Building a human-computer interaction framework based on TAM/TPB/PR: A study of user satisfaction for accessible products
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
Accessible products play an essential role in the lives of people with disabilities. This paper aims to identify key user satisfaction with accessible products factors affecting the use of accessible products by people with disabilities that influence user satisfaction. The extended model incorporates the essential elements of the TAM, TPB, and PR models and user satisfaction as an external variable. Data were collected from 339 users of accessible products. Structural equation modeling was used to identify significant variables in this study. SEM considered “behavioral intention” to be the most important among them. This study generated design strategies based on significant factors analyzed in the findings and validated the design cases using the PSSUQ questionnaire, which showed that users had better user satisfaction when using accessible products with the new design strategies.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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