Digital Academia: Exploring Students' Attitudes on Online Learning
Bibliographic record
Abstract
COVID-19 necessitated higher education institutions to adopt online learning for traditional undergraduate students. The implementation of online learning attained praise, especially from socially anxious students, yet it also enhanced hardships for others. The present study qualitatively explored undergraduate students’ attitudes toward online learning and the outcomes of the return to in-person learning on social anxiety. The sample comprised 1058 (Mage = 19.86, SD = 3.53 years) undergraduate students from Carleton University and the University of Waterloo. Results from thematic analysis revealed that most students preferred in-person learning for its numerous advantages including self-improvement, socialization, traditional university experience, and higher education quality. Moreover, a large proportion of respondents indicated traditional learning could hinder socially anxious students due to adjustments in course delivery, social connections, decreasing mental well-being, COVID-19 fears, and deficiencies in social skills. Findings will be discussed on strategies to support students using different learning modalities.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".