Needs Investigation Methods Compatible With Key End User Limitation (Nickel): A Tool For Selecting User Centered Needs Elicitation Methods For Older Adults
Bibliographic record
Abstract
During the design process older and/or disabled adults are often left out of the needs elicitation process because many of the User Centered Needs Elicitation Methods (UCNEM) are not accessible to these individuals. This thesis explains the development of NICKEL, a decision-support tool which allows users to determine UCNEMs that fit the human capability of the older and/or disabled adult participants in their study. Three levels of the cognitive, visual, hearing and physical human capabilities required for 19 UCNEMs are determined using a survey and focus group with expert designers/researchers. A user study is carried out to determine the usability and usefulness of NICKEL with novice and expert designers/researchers. Major findings indicated that NICKEL is an easy to use and useful tool for users when determining appropriate UCNEMs for older and disabled adults. Future work could include adding other capabilities such as interpersonal skills and adding new methods to NICKEL.
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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 | 0.020 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".