The association of self-efficacy, anxiety sensitivity, and perfectionism with statistics and math anxiety
Bibliographic record
Abstract
Statistics and math anxiety are pervasive problems for post-secondary students. We hypothesized that self-efficacy would be negatively related to math/statistics anxiety, and that anxiety sensitivity and perfectionism would be positively related to math/statistics anxiety, even when controlling for gender, university program, and education level. Method: Graduate and undergraduate students (N = 447, after exclusions) completed an online self-report questionnaire, including an abbreviated version of the Statistics Anxiety Rating Scale (STARS), math anxiety, self-efficacy, anxiety sensitivity, perfectionism, and demographics. Results: Exploratory factor analysis supported a six-factor structure for statistics anxiety. Self-efficacy was negatively associated with math/statistics anxiety, whereas anxiety sensitivity and perfectionism were positively associated with math/statistics anxiety. Relationships ranged from small-to-moderate, and most relationships persisted after adding covariates. Discussion: Our study suggests the feasibility of a short-form version of the STARS. Moreover, it provides important information on how personality is associated with domain-specific anxiety that can impede statistics education.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| 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".