The Effects of the Online versus Face-to-face (F2F) Modes of Teaching on the Academic Achievement of EFL Learners in Writing Skills Courses
Why this work is in the frame
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Bibliographic record
Abstract
English as a Foreign Language (EFL) practitioners regard writing as one of the most innovative discrete skills to teach. Many researchers examined the writing difficulties of EFL students and provided resolutions and guidance. Although the viability of the planned objectives was re-examined before any conclusions were made. However, this research aimed to investigate the effect of online and face-to-face (F2F) teaching methods on students’ academic performance in writing skills. The participants, N=44, were divided into two groups A and B and belonged to the English department in the second semester at Najran University, Najran, KSA. The controlled group A received online instruction, whereas the experimental group B received face-to-face instruction. A quasi-experimental study design was employed using the pre-test and the post-test research instruments. A test was administered to two groups to measure their levels of homogeneity at the beginning of the semester. Another test was then administered to the same groups after the first semester of teaching. In order to analyze the data, the SPSS program was used. According to the results, the F2F intervention improved student performance over the online mode. The F2F mode of participation was more comfortable and engaging for participants than the online mode. Additionally, F2F discussion produced better writing performances from the students than online communication does. Thus, despite certain benefits associated with F2F learning, further research is required in order to fully understand how F2F teaching approaches affect English learners' academic achievement in writing.
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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 | 0.004 | 0.012 |
| 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 | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it