Assessing the Multi-faceted Nature of Test Anxiety Among Secondary School Students: An English Version of the German Test Anxiety Questionnaire: PAF-E
Bibliographic record
Abstract
The current study concerns the validation of an English version of the German Test Anxiety Inventory, namely the PAF-E. This questionnaire is a multi-faceted measure of test anxiety designed to detect normative test anxiety levels and in consequence meet the need of consultancy. Construct and criterion validity of (PAF-E) were examined with a sample of 96 secondary students (Mage = 12.8, SD = 0.67; 55% girls) from an international school in Berlin (Germany) and 399 secondary students (Mage = 13.4, SD = 0.80; 56% girls) from Montréal (Canada). Both samples completed the PAF-E and related constructs, such as school-related self-efficacy, inhibitory test anxiety, achievement motivation, and the Big Five. Exploratory and confirmatory factor analyses confirmed the four-factor-structure (worry, emotionality, interfering thoughts, lack of confidence) of the original German Test Anxiety Inventory (PAF). Each subscale consists of five items with a total of 20 questions. Cronbach's alpha, ranging from.71 to.82 among Germans and.77 to.87 among Canadians as well as the re-test reliability (from.80 to.85 among Canadians) were sufficient. The differential patterns of correlations between other constructs and the indices of test anxiety indicate good construct validity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".