On being examined: do students and faculty agree?
Bibliographic record
Abstract
Students measure out their lives, not with coffee spoons, but with grades on examinations. But what exams mean and whether or not they are a bane or a boon is moot. Senior undergraduates (A. Perrella, J. Koenig, and H. Kwon) designed and administered a 15-item survey that explored the contrasting perceptions of both students (n = 526) and faculty members (n = 33) in a 4-yr undergraduate health sciences program. A series of statements gauged the level of agreement on a 10-point scale. Students and faculty members agreed on the value of assessing student learning with a variety of methods, finding new information to solve problems, assessing conceptual understanding and logical reasoning, having assessments with no single correct answer, and having comments on exams. Clear differences emerged between students and faculty members on specific matters: rubrics, student choice of exam format, assessing creativity, and transfer of learning to novel situations. A followup questionnaire allowed participants to clarify their interpretation of select statements, with responses from 71 students and 17 faculty members. All parties strongly agreed that exams should provide a good learning experience that would help them prepare for the future (students: 8.64 ± 1.71 and faculty members: 8.03 ± 2.34).
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.
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 | 0.024 | 0.106 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".