An Exploratory Investigation of Cognitive Mapping for Analyzing Needs in UX Design
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
Needs analysis is a major concern in innovation projects both for organizations pursuing business objectives and for the users whose needs should be satisfied. Different needs analysis methods can be used, depending on the scope and complexity of the project. However, not all the existing methods provide efficient decision-making support for designers whose task is to categorize and prioritize the needs. The aim of this article is to explore the application of cognitive mapping as a needs analysis method that will more efficiently analyze the nature of the needs and their interrelations. This analysis will provide a different perspective for understanding needs and, thus, contribute to decision making and prioritization. To this end, the proposed method was tested with the UX team of a large established North American transportation company. The feedback from the multiple groups involved in needs analysis indicated that the need mapping technique was perceived as useful and could be applied as a decision support.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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