Contexts, concepts and cognition: principles for the transfer of basic science knowledge
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
CONTEXT: Transfer of basic science aids novices in the development of clinical reasoning. The literature suggests that although transfer is often difficult for novices, it can be optimised by two complementary strategies: (i) focusing learners on conceptual knowledge of basic science or (ii) exposing learners to multiple contexts in which the basic science concepts may apply. The relative efficacy of each strategy as well as the mechanisms that facilitate transfer are unknown. In two sequential experiments, we compared both strategies and explored mechanistic changes in how learners address new transfer problems. METHODS: Experiment 1 was a 2 × 3 design in which participants were randomised to learn three physiology concepts with or without emphasis on the conceptual structure of basic science via illustrative analogies and by means of one, two or three contexts during practice (operationalised as organ systems). Transfer of these concepts to explain pathologies in familiar organ systems (near transfer) and unfamiliar organ systems (far transfer) was evaluated during immediate and delayed testing. Experiment 2 examined whether exposure to conceptual analogies and multiple contexts changed how learners classified new problems. RESULTS: Experiment 1 showed that increasing context variation significantly improved far transfer performance but there was no difference between two and three contexts during practice. Similarly, the increased conceptual analogies led to higher performance for far transfer. Both interventions had independent but additive effects on overall performance. Experiment 2 showed that such analogies and context variation caused learners to shift to using structural characteristics to classify new problems even when there was superficial similarity to previous examples. CONCLUSIONS: Understanding problems based on conceptual structural characteristics is necessary for successful transfer. Transfer of basic science can be optimised by using multiple strategies that collectively emphasise conceptual structure. This means teaching must focus on conserved basic science knowledge and de-emphasise superficial features.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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