Downsizing EPMcreate to Lighter Creativity Techniques for Requirements Elicitation.
Bibliographic record
Abstract
EPMcreate is a creativity technique for requirements elicitation based on a 16-step process. These steps suggest focusing on requirements related to every combination of two different target users or viewpoints. A series of experiments confirmed its feasibility; its applicability, both as individual and group technique; and its greater effectiveness than brainstorming. However, analysts involved in some of the experiments highlighted the large number of steps as a limitation of the technique. Recent experiments tested a variant of the EPMcreate, named Power-Only EPMcreate, based on 4 of the 16 steps. The experiments showed that it works better than EPMcreate for at least website requirements. Nevertheless, the question of whether any other combination of the steps of the original technique could work is still open. This paper illustrates a number of criteria for generating lighter creativity techniques, each based on a subset of the 16 steps of EPMcreate.
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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 | 0.011 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".