Learning Through a Pandemic: Youth Experiences With Remote Learning During the COVID-19 Pandemic
Bibliographic record
Abstract
The objective of this paper was to examine the school-related experiences of youth during the COVID-19 pandemic. Participants represented both clinical and community youth aged 14 to 28 who were sampled as part of a larger study. Feedback from youth attending school during the pandemic was qualitatively examined and youth who planned to attend school prior to the pandemic and did (n = 246) and youth who planned to attend but did not (n = 28) were compared quantitatively. Youth appreciated the flexibility of online learning and some also reported experiencing a lack of support from their school and the need for instructor training on how to deliver virtual classes effectively. Future studies should examine what factors influence student engagement with virtual learning, what strategies could improve supports for student in their long-term career development, and the longitudinal experiences of youth who may have chosen not to go back to school due to the pandemic. This survey was conducted in Ontario, Canada. A more diverse sample collected outside of Ontario would improve generalizability. Qualitative data were based on survey responses and not interviews. Thus we were unable to discern the reasons youth decided to attend school, or not, during the COVID-19 pandemic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".