Bibliographic record
Abstract
This paper has three objectives: (1) to examine the context in which faculty developers operate; (2) to review 25-year program of research for the findings that are most pertinent to teacher developers; and (3) to situate research into teacher development and consider the strategies that might persuade others to conduct research into teacher development in postsecondary education. The paper begins with an investigation of the structure of knowledge in university courses and moved through studies of the expectations of learning held by professors and students in selected disciplines. The results of the program of investigations over the years fall into three nested categories. At the most general level are findings about methods and lines of convergence across institutions and disciplines. At a more specific level is the examination of student learning and the comparisons between different types of student experience. Nested within these areas is the study of effects of differences in learning contexts. From this body of research, certain indicators of success for faculty developers have been derived. These are: (1) appropriate content in a course; (2) whether or not students have learned to think in a new way; and (3) the extent to which students incorporate their learning from courses into their other studies and their lives as scholars. A second set of indicators revolves around clear expectations for students and strategies for learning. A third set of indicators is needed to guide the research of faculty developers, and to explain instructional goals and methods and the extent to which they can be transferred. (Contains 2 tables, 2 figures and 29 references.) (SLD). Reproductions supplied by EDRS are the best that can be made from the original document. Indicators of success: From concepts to classrooms Janet G. Donald Centre for University Teaching and Learning McGill University 3700 McTavish Street Montreal Quebec Canada
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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 | 0.006 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".