Exploring perspectives of personal learning plans in a residency programme
Bibliographic record
Abstract
Abstract Background Personal learning plans (PLPs) have gained traction in postgraduate medical education as an avenue for enhancing resident learning. However, implementing PLPs in real‐world education settings presents unique challenges. To realise the potential of PLPs, we must understand the factors that influence the quality of PLP implementation. The purpose of this study was to explore the use and implementation of PLPs during residency training from the residents' and academic advisors' perspectives within a competency‐based residency programme. Methods We conducted semi‐structured interviews with residents ( n = 18) and academic advisors ( n = 9) in an Internal Medicine residency programme at a Canadian academic centre. Interviews were audio recorded, transcribed verbatim and analysed using open coding. Findings Three higher order themes were developed to represent the participants' perceptions of implementing PLPs in a competency‐based residency programme: (a) setting the stage for learning, (b) fostering meaningful engagement and (c) learning through reflection. Results indicated that implementing PLPs requires collaboration between residents and academic advisors and supports from the broader programme and institution. PLP implementation is an iterative process that can provide a salient avenue for reflection and the development of self‐regulation skills. Discussion and Conclusion PLPs can be a useful tool to foster self‐regulated learning skills in residency education. It is imperative to consider how social and environmental supports can be enacted to facilitate engagement with, and implementation of, PLPs.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".