Resource Based Learning: some approaches in Devon Secondary Schools
Bibliographic record
Abstract
This study, undertaken between 1982 and 1985, examines aspects of\nresource-based learning in Devon Secondary Schools. Consideration\nis given to examples of resource based learning in Secondary Schools\nand the work of supporting agencies over the past two decades.\nThe work of resource providing agencies in Devon is considered through\na number of examples. The main part of this study considers developmental\nwork undertaken over two years in one quarter of Devon's\nSecondary Schools. This work was undertaken as part of two Joint\nRegional Courses organised by Devon L.E.A./Exeter University.\nThe principal findings of the work are considered in the context\nof: changed organisation in pupils' work patterns; changes in\nL.E.A. support of Curriculum development/ In-Service work; recent\ndevelopments in the curriculum and responses made by Devon teachers\nto these changes.\nThe conclusion considers possible changes which schools and the\nL.E.A. could make to promote more effective use of resource based\nlearning approaches in secondary education.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".