An Implicit Analysis of the Prevalence of Test Anxiety among Preservice Teachers
Bibliographic record
Abstract
This unique study, which was carried out in an area that seemed under researched, collected data from 100 female preservice teachers in a college of education in Ghana on the actual sources and protest-march of test anxiety among trainee teachers, considering the peculiar position teachers occupy in the learning chain. Data were collected by using an adapted version of the Test Anxiety Inventory (TAI) developed by Spielberger and Vagg. A key finding is that, external agents such as future job security tend to be the major source of trainees’ test anxiety, which is at variance with what literature seems to suggest that students who experience test anxiety tend to be the type of people who put a lot of pressure on themselves to perform well. The findings seem to suggest that, tests in themselves do not stimulate anxiety but the premium and how high the stakes are for the test, tend to kindle anxious moments for preservice teachers.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".