A Scoping Umbrella Review of Competency-Based Education: Part I – A Descriptive Analysis of Trends, Practices, and Gaps
Bibliographic record
Abstract
Competency-based education (CBE) has been increasingly adopted and popularized across diverse disciplines and professional fields. However, its implementation faces challenges due to the absence of a unified framework. Part I of this study aims to explore different theoretical approaches to CBE and to identify key approaches, emerging trends, and focal areas across diverse educational contexts, fields, and regions. A scoping umbrella review was conducted to synthesize evidence on CBE from systematic reviews, meta-analyses, and other reviews. Searches were performed across five databases by an experienced librarian, focusing on CBE frameworks and outcomes. Only peer-reviewed articles published in English were included. Four reviewers screened articles using Covidence software, resolving disagreements through discussion and collaboration. The umbrella review of 36 articles reveals key trends: (1) most are literature or systematic reviews, (2) published between 2017 and 2022, (3) primarily from the U.S. and Canada, and (4) focused on higher education and medical/health sciences. The review identifies three categories of theoretical approaches: theories, models, and frameworks. This review highlights the evolving theoretical foundations of CBE and its expansion across disciplines. The integration of various theories, models, and frameworks into a cohesive meta-framework emerges as a critical next step.
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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 | 0.021 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.021 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".