Examining the Vocabulary Knowledge and Idiomatic Structures of EFL Learners in a Culturally - Oriented Learning Context
Bibliographic record
Abstract
This study looked into how cultural background knowledge affected the vocabulary and idiomatic phrases of Saudi pre-intermediate EFL students. Only 60 out of 100 EFL students who conducted the Oxford Quick Placement Test for this reason were chosen. Group 1 (American Culture; AC), Group 2 (Saudi Culture; SC), and Group 3 (Culture-Free; CF) were created by randomly selecting the responses. After that, each group was pre-tested on vocabulary and idioms. The groups' respondents were then given three different treatments. For the treatment, the SC group received instruction on 10 texts related to Saudi traditions and culture; the AC group received instruction on 10 texts containing vocabulary and idiomatic structures pertinent to the American culture; and the CF group received instruction on 10 texts that were culture-free but still contained some phrases and idiomatic structures. The data collected were examined and analyzed employing one-way ANOVA in addition to paired sample t-test following the instruction, which was broken up into 10 sessions of 60 minutes each. According to the findings, the AC and SC groups outperformed the CF group. Further, there was a significant difference between the pre-test and post-test of the SC, with Sig (.00) < 0.05, suggesting that teaching English vocabulary and idioms from the Saudi culture had a substantial impact. Finally, the results also showed that there was a significant difference between the pre-test and post-test of the AC group as Sig (.00) < 0.05, suggesting that teaching English vocabulary and idioms from the American culture had an influential impact on the participants. There are several ramifications of this study for instructors, and curriculum designers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".