Perception of E-Learning During COVID-19 Among Undergraduate Dental Students
Bibliographic record
Abstract
Objective: This survey study was carried out to assess the satisfaction of e-learning among undergraduate dental students. Materials & Methods: The questionnaire-based study was conducted in April 2020. The main target of research was undergraduate dental students of University of Health Sciences (UHS) affiliated dental colleges of Punjab. 1095 students were surveyed through online forms and data was analysed by SPSS 23. Convenient sampling method was used. Results: The results showed that the students were well aware of the current situation and almost all institutions offered online classes. Almost half of the respondents showed acceptance to E-learning. Majority of students faced difficulties in continuing their education through e-learning although a significant portion of them were in favour of home assignments. Majority of students wanted the online system to end and to cover the syllabus later. Conclusion: The dental students were well aware of the current situation and almost all institutions offered online classes. Almost half of the respondents showed acceptance to E-learning. Keywords: E-learning, COVID-19, Dental education
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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 | 0.002 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".