Increased Scaffolding and Inquiry in an Introductory Biology Lab Enhance Experimental Design Skills and Sense of Scientific Ability
Bibliographic record
Abstract
We present a model for the process of redesigning the laboratory curriculum in Introductory Organismal Biology to increase opportunities for meaningful inquiry and increase student recognition of their scientific skill development. We created scaffolded modules and assignments to allow students to build and practice key skills in experimental design, data analysis, and scientific writing. Using the Tool for Interrelated Experimental Design, we showed significantly higher gains in experimental design scores in the redesigned course and a more consistent pattern of gains across a range of initial student scores compared with the original format. Students who completed the redesigned course rated themselves significantly higher in experimental design, data collection, and data analysis skills compared with students in the original format. Scores on the Laboratory Course Activity Survey were high for both formats and did not significantly differ. However, on written course evaluations, students in the redesigned course were more likely to report that they engaged in "real science" and their "own experiments." They also had increased recognition of their specific analytical and writing skill development. Our results demonstrate that intentional, scaffolded instruction using inquiry modules can increase experimental design skills and sense of scientific ability in an introductory biology course.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".