Integrating Ultrasound Teaching into Preclinical Problem-based Learning
Bibliographic record
Abstract
OBJECTIVES: The aim is to provide students in the preclinical with ultrasound image interpretation skills. Research question: Are students in smaller groups with access to a combination of lectures and hands-on patient contact most likely to have better ultrasound image interpretation skills, than students in larger groups with only interactive didactic lectures? METHODOLOGY: First-year students at the preclinical Program of the College of Medicine, participated in two 2-h introductory interactive ultrasound sessions. The study comprised two cohorts: 2012/2013 students, who were offered large group teaching (LGT) sessions (control group), and 2013/2014 students, who received the intervention in small group learning problem-based learning (PBL) sessions (experimental group). The overall learning objectives were identical for both groups. The success of the module was evaluated using pre- and post-tests as well as students' feedback. RESULTS: The students in the experimental group showed significantly higher scores in interpretations of images than those in the control group. The experimental group showed achievement of learning outcomes along with higher levels of satisfaction with the module compared to the latter. CONCLUSION: Posttest knowledge of the basics of ultrasound improved significantly over the pretest in the experimental group. In addition, students' overall satisfaction of the ultrasound module was shown to be higher for the PBL compared to the LGT groups. Small groups in an interactive and PBL setting along with opportunities for hands-on practice and simultaneous visualization of findings on a high definition screen should enhance preclinical student learning of the basics of ultrasound. Despite the potential of ultrasound as a clinical, teaching and learning tool for students in the preclinical years, standardized recommendations have yet to be created regarding its integration into the curricula within academic institutions and clinical medicine. The interactive and PBL is here to stay at the college of medicine. Further research would be carried out to see if this trend persists in the upcoming vertical system-based curriculum of the college of medicine.
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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 | 0.022 | 0.138 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".