Results of a Usability Study to Test the Redesign of the Health Sciences Library Web Pag
Bibliographic record
Abstract
Introduction In 2012 University of Calgary (U of C) Libraries and Cultural Resources implemented a new webpage, establishing new standards for design. Branch library webpage redesign followed. The new standards, as well as changing needs and usage created an opportunity for the Health Sciences Library (HSL) to significantly rework their webpage. To ensure that the new design was easy for users, a usability study was conducted. Methods Following a do-it-yourself usability protocol, eight participants (four faculty, four students) were asked to complete eight tasks using a mock-up of the redesigned webpage. A think-aloud protocol was used. The participant’s thoughts and pathways to complete these tasks were captured using Camtasia and then analyzed by two librarians. Results 1. Important information needs to be “above the fold” 2. Unified search, using article title, is the fastest way to find a known article compared with searching by journal title 3. Database is still “library jargon” 4. When looking at a list of recommended databases, users will scan for databases they’ve heard of. 5. 7/8 users had trouble navigating through the Research Guides Discussion The biggest challenge of the testing was participant recruitment. The redesigned page worked well, and only small design changes were needed. The testing revealed key information about how users search that will be useful for designing future instruction. It also highlighted that work needs to be done to improve our Research Guides.
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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 | 0.034 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".