Grading Scheme, Test Difficulty, and the Immediate Feedback Assessment Technique
Bibliographic record
Abstract
The authors examined how the grading scheme affects learning and students' reactions to the Immediate Feedback Assessment Technique (IFAT), an answer form providing immediate feedback on multiple-choice questions. Undergraduate students (N = 141) took a general-knowledge multiple-choice test of low, medium, or high difficulty. They used the IFAT with a number-correct (NC), partial-credit (PC), or correction-for-guessing (CG) grading scheme. After 1 week, they retook the test using a traditional response form with an NC scheme. When the authors used the NC or PC scheme for Test 1, the number of correct answers increased by more than 30% on Test 2. However, the increase was only about half as large with the CG scheme, suggesting that it interferes with the IFAT's learning benefits. Responses to questionnaire items provided no strong clues regarding the origin of this difference. Participants in all treatment conditions had positive attitudes toward the IFAT.
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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 | 0.014 | 0.128 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".