MP39-03 THE LEARNING STYLES OF GRADUATING CANADIAN UROLOGY RESIDENTS
Bibliographic record
Abstract
You have accessJournal of UrologyEducation Research II (MP39)1 May 2024MP39-03 THE LEARNING STYLES OF GRADUATING CANADIAN UROLOGY RESIDENTS Nicolas Vanin Moreno and Naji J. Touma Nicolas Vanin MorenoNicolas Vanin Moreno and Naji J. ToumaNaji J. Touma View All Author Informationhttps://doi.org/10.1097/01.JU.0001008644.01945.6c.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The Kolb learning theory attributes differences in learning to how an experience is perceived and processed. Subsequent learning style inventories were created with the latest version in the form of the validated Kolb's Experiential Learning Profile (KELP). Studied in other surgical disciplines, identifying the learning style of urology residents may help in the development of teaching curricula that are best suited to knowledge and skill acquisition. The objective of this study is to both characterize the learning styles of graduating Canadian urology residents and correlate individual styles with exam performance. METHODS: The KELP was administered to all graduating Canadian Urological residents attending QUEST between 2021-23. All participants received a report at the conclusion of the course. Participants' preferred learning phase (Acting, Thinking, Reflecting, Experiencing) and a specific learning style (Deciding, Analyzing, Thinking, Acting, Initiating, Balancing, Reflecting, Experiencing, Imagining) were identified for all residents. Individual exam performance was recorded for both written and OSCE components. Cumulative, OSCE, and written scores were analyzed between learning phase, and learning style, respectively (mean percentile score±SD; One-way ANOVA, Tukey's multiple comparisons test, α=0.05). RESULTS: Graduates from 2021 (n=35), 2022 (n=29), and 2023 (n=37) were included. The most common preferred learning phase were "Acting" (38/101, 37.6%) and "Thinking" (35/101, 34.7%). The most common preferred learning styles were "Deciding" (19/101, 18.8%), "Acting" (15/101, 14.9%), and "Analyzing", "Initiating" and "Thinking" (14/101, 13.9%, each). There was no significant difference between preferred learning phase and oral, written, or total exam performance (p>0.05). Graduates with the "Acting" (69.72%±4.25 SD) learning style performed significantly better than the "Analyzing" (59.33%±10.67 SD) learning style in the OSCE component (p=0.02). There was no difference between learning styles and written or overall scores (p>0.05). CONCLUSIONS: Graduating Canadian urology residents vary in their preferred learning styles, but the majority seem to learn by acting and thinking. There was evidence of better oral exam performance between a hands-on learning style compared to an analytic one, however increased test numbers may better elucidate the strength and relevance of this relationship. This lays the groundwork for future studies correlating learning style to exam performance and identifying predictors of successful completion of residency. Source of Funding: No source of funding to declare © 2024 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 211Issue 5SMay 2024Page: e652 Advertisement Copyright & Permissions© 2024 by American Urological Association Education and Research, Inc.Metrics Author Information Nicolas Vanin Moreno More articles by this author Naji J. Touma More articles by this author Expand All Advertisement PDF downloadLoading ...
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.161 | 0.019 |
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".