and Enhance Deeper Learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Large first-year biology classes, with their heavy emphasis on factual content, contribute to low student engagement and misrepresent the dynamic, interdisciplinary nature of biological science. We sought to redesign a course to deliver fundamental biology curriculum through the study of health, promote skills development, and encourage a deeper level of learning for a large, multi-section first-year class. We describe the Biological Concepts of Health course designed to encourage higher-order learning and teach oral communication and independent learning skills to large numbers of first-year students. We used the Blooming Biology Tool to determine the cognitive skills level assessed in the newly developed course and the courses it replaced. This evidence-based approach demonstrated that our new course design achieved the goal of encouraging a deeper level of cognition, and further, successfully introduced both oral communication and independent learning skills in large first-year classes.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it