Putting It Into Practice: Bridging the gap between learning and doing.
Bibliographic record
Abstract
This paper sets out to explore thinking-through-making as a complex dynamic of learnt skills and intuitive thought and to examine how these may be taught in what will be termed in this context ‘learning and doing’. The paper proposes that, whilst there are established strategies relating to the acquisition of craft skills and to creativity, it is less clear how intuition, as the act of knowing or sensing in the moment, can be taught in the context of art and design education. The paper will take the practice of drawing as its exemplar in this exploration of intuition, examining how it might be described and imparted in an education context and its value in creative, entrepreneurial and sustainable practice. It sets out to unpack what we might mean by ‘intuition’ in arts practice by examining the Aristotelian concepts of techné, metis and kairos. This mode of thinking is seen as the desired result in creative practice and the paper will argue that it is expressed most cogently in the teaching of drawing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.066 |
| Scholarly communication | 0.014 | 0.019 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| 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".