Applying UEQ-S and VisAWI-S to Evaluate the User Experience of Four Online Information Literacy Tutorials
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
In this study, I applied the User Experience Questionnaire Short Version and the Visual Aesthetics of Website Inventory: Short Version to assess and improve the user experience of four online information literacy tutorials. I compared non-gamified tutorials with revised tutorials that incorporated user feedback improvements and gamification elements. The subsequent versions provided a more positive user experience. With a larger participant pool, overall UEQ-S mean values indicated neutral user experiences for three tutorials, while one showed a positive user experience. Given university students’ familiarity with digital technology, neutral user experience results are reasonable, considering the comprehensive academic content of these tutorials. The UEQ-S and VisAWI-S were valuable for developing information literacy tutorials to provide an improved user experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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