Basics and Beyond: Faculty Development as a Professional Learning Journey
Bibliographic record
Abstract
This paper describes the implementation of the Basics and Beyond certificate program for faculty that models a learning-centered, task-based approach to active learning. Unique aspects of the program include: flexible entry; a student focused/conceptual change model; a task-based, learning-centered approach (tasks and feedback drive the learning process); and authentic assessment. Throughout this program, tasks and feedback drive the learning process so as to engage faculty in active rather than passive learning. Faculty have immediate opportunities to apply new strategies to their own teaching context and receive feedback. In this way, the journey itself is as important as the destination. A two-year research project assessed the uptake and impact of the program. Quantitative and qualitative analysis of data shows changes in participants’ attitudes and approaches to their teaching. The data suggests that our model promotes deep learning that resulted in attitudinal and behavioral changes in the faculty participating in the Basics and Beyond program. In the paper we describe unique features of our program, the design of the research project, and our findings.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".