Cultural Differences between University Students in Online Learning Quality and Psychological Profile during COVID-19
Bibliographic record
Abstract
During the COVID-19 pandemic, educational systems had to adapt to the social and health situation immediately. This led to the appearance of the asynchronous teaching model. Throughout the pandemic at an educational level, we can distinguish three phases, eminently online, hybrid, and face-to-face. However, the perception of educational quality in these three educational moments, considering the psychometric profile and cultural differences comparing Ibero-American countries, has not been studied. The study aims to analyze the psychological profile, and perception of quality in the teaching–learning processes at the university stage, during the three processes of educational transition during COVID-19: online, hybrid, and face-to-face. Thus, 1093 university students from Ibero-American countries were studied. Through a questionnaire, demographic, academic, and psychological variables were analyzed during three phases of the pandemic. Data suggest that Latin American students had higher levels of trait anxiety and stress perception, as well as higher levels of loneliness, during the online teaching phase (lockdown), but higher grades and higher levels of motivation compared to Europeans. Indeed, Latin Americans showed greater convenience, and preference for online learning methods. However, during the face-to-face teaching phase, European students presented greater motivation and grades, showing a greater preference for this method of learning than Latin American students. Factors such as resilience, a more unfavorable and pronounced pandemic evolution, and greater social inequities, may explain the present results. Furthermore, the present study suggests that despite the effect of the pandemic on mental health, online education is postulated as an effective teaching–learning alternative. Indeed, online teaching models have come to stay, not as a substitute, but as a tool, an essential focus of attention on these models should be conducted in European countries, while the governments of Latin American countries ensure that the infrastructures and resources are equitable to be able to correctly implement this teaching model.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".