The positive benefits from the observation that test duration is mostly uncorrelated with student grades
Bibliographic record
Abstract
New and experienced instructors strugglewith setting tests and exams at a suitable level ofdifficulty, with appropriate questions for the allocatedtime. Tests that are too short might be thought of as givingstudents undue advantage. Exams that are too long leavestudents feeling pressured and anxious, and without timefor careful thought to display mastery of the conceptsbeing tested.Unlimited time tests are a way to eliminate the effect ofanxiety. In this paper we start by reviewing existing workon this topic and explain the data collected in our context.We confirm the literature findings that grades are notinflated by longer durations – if anything, we show thereis a slight decrease with longer durations.Practical applications exist for universities that arefacing pressure to shorten exam durations, due toscheduling limitations as class sizes grow. Mainly though,these results will set the mind of new instructors at ease,and validate suspicions of veteran instructors: tests mustbe of short-enough duration to alleviate time-pressure andanxiety. Building in excess time is required to fairly assesslearning outcomes. Students have a higher level ofsatisfaction knowing they can display their capabilityfairly, and this comes without undue advantage.
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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 | 0.013 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".