Comparing Cognitive Efficiency of Experienced and Inexperienced Designers in Conceptual Design Processes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Design cognition research aims to investigate the cognitive mechanisms and thought processes of human designers. In previous research, the cognitive activity of experienced and inexperienced designers has been compared in order to identify design strategies leading to design creativity. However, it is still unknown whether the design strategies applied are effective and whether the design processes are efficiently improved. In this paper, cognitive efficiency, describing how designers optimize mental resources to achieve creativity in conceptual design processes, was directly measured by the mental effort of designers and the creativity level of design outcomes. The results showed that the experienced designers generated more design concepts with higher quality and variety than did the inexperienced designers. The cognitive efficiency measures indicated that design expertise contributed to improving cognitive efficiency scores of quality. In addition, the systematic design method used by some designers was found to be related to high cognitive efficiency. It can be seen that the evaluation of cognitive efficiency has practical applications for designer training, design methodology evaluation, and design process improvement.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it