Classroom Management in Virtual Learning: A Perceptions Study with School Teachers in Qatar
Bibliographic record
Abstract
The aim of the study is to analyze the issue of virtual classroom management throughout the COVID-19 pandemic using a case study approach in a descriptive analytical method. Participants in this study are 110 teachers currently engaged in preparatory and secondary schools in different parts of Qatar. The data collection instrument used was a 4 point Likert Scale based questionnaire targeted to elicit respondents' attitudes and opinions towards virtual classroom management, challenges faced in this, and the most suitable strategies to overcome these challenges. Descriptive statistics, frequencies, and percentages were used to analyze the data. Results based on the findings show three axes: teachers’ challenges, beliefs, and attitudes. Findings indicate that teachers face difficulty in virtual classroom management and attribute the biggest challenge to their inability to check distractions in the home-based learning environment. Another significant finding is that classroom management is marginalized given the extremely limited teacher-student contact in the virtual education mode. Lastly, learner interaction is drastically stunted in virtual mode bringing the teachers to the conclusion that teaching in the physical mode is the only way to ensure classroom management.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".