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Yemeni medicine students’ competence in medical English collocations

Paper · 2024 · Abdullah Al-Eryani, Abdulwadood Annuzaili and Sadiah Alwesabi

Summary

The study asks how well Yemeni medical students handle English collocations specific to medicine, and what holds them back. The authors used a mixed design with two instruments. The first was a test with a receptive part (multiple-choice recognition) and a productive part (translation-based production). The second was a closed-ended questionnaire on perceived obstacles. Scores were low on both parts: about 30% correct for recognition and about 35% for production. Production scoring slightly higher is unusual, and the authors explain it by students writing assignments and exams far more often than they read medical texts. Difficulty seemed to depend more on the task format than on the grammatical type of the word pair. The reported obstacles were:

  • teachers paying little attention to collocations,
  • syllabuses ignoring them,
  • traditional teaching methods,
  • students not seeing their value,
  • general English weakness,
  • Arabic–English linguistic and cultural gaps.

This matters because medical knowledge circulates mainly in English, and these word combinations are a major barrier to comprehension and fluent use.

Key points

  • Overall accuracy was 30.38% on the receptive (multiple-choice) test and 34.5% on the productive (translation) test.
  • Verb-noun collocations were easier to recognize in multiple choice than to produce in translation, which suggests task type governs difficulty more than collocation class.
  • Proposed error sources are L1 negative transfer, approximation and overgeneralization, rarity of specific collocations, low exposure to medical texts, and limited medical vocabulary.
  • In the questionnaire, 50% agreed that Arabic–English linguistic differences hinder learning, and 40% said the same of cultural differences.
  • Recommendations include collocations in EMP curricula, authentic medical input, communicative teaching, and explicit contrast between L1 and L2 collocation patterns.

Interesting ideas

  • I1. Testing the same knowledge in both recognition and production modes shows that a system can know a combination passively yet fail to generate it.
  • I2. Difficulty tracked task format more than word-class type, which warns against scoring by category alone.
  • I3. Approximation, meaning keeping one correct component and substituting a near-synonym for the other, is a typical failure pattern for non-native combinations.
  • I4. Rare domain collocations are hardest, so frequency of exposure is a key factor.
  • I5. Negative L1 transfer comes from mapping a native phrase word for word into English.

For Mova

How these ideas could serve Mova, our small open language model — its files, stages and tests:

  • I1 (learn): Evaluate collocation handling separately for parsing (recognize the pair) and for generation (produce it), so that strengths in one mode do not hide gaps in the other.
  • I2 (answer): When school-course tests show errors, break down results by question format (choice versus open production) before blaming a grammatical category.
  • I3 (back): Have the generator check verb-noun and adjective-noun pairs against a compiled collocation list, flagging near-synonym substitutions that sound unnatural.
  • I4 (world): Store domain-specific collocations (e.g. medical verb-object pairs) with frequency marks in compiled knowledge, so rare but fixed pairs are treated as units rather than free combinations.
  • I5 (back): In translation through the meta-world, generate English collocations from the meaning frame rather than by word-level mapping from the source language, to avoid calqued pairs.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

Also on the byline: Sana'a University · 21 September University for Medical and Applied Sciences.

 Fields, topics and concepts

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksPsychology · 1,552 worksDevelopmental and Educational Psychology · 499 worksMedicine · 241 worksPublic Health, Environmental and Occupational Health · 10 works

🧭 Topics 2Research subjects and languages the work is about.English · 2,263 worksIdioms & multiword expressions · 217 works

Cite

Cite as Abdullah Al-Eryani, Abdulwadood Annuzaili and Sadiah Alwesabi. 2024. Yemeni medicine students’ competence in medical English collocations. ExELL (Explorations in English Language and Linguistics) 12.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.51558/2303-4858.2024.12.2.306

@inproceedings{aleryani2024yemeni,
  title = {{Yemeni medicine students’ competence in medical English collocations}},
  author = {Abdullah Al-Eryani, Abdulwadood Annuzaili and Sadiah Alwesabi},
  booktitle = {ExELL (Explorations in English Language and Linguistics) 12},
  year = {2024},
  doi = {10.51558/2303-4858.2024.12.2.306},
  url = {https://doi.org/10.51558/2303-4858.2024.12.2.306}
}

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