Cooperative Learning in Scotland. Perspectives on the role of cooperative learning in supporting curricular policy and innovation
Bibliographic record
Abstract
The stated aim of the new Curriculum for Excellence is to deliver an education system in Scotland that meets the demands of the 21st Century. The new curriculum has been the subject of controversy relating to its capacity to support learning and the approaches to learning and teaching it advocates. The changes in curriculum require developments, for some practitioners, in how learning and teaching takes place with a focus on active learning. This paper explores whether one active learning strategy, cooperative learning, can assist teachers in delivering the new curriculum. Cooperative learning is a pedagogy that has been the focus of significant research in the United States and Canada with developing interest in a variety of countries (Gillies 2000; Gillies & Boyle 2005; Johnson 1993; Johnson 1985; Kagan & Kagan 2009; Slavin 1984; Weigmann 1992) but to date the research in the UK is limited. This paper explores findings on cooperative learning in a global context and through a case study in Scotland. The case study reported in this paper reflects on the responses of pupils to the introduction of cooperative learning in a secondary school in Scotland and the ways in which this approach appeared to support them in developing the four capacities of the new curriculum.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".