ProQuest Ebook Platform Outperforms EBSCO Ebook Platform in Functionality and Usability Study
Bibliographic record
Abstract
A Review of: Calhoun, E., & Zhu, M. (2023). A comparison study and heuristic evaluation of two aggregator ebook platforms: ProQuest eBook Central and EBSCOhost eBooks. Journal of Electronic Resources Librarianship, 35(2), 132–138. https://doi.org/10.1080/1941126X.2023.2197754 Objective – To identify the strengths and limitations in functionality and usability of two electronic book (ebook) platforms. Design – Comparison study and heuristic evaluation. Setting – University of Toronto Libraries. Subjects – The user interfaces and the library administration portals of the ProQuest and EBSCO ebook platforms. In ProQuest, the user interface is Ebook Central, and the administration portal is LibCentral. In EBSCO, the user interface is EBSCOhost eBooks, and the administration portal is EBSCO Collection Manager. Methods – The evaluation was conducted in August 2022. The authors compared the user interfaces for ease of use, searching and reading functionality, additional features, and accessibility. To evaluate the usability of features, the authors performed a heuristic evaluation by evaluating common tasks that a user would perform against the set of heuristic principles developed by Jakob Nielsen. When usability issues were identified, they were given a severity rating of critical, moderate, or minor. The authors then compared the administration portals using a set of common tasks that a library administrator would perform when managing ebook collections. A heuristic evaluation of the administration portals was not performed. Main Results – The ProQuest and EBSCO user interfaces have similar functionality. Users can search across the platform and within an ebook, view digital rights and bibliographic information, and access the full-text of a book. However, the heuristic evaluation revealed usability issues with both platforms. On the ProQuest platform, minor issues include misleading feature availability and non-descript link labelling. On the EBSCO platform, there are several issues with varying severity ratings. The most critical issue is that there is no warning that content saved to folders will be lost unless the user is signed into the platform. The moderate issues include a lack of autocorrection or spelling alternatives when searching, hyperlinks that blend into regular text, and a cluttered results page. Minor issues include inconsistent font hierarchies and different full-text access pathways depending on whether ebooks are available or unavailable to access. In the administration portal comparison, the two platforms are comparable for managing ebook download periods. When generating reports and configuring alerts, the ProQuest platform offers more customization options than the EBSCO platform. Conclusion – This study describes the strengths and limitations of the ProQuest and EBSCO ebook platforms. Overall, the ProQuest platform outperformed the EBSCO platform. For users, the ProQuest interface has fewer and less significant issues than the EBSCO interface. For library administrators, ProQuest offers more options for customizing reports and alerts. The findings of this comparison study and heuristic evaluation may help librarians and library staff choose the most suitable ebook platform for library users and administrators.
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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 | 0.020 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".