Developing Pedagogy for the Creation of a School Makerspace: Building on Constructionism, Design Thinking, and the Reggio Emilia Approach
Bibliographic record
Abstract
Making and makerspaces, current buzz words in education, have gained prominence for their ability to develop the problem solving, collaboration, creativity, and technological skills needed for the 21st century. In preparation for the creation of a makerspace within a primary school learning commons, a list of necessary pedagogical components were identified based on three distinct discourses: constructionism, as derived from the work of Seymour Papert and the team in the Media Lab at the Massachusetts Institute of Technology, the principles of design thinking in an educational context, and the pedagogy of Reggio Emilia. In examining these discourses separately, the writer determined elements common to all three. Drawing upon these common elements, guiding questions were developed that can be used to inform the creation of a school makerspace.
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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 | 0.017 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.030 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".