Developing Scientific Writing Skills in Upper Level Biochemistry Students through Extensive Practice and Feedback
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
Effective communication is one of the most marketable and transferable skills a graduate can have. Unfortunately, science programs rarely develop effective writing skills due to the time‐consuming nature of evaluating these skills. Here, we try to adapt tools from specifications grading to simplify marking and maximize student success in a third‐year biochemistry lab techniques course. We provided feedback to students on whether or not they were writing to the expected level on short lab reports so that they could implement it in a cumulative lab report. Students struggled to accept the all or none nature of specifications grading and did better with a writing workshop and one‐on‐one feedback. Overall, writing improved the most in sections where students received the most practice. We observed moderate success in improving writing skills in class size of 35, which is larger than most previous exercises of this nature. Support or Funding Information Thank you to Kyle McDade and Ryan Toth for their help in grading.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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