Preclinical Medical Students' Perspectives and Experiences With Structured Web-Based English for Medical Purposes Courses: Cross-Sectional Study
Bibliographic record
Abstract
Background: English for medical purposes (EMP) is essential for medical students as it serves as a foundational language for medical communication and education. However, students often undervalue its importance within the medical curriculum. Given their demanding schedules and workload, educational methods for EMP must align with their needs. Structured web-based learning offers flexibility and convenience, yet limited research has explored its exclusive application for EMP in undergraduate medical education. Objective: This study aimed to evaluate medical students' perspectives on structured web-based EMP courses and assess their impact on medical English proficiency using objective and subjective measures. Methods: Structured web-based EMP courses were developed based on evidence-based guidelines, addressing barriers to web-based learning during development and implementation. A cross-sectional study was conducted with 535 medical students who completed these courses. Data were collected via questionnaires, the learning management system, and the Khon Kaen University Medical English Test (KKUMET), which assessed proficiency in listening, reading, writing, and speaking. Data were analyzed using descriptive statistics. Results: Of the 535 students, 452 (84.5%) completed the survey. Participants reported confidence in reading (mean 4.11, SD 0.87), vocabulary (mean 4.04, SD 0.84), and listening skills (mean 4, SD 0.89), but lower confidence in writing skills (mean 3.46, SD 1.07). The KKUMET results showed statistically significant improvements in all 4 language skills after course completion (P<.001). The top-rated benefits of the courses were convenience (mean 4.77, SD 0.59), sufficient instruction (mean 4.5, SD 0.85), and clear content (mean 4.41, SD 0.80). Conclusions: Structured web-based EMP courses are relevant and well received by medical students. These courses significantly improve students' medical English proficiency, as evidenced by both subjective feedback and objective measures. Medical educators should consider integrating structured web-based EMP programs to better support students' language proficiency in medical contexts.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".