Social Media as an Educational Tool in English: Examining the before and During-Lockdown Trends and Attitudes at Kuwait University
Bibliographic record
Abstract
This research aims at investigating the use of social media by students of Kuwait University (KU). Kuwait has been one of the first countries in the Arab world to have recognized the importance of English in the socio-economic development of its people. Accordingly, English enjoys a favorable position in the educational paradigm of Kuwait with it being a compulsory school subject alongside Arabic. With the outbreak coronavirus (COVID-19), Kuwaiti educational authorities, and many other countries, were obliged to enforce closure to all educational institutions and substitute traditional learning with online learning. A large number of tech tools came into prominence to ensure the continuance of education, so great was the desire to innovate that social media platforms came to be exploited for the purpose. Through a quantitative method, this study collects data from 400 students of English at Kuwait University to investigate the nature of change in the use of Social Media in English classrooms before and during the pandemic period. Results show that the students, both male and female, are positively disposed to its use now and in the future in learning, that is gender is not a differentiating variable in the use of SM in learning, a finding which is novel given that it diverges from previous findings in the field. Further, the language learners at Kuwait University recognize the benefits of SM in education implying that, regardless of gender, students share almost equal levels of favorable perceptions. The study importantly concludes that SM has a lot of untapped potential to offer when it comes to being used as part of the educational process. As a result, this study recommends a wider scope of using SM in universities and institutions so as to improve the process of teaching and learning.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".