Bibliographic record
Abstract
This paper proposes a mechanism to design Tangible User Interface (TUI) based on Adapted to the design of TUIs, the fitness-of-use mechanism now takes into consideration the potential conflicts between the hardware of the artifact (electro-mechanical components) and the form of the user's control (Physicalergonomics). The design problem is a search for an effortless co-existence (fitness-of-use) between these two aspects. Tangible interface design differs from traditional graphical interface design as unsolved conflicts between hardware and ergonomics can deeply affect the desired interaction. Here we propose a mechanism (in the form of eight questions) that support the design by defining the boundaries of the task, orienting the hardware (electro-mechanics) and ergonomics of the design space for various sub-tasks and finally fitting the different components of the hardware and physicalergonomics of the artefact to provide a component level fitness which will delineate the final tangible interfaces. We further evaluate the effectiveness and efficiency of our approach by quantitative user evaluation.
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How this classification was reachedexpand
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 | 0.012 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.093 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".