Student experiences of participating in five collaborative blended learning courses in Africa and Asia: a survey
Bibliographic record
Abstract
BACKGROUND: As blended learning (BL; a combination of face-to-face and e-learning methods) becomes more commonplace, it is important to assess whether students find it useful for their studies. ARCADE HSSR and ARCADE RSDH (African Regional Capacity Development for Health Systems and Services Research; Asian Regional Capacity Development for Research on Social Determinants of Health) were unique capacity-building projects, focusing on developing BL in Africa and Asia on issues related to global health. OBJECTIVE: We aimed to evaluate the student experience of participating in any of five ARCADE BL courses implemented collaboratively at institutions from Africa, Asia, and Europe. DESIGN: A post-course student survey with 118 students was conducted. The data were collected using email or through an e-learning platform. Data were analysed with SAS, using bivariate and multiple logistic regression. We focused on the associations between various demographic and experience variables and student-reported overall perceptions of the courses. RESULTS: =0.0036, OR=0.165; 95% CI: 0.049-0.555) were found to be associated with a more positive perception of BL, as measured by student rating of the overall helpfulness of the e-learning component to their studies. In contrast, perceiving the assessment as adequate was associated with a worse perception of overall usefulness. In a multiple regression, the course, experiencing no technical problems, and perceiving the discussion as adequate remained significantly associated with a more positively rated perception of the usefulness of the online component of the blended courses. DISCUSSION: The results suggest that lack of technical problems and functioning discussion forums are of importance during BL courses focusing on global health-related topics. Through paying attention to these aspects, global health education could be provided using BL approaches to student satisfaction.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".