Test‐enhanced learning and its effect on comprehension and diagnostic accuracy
Bibliographic record
Abstract
CONTEXT: In health professions education, tests have traditionally been used to assess the skills and knowledge of learners. More recently, research in psychology and education has shown that tests can also be used to enhance student memory; a phenomenon called the 'testing effect'. Much of the research in this domain has focused on enhancing rote memory of simple facts, and not on the deeper comprehension and application of complex theoretical knowledge necessary to diagnose and manage patients. The purpose of this study was to examine the effects of testing on students' comprehension of the basic science mechanisms and diagnostic accuracy. METHODS: Undergraduate dental and dental hygiene students (n = 112) were taught the radiographic features and pathophysiology underlying four intrabony abnormalities. Participants were divided into two groups: the test-enhanced (TE) condition and the study (ST) condition. Following the learning phase, the TE condition group completed an interventional test that tested the basic science mechanisms and the ST condition group was given additional study passages without being tested. Participants in both groups then completed a diagnostic test and a memory test immediately after the learning phase and 1 week later. RESULTS: A main effect of testing condition was found. The participants in the TE condition group outperformed those in the ST condition group on immediate and delayed testing. Unlike the diagnostic test, the memory test showed no difference between the groups. CONCLUSION: The inclusion of the basic science test appears to have improved the students' understanding of the underlying disease mechanisms learned and also improved their performance on a test of diagnostic accuracy.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".