Perspectives on Covid19 Safety Protocols among Non-Native English Speaking Teachers and Students
Bibliographic record
Abstract
This study sought to elicit global perspectives on Covid19 safety protocols when communicated in English to teachers and students of other languages. Adherence through comprehension of safety protocols by non-native English speaking students and teachers of higher education institutions (HEIs) is central to this investigation. Covid19 pandemic resulted in an unprecedented impact on the education sector. Since the well-being of students and teachers against any form of risk is a priority, safety protocols should be communicated effectively using comprehensible language. However, there is a valid observation on the lack of inquiries on how HEIs communicate, facilitate and implement those safety protocols to ensure adherence. Hence, the quantitative research approach was employed to address the problem presented. Primary data were collected through a structured questionnaire from 450 global student and teacher respondents. The respondents were chosen through a referral sampling technique, also known as a snowball, they joined the online survey, which took place for a month. The descriptive correlational research design was used, and the data were treated using descriptive and inferential statistical tools. Results revealed that out of eighteen components of safety protocols for educational institutions, wearing face masks is clearly understood and was noted as the most prevalently observed. The high level of knowledge and awareness on safety protocols among respondents is linked to massive information dissemination. The step-wise regression model identified only two significant predictors for a conforming perspective: wearing a face mask and physical distancing. The rest of the pre-identified protocols do not significantly affect or influence the perspectives. These results suggest that the respondents adhere to all protocols and agree that wearing face masks is their foremost concern. A negative perspective is indicated toward those who resist following the Covid19 protocols, suggesting that the respondents are aware of the importance of safety protocols in reducing positive cases if religiously observed. This study concludes that protocols for any crisis should be maintained and institutionalised because they serve their purpose better with proper implementation. Furthermore, English as a medium for communicating those health and safety is not a barrier and did not interfere with the respondents’ understanding and adherence. Therefore, the language of the protocols is within the grasp of the respondents, which is attributed to the success of its implementation.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".