Lessons Learned from a Distance-based Consulting Program to Assist Faculty Development Projects
Bibliographic record
Abstract
Changes in faculty roles and demographics necessitate a re-examination of the types of professional development opportunities offered in academic institutions. A distance-based consulting program was designed to assist faculty development projects as they progress through all stages of faculty development: needs assessment, project design, implementation, and, in particular, program evaluation and dissemination of results (i.e., presentations and published articles). The progress of 17 faculty development projects in primary care educational sites that received assistance in the United States and Canada was tracked over two years. Three factors were identified as having the most impact on the success of faculty development projects: (1) funds committed to and designated for faculty development; (2) funded, protected time for at least one person to implement the faculty development initiative; and (3) an environment capable of supporting faculty development initiatives (e.g., no major budget shortfall, few faculty transitions, a strong mission, no threat of mergers). Only a few of the participating sites reached the stage of evaluating and publishing articles about the outcomes of their projects within the designated 15-month time frame, with many sites reporting environmental impediments to project success. The authors describe the institutional characteristics that facilitated project success, assess the usefulness of distance-based consulting efforts, and offer recommendations for future distance-based consulting programs. They conclude by noting that the personal touch (i.e., one-on-one contact with consultants) is what is most appreciated, and that excellent one-on-one, in-person assistance may be inherently more effective than even the best-run distance-based consulting.
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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 | 0.017 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".