Effective competency-based medical education requires learning environments that promote a mastery goal orientation: A narrative review
Bibliographic record
Abstract
PURPOSE: Competency-based medical education (CBME) emphasizes the need for learners to be central to their own learning and to take an active role in learning. This approach has a dual aim: to encourage learners to actively engage in their own learning, and to push learners to develop learning strategies that will prepare them for lifelong learning. This review paper proposes a theoretical bridge between CBME and lifelong learning and puts forth the argument that in order for CBME programs to produce the physicians truly needed in our society now and in the future, learning environments must be intentionally designed to foster mastery goal orientations and to support the development of adaptive self-regulated learning skills and behaviours. MATERIALS AND METHODS: This narrative literature review incorporated results of searches conducted by a subject librarian in PsycInfo and MedLine. Articles were also identified through reference lists of identified papers to capture older key citations. Analysis of the literature used a constructivist epistemological approach to develop an integrative description of the interaction of achievement goal orientation, self-regulated learning, learning environment, and lifelong learning. RESULTS: Findings from achievement goal theory research support the assumption that adoption of a mastery goal orientation facilitates the use of adaptive learning behaviours, such as those described in self-regulated learning theory. Adaptive self-regulated learning strategies, in turn, facilitate effective lifelong learning. The authors offer evidence for how learning environments influence goal orientations and self-regulated learning, and propose that CBME programs intentionally plan for such learning environments. Finally, the authors offer specific suggestions and examples for how learning environments can be designed or adjusted to support adoption of a mastery goal orientation and use of self-regulated learning behaviours and strategies to help support development of adaptive lifelong learners.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 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".