Ottawa 2020 consensus statement for programmatic assessment – 1. Agreement on the principles
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: In the Ottawa 2018 Consensus framework for good assessment, a set of criteria was presented for systems of assessment. Currently, programmatic assessment is being established in an increasing number of programmes. In this Ottawa 2020 consensus statement for programmatic assessment insights from practice and research are used to define the principles of programmatic assessment. METHODS: = 20), an inventory was completed for the perceived components, rationale, and importance of a programmatic assessment design. Input from attendees of a programmatic assessment workshop and symposium at the 2020 Ottawa conference was included. The outcome is discussed in concurrence with current theory and research. RESULTS AND DISCUSSION: Twelve principles are presented that are considered as important and recognisable facets of programmatic assessment. Overall these principles were used in the curriculum and assessment design, albeit with a range of approaches and rigor, suggesting that programmatic assessment is an achievable education and assessment model, embedded both in practice and research. Knowledge on and sharing how programmatic assessment is being operationalized may help support educators charting their own implementation journey of programmatic assessment in their respective programmes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.000 |
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 it