Testing the guidance hypothesis for location learning in GUIs

Knowing command locations is an important part of expert performance in GUIs, but building this knowledge requires laborious visual search. Many UI tutorials provide visual guidance during training (e.g. icon highlighting) to make visual search easier – but the “guidance hypothesis” suggests that users will rely on the guidance rather than learning locations, compromising performance in the real UI where guidance is unavailable. To test the guidance hypothesis for GUI location learning, we developed a design framework that identifies two key dimensions of guidance: visual style and temporal delay. We then performed three studies with two GUIs (a CommandMap and the Blender 3D modeling application), investigating three styles of guidance (highlighting, animated trails, and stencils) and three presentation delays (immediate, static, and increasing). Results showed that delay had a substantial effect on location learning: immediate presentation impaired learning of icon locations compared to unguided training, but static and increasing delays showed no significant differences in learning compared to the baseline. Though the effects of guidance style were less obvious, animated trails reduced location learning on some measures. Our work provides new understanding of the guidance hypothesis and new opportunities for tutorial designers to build effective and usable training systems for GUIs.

Authors

Institutions

Publication Details

Journal
Human-Computer Interaction
Published
2026-10-29
DOI
https://doi.org/10.1080/07370024.2026.2741812
Primary Topic
Usability and User Interface Design
Type
article
Field-Weighted Citation Impact
0.00

Funders

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

Testing the guidance hypothesis for location learning in GUIs

Andy Cockburn, Carl A. Gutwin, Morgan Beattie
2 links
Human-Computer Interaction
Usability and User Interface Design
article

Testing the guidance hypothesis for location learning in GUIs

Andy Cockburn, Carl A. Gutwin, Morgan Beattie
article en

Abstract

Knowing command locations is an important part of expert performance in GUIs, but building this knowledge requires laborious visual search. Many UI tutorials provide visual guidance during training (e.g. icon highlighting) to make visual search easier – but the “guidance hypothesis” suggests that users will rely on the guidance rather than learning locations, compromising performance in the real UI where guidance is unavailable. To test the guidance hypothesis for GUI location learning, we developed a design framework that identifies two key dimensions of guidance: visual style and temporal delay. We then performed three studies with two GUIs (a CommandMap and the Blender 3D modeling application), investigating three styles of guidance (highlighting, animated trails, and stencils) and three presentation delays (immediate, static, and increasing). Results showed that delay had a substantial effect on location learning: immediate presentation impaired learning of icon locations compared to unguided training, but static and increasing delays showed no significant differences in learning compared to the baseline. Though the effects of guidance style were less obvious, animated trails reduced location learning on some measures. Our work provides new understanding of the guidance hypothesis and new opportunities for tutorial designers to build effective and usable training systems for GUIs.

Human-Computer Interaction
University of Canterbury (NZ), University of Saskatchewan (CA)
Natural Sciences and Engineering Research Council of Canada
Quality education
Openalex Percentile: Top 35%
Usability and User Interface Design
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.

Laika access coming soon
Testing the guidance hypothesis for location learning in GUIs — Andy Cockburn, Carl A. Gutwin, et al. · Human-Computer Interaction (2026) | TGRS Research Map | TGRS