Investigating Current Academic Stress and Test Anxiety for Undergraduate Students Experiencing the Covid-19 Pandemic of 2020
Bibliographic record
Abstract
Around the world, students of all ages are becoming increasingly stressed. Academic stress and test anxiety are two aspects of education-based stress that have been studied since the 1980s. Despite attempts to identify myriad predictors and to develop interventions that can mitigate these two educational impediments, undergraduate students continue to report high levels of stress. The current study was an opportunistic study that investigated the effect of the Coronavirus 2020 pandemic on academic stress and test anxiety among 200 undergraduate students at two primarily undergraduate institutions (PUIs) with different ethnic and SES compositions. The study also assessed the influence of the presence of a pet on reported academic stress and test anxiety levels. No difference was found between levels of academic stress or test anxiety for students evaluated before the pandemic began, when transitioning to a pandemic status, or during the pandemic with quarantine in effect. Moreover, the presence of a pet did not mediate the self-reported levels for either academic stress or test anxiety. However, academic stress and test anxiety levels were at an all-time high compared to previous cohorts assessed across multiple decades with females showing a greater vulnerability in both areas of stress. These results highlight the critical importance of identifying factors that are driving these stressors and developing effective interventions for undergraduate students to manage their stress levels.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".