INFLUENCE OF GRAMMAR TRANSLATION METHOD (GTM) ON LIBYAN STUDENTS’ ENGLISH PERFORMANCE IN COMMUNICATIVE SITUATIONS
Bibliographic record
Abstract
In the past and present, the Libyan government has offered free schooling at all levels in public education. Till the early past, more specifically till 2014, the Libyan government used to send honored students at high school levels to pursue their university studies overseas, honored students at university levels to pursue their masters’ degrees overseas, and holders of masters’ degrees to pursue their doctorates’ degrees overseas, specifically the United States, Canada, the United Kingdom, Australia, and other countries all over the world. English was taught as a foreign language at school from the 5th grade, but it is has been taught from 1st grade since 2016. Although all these efforts conducted by the Libyan government, the use of Libyan students’ English performance in communicative situations has been unsatisfactory. Many studies and research regarding Libyan contexts reveal that the main reason for this dissatisfaction is attributed to the method of teaching English used at Libyan schools. Thus, this study endeavored to find out the influence of this method on Libyan students’ English performance when communicating in English in reality. This study follows qualitative research method, basing on secondary recourses represented in reviewing of literature and primary recourses represented in interviewing ten Libyan teachers of English. The study has obtained several findings, the most important of which is that GTM does not help Libyan students use English communicatively in reality; rather, it helps them know about English as a class subject. The study presents some recommendations based on the findings obtained. The most important of which is that teachers of English should use other appropriate methods of teaching that help Libyan students use English in communicative situations, and grammar should be taught in context.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".