Proposition and Test of a Quality Assessment Extension WebQual Model in Brazil
Bibliographic record
Abstract
This study has a purpose to test the extended WebQual Model from the inclusion of the construct familiarity has nomological validity, besides to verify the explained variance to satisfaction and intention to reuse are higher in the extended model than the original model. The quality evaluation WebQual model presents a measurement process from twelve constructs: information fit-to-task, tailored information, on-line completeness, relative advantage, easy of understanding, intuitive operations, trust, response time, visual appeal, innovativeness, emotional appeal and consistent image. Constructs familiarity, satisfaction and intention to reuse by users were included in this model. Data were collected by electronic means, and at the end, 456 questionnaires were obtained from the Rede Habitar portal and 240 questionnaires from Rede Imvista portal, totalizing 696 questionnaires. Obtained results indicate that the analyzed portals quality evaluation is reasonable, which all one-dimensional indices, reliability, and convergent validity showed suitable results. In the discriminant validity, only two correlations did not show proper values. Nomological validity was achieved and the relationship between the extended model constructs were shown suitable. In explained variance terms, the construct familiarity insertion increased the indicator’s value for satisfaction, however it should also be considered the lack of discriminant validity between familiarity and satisfaction.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".