Mixed-Method Survey Research is Useful to Incrementally Improve Library Homepage Design
Bibliographic record
Abstract
A Review of: Deschenes, A. (2014). Improving the library homepage through user research – without a total redesign. Weave, 1(1). http://dx.doi.org/10.3998/weave.12535642.0001.102 Abstract Objective – To assess content organization and wording of links on the library’s homepage. Design – Mixed-methods survey. Setting – Small college, United States of America. Subjects – 57 library users. Methods – Library staff distributed paper surveys at the entrance to the library, with the goal of collecting a minimum of 30 surveys. The survey directed participants to indicate their preferred terms from a list, and their preference for ordering the menu items on the library’s homepage. Qualitative survey data was also collected via several open-ended questions that began with prompts such as “I really love…” and “I can never find…” Main Results – The search box tab labelled “Library Catalogue” was preferred over “Books and Media,” which the staff believed to be a more user-friendly term. Using a pre-defined list, participants ranked the Library Catalogue as the most important tab, followed by E-Resources, Articles, and Library Guides. A link to the Library Catalogue was also selected as the most important resource sidebar link, followed by E-Resources, Full-Text Journals, Library Guides, and Refworks. The service sidebar links by order of importance were found to be: Library Hours, Group Study Rooms, Writing & Citing, Interlibrary Loan, and Chat with a Librarian. Qualitative feedback received demonstrated a lack of understanding what the terms “Library Guides” and “A-Z List” mean, and difficulty finding a complete list of databases. Library staff received feedback that the Library Hours and Account Log In should be made more prominent. Conclusion – Library staff updated the website to reflect user preferences for wording and order of links on the homepage. Google Analytics showed a decrease of 30 seconds per average visit after the changes, which the author attributes to better wording and organization. There were no complaints about the website in the first three months after the change. The author concludes that a paper survey is an effective tool for librarians who would like to make incremental changes on their homepages.
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.
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 | 0.505 | 0.616 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.011 | 0.015 |
| Open science | 0.009 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.014 |
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".