Connecting Beyond the Classroom: Use of Viber as a Support Tool for Enhancing Essay Writing Skills and Online Language Learning Engagement among Students
Bibliographic record
Abstract
This research study discovered students' online English learning engagement through the use of Viber as a support tool in essay writing by the first-year English majors at a university level with a total of ten participants, five women and five men. It employed the Quasi-experimental design, and pre-and post-test design was used to measure the language learning engagement of the first-year students at a tertiary level. Data were analyzed through frequency count and percentage with the help of SPSS. The result shows that student engagement and level of attitude in language class before the utilization of VST is very low. This means they are very upset in the language class, especially in writing. However, after using VST, their attitude towards writing changes, which means that Viber positively impacts their attitude towards writing. It is also found that they are proficient and well-immersed in writing. Based on the pre-test and post-test scores, they may use Viber as a Support tool or opt to use traditional support because this study revealed that their performance in writing remains good for the two interventions. However, teachers may consider the view of students on using Viber, for this gives them greater efficiency in writing because it makes them focus. Teachers may consider incorporating Viber in their teaching methods to enhance their students' writing skills and overall learning experience.
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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 | 0.011 | 0.011 |
| 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 | 0.000 |
| Open science | 0.000 | 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".