Evolving attitudes toward online education in Peruvian university students: A quantitative approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: The COVID-19 pandemic has accelerated universities' adaptation process toward online education, and it is necessary to know the students' attitudes toward this online education. Objective: To describe the evolution of the attitude toward online education among social science students at a public university in Peru in the academic year 2020, in the context of the COVID-19 pandemic. Methods: The study uses a quantitative approach, a descriptive level, a non-experimental design, and a longitudinal trend. The sample consisted of 1063 students at the beginning of the class period, 908 during the classes, and 1026 at the end of the class period. The questionnaire for data collection was the Attitude scale toward online education for university students during the COVID-19 pandemic. The data was collected using Google Forms. Results: -value <0.05). Conclusion: The evolution of the attitude towards online education in the sample had a non-significant positive trend. In the initial and process stages, a weak negative attitude prevailed due to the institution's inexperience and poor digital infrastructure; in the end, the attitude became weak and positive due to the adaptation and need for online education.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it