Exploring the contributions of self-efficacy and test anxiety to gender differences in assessments
Bibliographic record
Abstract
The observed performance difference between women and men on assessments in physics-the "gender gap"-is a significant and persistent inequity which has broad implications for the participation of women in physics. Research also shows that gender-based inequities extend to affective measures, such as self-efficacy. In this exploratory study, we report on gender disparities in self-efficacy and test anxiety and their relationship to assessment scores in our active-learning introductory physics course. Overall, gender-based differences in favour of men are observed in all our measures, with women having lower scores on measures associated with success (self-efficacy and assessment scores) and a higher score on a possibly detrimental affective factor (test anxiety). Using a multiple regression model-selection process to explore which measures may explain end-ofcourse Force Concept Inventory (FCI) and final exam scores, we find that the best fitting models include FCI pretest and self-efficacy as predictors, but do not include test anxiety.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".