The Influence of Coronavirus Diseases 2019 (COVID-19) Pandemic and the Quarantine Practices on University Students' Beliefs About the Online Learning Experience in Jordan
Bibliographic record
Abstract
Coronavirus Disease 2019 (COVID-19) is a contagious disease that affects the respiratory system. In addition to the severe effects of the disease on health, the pandemic caused a negative impact on basic needs and services, employment, education, and economy worldwide. In Jordan, the whole country locked down, and quarantine was enforced by the military forces, which successfully controlled the spread of the disease. This research aims to study the influence of the COVID-19 pandemic and its associated quarantine on university students' beliefs about online learning practice in Jordan. An online descriptive survey involved questions that covered students' demographic information, student's basic and advanced knowledge about COVID-19, students' online learning experience during the quarantine, and finally students' views on the enforced quarantine practice in Jordan. Results showed that students have a good knowledge (>50%) about the COVID-19 basic information and a moderate knowledge (<50%) regarding COVID-19 advanced information. In general, students were pessimistic about the future of COVID-19 both locally and worldwide. Although some students acknowledged that they learned new skills in the fields of electronics, informatics, and computer software during the pandemic, most of them were unsatisfied about the quality and quantity of the given material, online exams, and the evaluation processes. Unfortunately, most of the students faced internet technical problems or challenges to electronic accessibility. The majority of the participants (>90%) supported the military-enforced quarantine implemented in the country despite the hard time the students had during the quarantine. We conclude that university students were able to protect themselves from COVID-19 through their good knowledge about the infectious disease and their commitment to follow the rules imposed by the Government of Jordan. Nevertheless, the challenges caused by the pandemic and its associated quarantine, combined with the sudden unprecedented online experience, negatively impacted students' thoughts and beliefs about the online learning experience during the quarantine. Further studies need to be performed in this context. We hope our results will help decision-makers better understand the students' attitudes and motivation toward online learning and how this will affect their future plans and decisions.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".