Difficulties Encountered by Arabic-Speaking Undergraduate and Graduate English Language Students in Interpreting English Formulaic Expressions
Bibliographic record
Abstract
This study investigates the difficulties that undergraduate and graduate students of English language encounter intheir interpretation and translation of English idiomatic/formulaic expressions into Arabic. Since the majority ofthese idiomatic expressions (referred to hereafter as IEs) in English or any other language potentially have morethan one interpretation, it has been assumed that these expressions constitute a major problem for non-nativespeakers of English, particularly for those who do not have adequate semantic and pragmatic competence in thetarget culture.The interpretation/translation task used in this study consists of three English formulaic expressions deliberatelyselected to measure both undergraduate and graduate students’ semantic and pragmatic competence ininterpreting/translating these formulaic expressions. The results of this study are based on the writteninterpretation/translation and the informal solicitation of responses from 83 undergraduate students of Englishlanguage and 13 graduate students of Applied Linguistics and Translation.The disparity in the students' performance on the interpretation task that was administered to both groupsunequivocally verified the claim that 'inter-lingual transfer’ occurs when foreign students are called upon totranslate from their mother tongue to a foreign language; and that acquiring adequate competence in thepragmatics of the target language and culture is highly essential for the acquisition of literacy and avoidance ofmisinterpretation of such expressions (Gass & Selinker, 1983; Odlin, 1989; Kharma & Hajjaj,1997; Mahmoud,2002).The findings of this study indicate that graduate students have done overwhelmingly well in comparison withtheir undergraduate counterparts. This is probably due to their continued training in translating material to andfrom the target language and culture. The findings have also emphasized the importance of providing studentswith adequate training in pragmatics, intercultural communication, and translation.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".