A mixed-methods approach to evaluating student nurses changing answers on multiple choice exams
Bibliographic record
Abstract
Using a mixed methods approach, the purpose of this study was to examine the perceptions and patterns of nursing student’s changing answers on multiple choice exams. The sample of 86 students enrolled in an undergraduate nursing program were surveyed after their first exam of the semester. Exam response forms were examined for erasure marks to determine the answer changes on the exam grade; additionally, the relationship between self-reported school performance and frequency of changing answers, and self-reported anxiety and frequency of changing answers was examined. A qualitative exploration of two open-ended items included examining student perceptions about changing answers on unit exams. Five themes emerged from the qualitative exploration of how students felt about changing test answers: Educated gamble, confidence, anxiety learned, gut instinct and ambivalence. Three themes emerged from the analysis of the reasons students changed answers: Uncertainty, light bulb effect, and testing errors. The study’s quantitative results indicated that although the student indicated anxiety regarding changing answers, a majority did so anyway. Moreover contrary to students’ negative feelings regarding answer changing, most answer changing resulted in a modest improvement in their grade.
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 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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".