Facet Use in Search Tools is Influenced by the Interface but Remains Difficult to Predict
Bibliographic record
Abstract
A Review of: Dahlen, S. P. C., Haeger, H., Hanson, K., & Montellano, M. (2020). Almost in the wild: Student search behaviors when librarians aren’t looking. Journal of Academic Librarianship, 46(1), 102096. https://doi.org/10.1016/j.acalib.2019.102096 Abstract Objective – To examine the relationship between student search behaviours and the quality of scholarly sources chosen from among library search tools. Design – Unmonitored search sessions in a facilitated library setting. Setting – A mid-sized public university in the United States of America. Subjects – 50 upper-level undergraduate students in the social and behavioural sciences. Methods – Recruited participants were given one of two search prompts and asked to use EBSCO’s Social Science Abstracts and two configurations of ProQuest’s Summon, with one being pre-scoped to exclude newspapers and include subject areas within the social sciences. The search tools were assigned in random order. In each case, the participant was asked to find two of the “best quality” articles (p. 3). A librarian was present in the room but did not observe participants; instead, all sessions were recorded using Camtasia Relay. Afterwards, participants were interviewed about the process they used and their impressions of the search tools. They also completed a survey collecting information on their GPA and whether they had previously had library instruction. Main Results – Facet use differed significantly between the EBSCO database and Summon, though not between the two different configurations of Summon. There was a significant relationship between high use of facets in one platform being connected to high use in the other platforms. In contrast to some previous studies, a non-trivial proportion of participants went beyond the first page of search results. In support of most previous studies, participants infrequently searched on the subject field or changed the default sort order. Summon’s article suggestion feature was noted as being especially helpful, and clicking on suggested articles was significantly correlated with the number of article records viewed. Conclusion – The choice of search tool has a large influence on students’ subsequent search behaviour. Many of the advanced features are still missed by students, although in this study the majority of sources picked were of high quality. The authors note the importance of configuring the interface so that facets and other features deemed worthwhile by librarians are higher up on the page. The researchers reason that the prominent display of facets leads to greater uptake. Despite finding no association between library instruction and facet use, teaching students how to use facets remains an advisable strategy.
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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 | 0.014 | 0.131 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".