An evaluation of a visual interface for supporting query formulation in scholarly searching

Performing an effective literature review is a fundamental academic skill. Whether writing up a final project, preparing a research proposal, or simply finding answers to complex questions, students need to be able to systematically gather and analyse evidence from a variety of sources. However, many students have difficulty formulating effective search queries and understanding how to optimise their search strategy. This paper evaluates a novel approach to query formulation based on an alternative, visual interface. The approach is evaluated alongside a conventional, form-based interface in a comparative, controlled setting. The study finds that overall, participants considered the visual interface to be more complex and difficult to use. However, at the same time they used significantly more terms, facets and reformulations in the visual interface, and gave more attention to creating and refining more complex queries. In addition, the majority considered the visual interface to have greater transparency, with a clearer overview of the search tasks that encouraged them to invest greater effort in completing them successfully. The results demonstrate that visual approaches can offer tangible benefits in developing and improving students’ competence in exploratory search tasks.

Authors

Institutions

Publication Details

Journal
Journal of Librarianship and Information Science
Published
2024-11-04
DOI
https://doi.org/10.1177/09610006241291603
Citations
1
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An evaluation of a visual interface for supporting query formulation in scholarly searching

Tony Russell‐Rose, Tanja Svarre Jonasen
1 citations
Journal of Librarianship and Information Science
Semantic Web and Ontologies
0.35
article

An evaluation of a visual interface for supporting query formulation in scholarly searching

Tony Russell‐Rose, Tanja Svarre Jonasen
article en
1 citations

Abstract

Performing an effective literature review is a fundamental academic skill. Whether writing up a final project, preparing a research proposal, or simply finding answers to complex questions, students need to be able to systematically gather and analyse evidence from a variety of sources. However, many students have difficulty formulating effective search queries and understanding how to optimise their search strategy. This paper evaluates a novel approach to query formulation based on an alternative, visual interface. The approach is evaluated alongside a conventional, form-based interface in a comparative, controlled setting. The study finds that overall, participants considered the visual interface to be more complex and difficult to use. However, at the same time they used significantly more terms, facets and reformulations in the visual interface, and gave more attention to creating and refining more complex queries. In addition, the majority considered the visual interface to have greater transparency, with a clearer overview of the search tasks that encouraged them to invest greater effort in completing them successfully. The results demonstrate that visual approaches can offer tangible benefits in developing and improving students’ competence in exploratory search tasks.

Journal of Librarianship and Information ScienceVol. 58(1)
Goldsmiths University of London (GB), Aalborg University (DK)
Aalborg Universitet
Quality Education
Openalex Percentile: Top 32%
Semantic Web and Ontologies
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.