Bibliographic record
Abstract
The Michener Institute is Canada’s only postsecondary institution dedicated exclusively to education for the applied health science professions. Michener’s academic innovation strategy is focused on competency-based curriculum design, and leading edge education ensuring Best Experience Best Education for every learner. The compelling reasons for the redesign of health care education include: (1) concerns that the present medical education model is not sufficiently preparing graduates to ensure safe and effective practice, (2) potential compromise to the long-term ability of medical education delivery because of a limited number of clinical education sites, and (3) evidence that highlights the need for rigor in the assessment of competencies for health professions. The Michener Institute has taken a unique approach to address the challenges in medical education. The Academic Innovation Strategy is supported by 3 pillars which include Interprofessional Education (IPE), simulation education, and competency assessment, including assessment of readiness for clinical education. IPE is defined as “occasions when two or more professions learn together with the object of cultivating collaborative practice” (Barr, Freeth, Hammick, Koppel, & Reeves, 2000). New curriculum was developed to ensure graduate competency in interprofessionalism. Micheners’ organizational structure, use of physical resources and organizational communication patterns were redesigned to emulate the foundation principles of IPE. Simulation education provides a safe environment for learners to hone skills in communication critical thinking, crisis management, in addition to the profession-specific technical skills. Simulation provides learners with life situations where there is immediate feedback about decisions and actions in an environment tolerant of errors. By building on established simulation education expertise, Michener was able to reduce dependency on external clinical education sites. Developing authentic assessment of clinical education preparedness is not well documented. Our strategy is to develop authentic assessment to ensure that learners are prepared for clinical practice. Authentic assessment requires real-world application of skills and knowledge that have meaning beyond the assessment activity (Archbald & Newmann, 1988). Several important issues are raised and discussed in relation to the academic innovation strategy. What does an authentic assessment for readiness for clinical include? How much time is required for students to reach clinical competency? How does the curriculum design process support academic innovation? What are the research opportunities? This poster will highlight the rationale for the innovative strategy introduced by Michener, describe the strategic plan and illustrate the leading-edge curriculum design that integrates IPE, simulation education and a readiness for clinical assessment Conflict of Interest: Authors indicated they have nothing to disclose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.048 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.030 | 0.021 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".