Development of the Biological Experimental Design Concept Inventory (BEDCI)
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
Interest in student conception of experimentation inspired the development of a fully validated 14-question inventory on experimental design in biology (BEDCI) by following established best practices in concept inventory (CI) design. This CI can be used to diagnose specific examples of non-expert-like thinking in students and to evaluate the success of teaching strategies that target conceptual changes. We used BEDCI to diagnose non-expert-like student thinking in experimental design at the pre- and posttest stage in five courses (total n = 580 students) at a large research university in western Canada. Calculated difficulty and discrimination metrics indicated that BEDCI questions are able to effectively capture learning changes at the undergraduate level. A high correlation (r = 0.84) between responses by students in similar courses and at the same stage of their academic career, also suggests that the test is reliable. Students showed significant positive learning changes by the posttest stage, but some non-expert-like responses were widespread and persistent. BEDCI is a reliable and valid diagnostic tool that can be used in a variety of life sciences disciplines.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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