Using Gamification to Understand Accreditation in Postgraduate Medical Education
Bibliographic record
Abstract
Accreditation of postgraduate medical education (PGME) exists in a number of nations and requires a thorough understanding of the inherent concepts for optimal use. Ideally, accreditation entails assessment of programs against standards to benefit stakeholders, such as patients, learners, or the public. This establishes it as a social construct. Defining the elements of PGME accreditation from an international perspective is a daunting challenge, given that local context and considerations vary. The components of this complex construct can be understood effectively with “gamification.” Gamification has been beneficial in other educational areas to clarify concepts and enhance comprehension.1 Here we offer an accreditation consensus game to guide groups of stakeholders in international settings through the relevant questions and answering these questions through a range of strategic options.2 Our gamification approach illuminates accreditation in PGME from an international perspective and highlights its social attributes.Educational gaming in health professionals education is an emerging teaching methodology that promotes active learning environments where participants engage in activity and reflect on that activity, abstract useful insights from the analysis, and put the results to work.3 A recent systematic review found gamification often is more effective than other approaches.4 Participants learn from their own actions and benefit from interactions with others and the discussions that follow.5 Games facilitate experiences which become resources for learning. The game in this article is designed to promote critical thinking and reflection on the complex social construct of accreditation in a fun and exciting way, which in turn may increase retention. Our gamification approach builds on and adapts the framework constructed from a previous study of Dutch accreditation development (table).2Participants are assigned to small groups and are tasked with constructing their ideal accreditation system by discussing the options presented as playing cards for each of the why, what, how, and who elements of the framework, and reaching consensus about the most appropriate option(s), while taking into account their local context and stakeholders' perspectives. Variations of the game include playing from the perspective of different stakeholder groups (eg, administrators, clinical teachers, patients, and others) and contrasting the outcomes.The accreditation game and the instructions to play are available as online supplemental material.Our aim was to use gamification to enhance insight into relevant concepts of PGME accreditation and in turn enhance the applicability and adaptability of accreditation concepts to different international contexts and stakeholder perspectives. Comparisons of the strategies that come from these different contexts and perspectives could result in new knowledge about enduring concepts across different national contexts and relevant attributes for a given situation. For example, participants from recently developed PGME education systems were most interested in quality assurance philosophies, while stakeholders from more mature systems desired continuous quality improvement, customization, and variation for the sake of excellence.The game was specifically designed to ensure participants make difficult choices in selecting the best or most optimal statements based on their ideal accreditation system (ie, there were fewer card places in the game than statement choices available). In multiple evaluations after tryouts of the game in several countries, we saw that this approach was well-liked and useful. We believe that this game increases insight that accreditation systems are based on choices among a range of strategic options, and sparks reflection on how these concepts would apply to local systems.The application of this accreditation game is not limited to PGME; with a few alterations it could also be useful for accreditation of medical schools or other health professionals' education. In addition, educational games could be helpful in promoting accreditation.In many cases educational games involve a competitive activity,6 whereas in our accreditation game we encourage participants to build their ideal system and compare its qualities with the existing system in a collaborative manner. Future research needs to be conducted regarding the effectiveness of the game in learning retention and this approach for understanding other complex constructs in PGME.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".