Bibliographic record
Abstract
We ask the reader to consider a proposal for cooperative renewal in the evaluation of a course (OurU) offered in partnership between a university and community-based adult learning center. This proposal’s aim is to enhance adult learners’ ability to evaluate their learning experiences, with the goal of adopting more learner-directed content into OurU’s curriculum. Drawing from instructional team members’ experiences in a diverse adult learning environment, the authors propose steps to develop a more holistic and dynamic approach to evaluation. In this snapshot of a course operating within the same budgetary realities familiar to others in the field, resourcing evaluation is a priority for developing a dynamic assessment evaluation model. This article is offered from the view that learning is a social process and community-based research and learning can be an organic connection place between universities and the communities they serve. This article is intended primarily for practitioners in community-based adult learning contexts seeking alternatives to course evaluation processes that situate learners at the process center, as well as academics interested in participating in partnering with community adult learning centers to strengthen adult learners’ evaluation and research capacity.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.126 | 0.023 |
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".