Google Meet and Foreign Language Teaching: Anxious Already?
Bibliographic record
Abstract
The present study is quantitative research that attempts to scrutinize the drawbacks and acceptable ways of using a prominent online meeting platform, Google Meet, while determining its role in view of students’ perceptions as far as foreign language teaching and anxiety is concerned. Using online meeting programs can be considered to be an amusing and a versatile solution at first step. Yet, during the COVID-19 pandemic such platforms despite being a great remedy for the continuation of education on the one hand, were tested whether they would manage to substitute face-to-face education environment at the required level. While the previous studies prior to the pandemic could provide only limited and regional case studies carried out around the globe, those which are implemented in the wake of it will constitute a determining pattern regarding its use for utmost benefits or harm. Therefore, the real contribution or negative effects of such platforms will emerge depending on the further studies similar to the current one. Hence, in conformity with the purpose of the study, first a case specific Likert type scale was constructed utilizing inferential statistics to provide a better projection. Then, the scale was applied to 130 university students attending the English Language Literature Department of a state university to find out solutions for two fundamental research questions. As the results were analyzed through descriptive statistics, the findings of the study denoted different perspectives of students which would provide beneficial results for the upcoming interests of foreign language teaching field.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".