The shift from class-based to online learning during COVID-19: A student and academic perception
Bibliographic record
Abstract
The COVID-19 pandemic, which was globally declared during the first quarter of the year 2020, led to the transition of teaching activities from the traditional classroom setting to online platforms. This study evaluated preparedness and perception towards online learning and its impact among pharmacy academics and students by using two self-administered questionnaires. Fifteen academics and 60 students answered the questionnaire. Participants had the required technology for online learning (academics n=14, 93%; students n=56, 93%) and believed that the transition to online learning was easy (academics n=12, 80%; students n=41, 68%). Most participants (academics n=12, 80%; students n=46, 77%) stated that online learning allowed more flexibility even though they preferred classroom-based approach. A minority of students stated that the shift to online learning during the pandemic made them feel alone (n=11, 18%), anxious (n=7, 12%) and depressed (n=9, 15%). Given the option, participants would prefer a hybrid learning approach, whereby some teaching activities are switched to online platforms.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".