Does Instructional Quality Impact Male and Female University Students Differently? Focusing on Academic Stress, Academic Satisfaction, and Mental Health Impairment
Bibliographic record
Abstract
Gender differences in university students’ well-being and mental health are prominent concerns in higher education. During the COVID-19 pandemic, male and female students have reported specific stressors that have impacted their well-being and mental health, including difficulty concentrating, concerns about academic performance, and classroom workload. All of these stressors could be mitigated by instructional quality in courses. This study sought to better understand the associations between instructional quality and mental health impairment, i.e., poor mental health and high psychological distress, among male and female undergraduate students during the COVID-19 pandemic. We asked whether perceived instructional quality has a protective effect on students’ mental health with regard to academic stress and academic satisfaction across genders. We used longitudinal data from an ethnically diverse sample of 209 students (68% females, 82% freshmen, 50% Asian, 32% Hispanic, 13% White, 5% other) from a public university in Southern California, United States. Data were assessed during the winter and spring quarters of the academic year 2019–2020, i.e., before and after the outbreak of the COVID-19 pandemic in the US. Associations between instructional quality and students’ mental health impairment did not differ across genders. The findings indicated that perceived instructional quality at the beginning of the spring quarter 2020 was indirectly related to male and female students’ mental health impairment at the end of this quarter. This association was mediated by academic satisfaction. This finding points to a protective effect of instructional quality on students’ mental health. However, no effect was found concerning changes to mental health. Gender differences occurred in the link between academic stress and mental health impairment. Academic stress was a stronger predictor of mental health impairment for female students compared to male students. Furthermore, for female students alone, academic stress predicted changes in mental health impairment. We discuss practical implications for higher education. First, our study highlighted that instructional quality in higher education courses might lead to academic satisfaction and thereby help protect university students’ mental health. Second, higher education might consider providing additional support for (female) students to improve their stress management. We argue that improving and enhancing the academic environment are more important than reducing the burden of stressors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".