The Form of Search Tool Chosen by Undergraduate Students Influences Research Practices and the Type and Quality of Information Selected
Bibliographic record
Abstract
A Review of: Asher, A. D., Duke, L. M., & Wilson, S. (2012). Paths of discovery: Comparing the search effectiveness of EBSCO Discovery Service, Summon, Google Scholar, and conventional library resources. College & Research Libraries, 74(5), p. 464-488. Objectives – To explore the effectiveness of different search tools (EBSCO Discovery Service (EDS), Summon, Google Scholar and traditional library resources) in supporting the typical research queries faced by undergraduate students and gain an understanding of student research practices. Design – Mixed methods approach using quantitative data collected from grading of students’ selected resources combined with qualitative data from a search process interview with students. Setting – Two university libraries in the United States of America (Bucknell University (BU) and Illinois Wesleyan University (IWU)). Subjects – Eighty-seven undergraduate students across a range of disciplines. Methods – Participants were assigned to one of five test groups and required to find two resources for each of four standardised research queries using a specified tool: EDS; Summon; Google Scholar; Library catalogue/databases; or “no tool” where no specific tool was specified and participants were free to choose. The resources submitted by students for each of the four queries were rated on a scale of 0-3 by four librarians using a rubric, to produce average ratings for each tool. The interview comprised two parts: the search task, followed by a reflective interview based on open-ended questions relating to search practices and habits. The search process interview was recorded using Camtasia screen capture and audio software, and the URLs used by participants were also recorded. Main Results – Quantitative results indicated that students who used EDS selected slightly higher quality sources on average (scoring 2.54 out of 3), compared to all other groups. Those who used EDS also completed the queries in less time (747 seconds) than those using Summon (1,209 seconds), Google Scholar (968 seconds), library databases (963 seconds) or where no tool was specified (1,081 seconds). Academic journal articles also represented the relatively highest proportion of resources for this group (73.8% of resources chosen), whilst newspaper articles were chosen most frequently by those using Summon (20.6% of resources chosen). The qualitative findings suggest that students may over-rely on the top results provided by search systems, rather than using critical analysis and evaluation. Conclusion – Although EDS performed slightly better overall, in some cases the tools produced relatively similar results, and none of the tools performed particularly poorly. Indeed the reasonably strong performance of both Google Scholar and traditional library tools/databases in some aspects (such as the relative proportion of books and journal articles chosen by students), may raise questions regarding the potential benefit of acquiring a new discovery product, given the possibly significant costs involved. As the study finds that most students do not go beyond simple searches and the first page of results, regardless of the tool they are using, this suggests that discovery services do not substantially lessen the need for information literacy instruction, although it may provide some opportunity to redirect teaching time away from retrieval and towards higher-order skills such as evaluating information and critical thinking.
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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 | 0.027 | 0.161 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".