Using anticipated learning outcomes for backward design of a molecular cell biology Course‐based Undergraduate Research Experience
Bibliographic record
Abstract
Anticipated learning outcomes (LOs) were defined and used for the backward design of a Course-based Undergraduate Research Experience (CURE). These LOs reflect the inquiry-based nature of CUREs and capture key knowledge and skills inherent to scientific practice and essential in research. The LOs were used to plan a formative and summative assessment strategy to support and evaluate student achievement. A research question was identified that aligned with the learning goals of the course, provided an opportunity for discovery and iteration, and introduced a variety of molecular, cellular, and biochemical techniques. The course is offered to students in the final year of their degree and delivered over a 12-week period with two 3-hr labs each week. These LOs, and the rigorous assessment strategy used to support them, could be adapted to different projects. Likewise, the laboratory exercises are presented as a series of modules highlighting opportunities for adaptation to a variety of schedules.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".