Cultural Barriers: Pros and Cons on ELT in Iran
Bibliographic record
Abstract
During the process of language learning some crucial cultural factors may be notified, seriously hindering the effective learning process, and commonly known as cultural barriers. Effective language learning among different cultures is especially challenging, due to the different ways of thinking, seeing, hearing, and interpreting the world provided by cultures. Cultural barriers are considered as those traditions which become hurdles in path of understanding or teaching/learning different languages, among which body language, religious beliefs, etiquette and social habits are noteworthy. The present study is mainly focused on the positive and negative impacts of cultural barriers on English language teaching/learning process in Iran. Accordingly, the effect of the usage of social factors, religious matters, taboo words as cultural dimensions are investigated, on the basis of the questionnaires prepared and distributed among 80 Shahid Beheshti University (Tehran/Iran) students. The questions are mainly to diagnose the cultural elements which might hinder or foster the learning process, and to propose solutions on its basis. The analysis describes the relationships between the items in the survey. For the purpose of the research percentages are used to express how the five main domains under consideration and the included matters are relative to one another. The statistical analysis of the questionnaires explores the effect of the usage of cultural dimensions on ELT in the community being studied. The partial effect of each domain is calculated, the results of which highlight the main criteria included under the broad term of cultural barriers and its implications on overcoming the desired outcomes in the teaching/learning process in Iran.
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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 | 0.003 | 0.012 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".