Using the AAMC Toolbox for Evaluating Educators: You be the Judge!
Bibliographic record
Abstract
Abstract Introduction In the past two decades, significant progress has been made in defining and justifying the value of scholarship in education. However, educators at many academic health centers continue to struggle with advancement and promotion because the process for evaluating their contributions is often cumbersome and accepted standards for evaluation are vague or lacking. The basis for evaluating educators has been strengthened by defining educational scholarship and by developing templates for faculty to document their educational contributions using educator's portfolios. This toolbox presents a sound framework for evaluating educational contributions in a rigorous manner analogous to the peer review process used for assessment of a faculty member's work in research and other scholarly work. Methods This 90-minute workshop is designed to provide hands-on opportunities for members of promotions/tenure committees to utilize the AAMC Toolbox for Evaluating Educators resource in the assessment of faculty member performance whose careers focus across the following five domains of educator activity: learner assessment, curriculum development, mentoring and advising, education leadership and administration, and teaching activities. The exercises in the workshop allow participants to use the indicators to reach summative decisions through a rigorous and consistent application of clear yet flexible standards. The workshop consists of an introductory PowerPoint presentation and small-group activities followed by a facilitated large-group discussion that allows the participants to explore how the evidence-based standards in the toolbox can be integrated with existing institutional processes for the evaluation of the performance of educators. The workshop and its resources can be adapted and used for training/professional development sessions for other decision making committees/members (e.g., awards committees or selection committees for a teaching academy). Results A professional development workshop using the Toolbox has been presented at each of the regional Group on Educational Affairs meetings, at the Group on Faculty Affairs annual Professional Development Conference, and in plenary sessions at two annual AAMC meetings. The participants have reviewed, critiqued and applied the indicators in the Toolbox during interactive exercises. The authors used written and oral feedback to refine the structure and content of the Toolbox. Discussion The resource was created primarily for faculty and committees charged with faculty evaluation and decision making; however, it is also useful for educators who are seeking promotion and their mentors including faculty affairs and education administrative leaders. Knowledge of the standards by which one's performance will be judged helps an educator create a portfolio that documents his/her activities and the impact of their work, in a standardized format that can be readily assessed.
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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 | 0.055 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.043 | 0.040 |
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".