An automated cognitive walkthrough
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Display-based action at the user interface
International Journal of Man-Machine Studies
Cognitive walkthroughs: a method for theory-based evaluation of user interfaces
International Journal of Man-Machine Studies
Learning strategies and exploratory behavior of interactive computer users
Learning strategies and exploratory behavior of interactive computer users
Turning research into practice: characteristics of display-based interaction
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A dual-space model of iteratively deepening exploratory learning
International Journal of Human-Computer Studies - Special issue: the role of cognitive science in human-computer interaction
Natural command names and initial learning: a study of text-editing terms
Communications of the ACM
Human Problem Solving
LICAI+: a comprehension-based model of learning for display-based human-computer interaction
CHI EA '97 CHI '97 Extended Abstracts on Human Factors in Computing Systems
A comprehension-based model of exploration
Human-Computer Interaction
Latent semantic linking over homogeneous repositories
DocEng '01 Proceedings of the 2001 ACM Symposium on Document engineering
An infrastructure for open latent semantic linking
Proceedings of the thirteenth ACM conference on Hypertext and hypermedia
Effects of scent and breadth on use of site-specific search on e-commerce Web sites
ACM Transactions on Computer-Human Interaction (TOCHI)
Modeling information navigation: implications for information architecture
Human-Computer Interaction
Information structure and practice as facilitators of deaf users' navigation in textual websites
Behaviour & Information Technology
The Learning Grid and E-Assessment using Latent Semantic Analysis
Proceedings of the 2005 conference on Towards the Learning Grid: Advances in Human Learning Services
E-assessment using latent semantic analysis
3LeGE-WG'03 Proceedings of the 3rd international LeGE-WG conference on GRID Infrastructure to Support Future Technology Enhanced Learning
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Models of learning and performing by exploration assume that thesemantic similarity between task descriptions and labels on displayobjects (e.g., menus, tool bars) controls in part the users searchstrategies. Nevertheless, none of the models has an objective wayto compute semantic similarity. In this study, Latent SemanticAnalysis (LSA) was used to compute semantic similarity between taskdescriptions and labels in an applications menu system.Participants performed twelve tasks by exploration and they weretested for recall after a l-week delay. When the labels in the menusystem were semantically similar to the task descriptions, subjectsperformed the tasks faster. LSA could be incorporated into any ofthe current models, and it could be used to automate the evaluationof computer applications for ease of learning and performing byexploration.