Integrating a Longitudinal Course on the Principles of Research in an Outcomes-Based Undergraduate Medical Education Curriculum
Bibliographic record
Abstract
Background and Need for Innovation: Teaching and learning approaches can support medical students in developing the research skills necessary to be adept consumers of scientific research. Despite various influencing factors, existing literature on effective strategies in undergraduate medical education remains limited. Goal of Innovation: Using a spiraled curriculum, we created and evaluated a longitudinal course to enhance medical students' research abilities. Steps Taken for Development and Implementation of Innovation: During a recent curriculum renewal at one medical school, a three-year longitudinal course on the principles of research was developed and implemented. The innovation of this course includes the sequential nature and deliberate redundancy of curriculum content, how new knowledge is linked to prior learning, and the progressive level of difficulty in knowledge application and skill development. Evaluation of Innovation: The authors analysed faculty members' and students' satisfaction and their perceptions of each session of the course using program evaluation data collected between 2019 and 2021. Both faculty members and students recognized the benefits of revisiting concepts and highlighted learning outcomes like improved synthesis of information, explaining findings to patients, and enhanced critical thinking. Critical Reflection: The adoption of a spiraled curriculum in undergraduate medical education offers a systematic approach for developing students' research skills. The positive reception of this innovation underscores its potential to help future health professionals form a professional identity as adept researchers. However, its implications demand careful consideration and ongoing evaluation to ensure that the desired outcomes are sustained.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".