The multiple dimensions of curriculum mapping: designing a comprehensive outcomes-based framework
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
In curriculum design processes, the principle of constructive alignment represents an effective tool for aligning curricula, pedagogy and assessments to make curriculum content explicit. Yet there remain gaps in the achievement of constructive alignment in higher education. Curriculum mapping processes attempt to map the vertical and horizontal alignment between modules and courses; however, as we argue in this article, there may be gaps in these processes such that full constructive alignment is not adequately achieved. In this article, we present a framework that identifies all connecting relationships between module and course learning outcomes as required for comprehensive constructive alignment. The framework serves to highlight where these gaps (or what we call fracture points) may occur that are not adequately addressed by curriculum mapping processes. The utility of this framework comes not only in offering insight into the contributory roles of learning outcomes and constructive alignment processes (and thus providing the opportunity to reflect and address disparities that may lead to curricular misalignment in higher education); it also provides more coherence in approaches to understanding the why of learning outcome design.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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