Novice and Advanced Learners’ Satisfaction and Perceptions of an e-Learning Renal Semiology Module During the COVID-19 Pandemic: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Nephrotic syndrome is a unique clinical disorder, which provides interesting teaching opportunities that connect physiological and pathological aspects to clinical practice. During the current COVID-19 outbreak, in-person teaching in our institution was not permitted, thus creating a unique challenge for clinical skills teaching. A case-based electronic learning (e-learning) activity was designed to replace the traditional in-person teaching of renal semiology. e-Learning activities have been shown to be effective for knowledge retention and increasing novice learners' performance. However, major knowledge gaps exist concerning the satisfaction of learners with e-learning activities as the sole form of teaching, specifically for undergraduate clinical skills education. OBJECTIVE: Our study aimed to prospectively assess undergraduate medical students' perceptions of and satisfaction with an e-learning activity teaching renal semiology. METHODS: All second-year medical students (novice learners) from the medical faculty of the University of Geneva, Switzerland, undertook the e-learning activity and were invited to participate in a nonmandatory, validated web-based survey, comprising questions answered using a 10-point Likert scale and one qualitative open-ended question. For comparison and to provide further insights, 17 fourth- to sixth-year students (advanced learners) were prospectively recruited to participate in both the e-learning activity and the evaluation. A mixed methods analysis was performed. RESULTS: A total of 88 (63%) out of 141 novice learners and all advanced learners responded to the evaluation survey. Advanced learners reported significantly higher satisfaction with the e-learning activity (mean 8.7, SD 1.0 vs mean 7.3, SD 1.8; P<.001), clarity of objectives (mean 9.6, SD 0.8 vs mean 7.7, SD 1.7; P<.001), and attainability of objectives (mean 9.8, SD 0.5 vs mean 7.3, SD 1.3; P<.001). Both groups showed high interest in the inclusion of the activity as part of a blended learning approach; however, there was low interest in the activity being the sole means of teaching. CONCLUSIONS: Case-based e-learning activities might be better suited for advanced learners and could increase learners' satisfaction within a blended teaching instructional design. More research on students' satisfaction with e-learning activities in the field of clinical skills education should be done. In addition, more effort should be put into finding alternative teaching tools for clinical skills education in light of the ongoing COVID-19 pandemic and future health crises.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".