Adaptive Human-Computer Interfaces Using Expert Profiles
Abstract
Adaptive human-computer systems accommodate a wide variety of users learning to interact with computers because they adjust to different skill levels and provide novices with appropriate levels of expertise needed to perform certain tasks. This effort was directed toward developing improved models of experts based on goal-based models and toward assaying and isolating individual differences of inexperienced users in order to adapt the software interface to these individual differences. Results show that inexperienced users and that slower users were more variable in their search times than experienced users and that slower users selected more inefficient search commands. Two performance-based and one cognitive-based command selection aid improved search performance and strategies of slower, inexperienced users. Since spatial and verbal ability were found to correlate of slower, positively with search strategies, inexperienced users learned to select fewer and more efficient commands when provided with spatial augmentation (graphic presentation). Keywords: Educational psychology, Cognitive psychology, Human-computer interaction.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 1990
- Accession Number
- ADA226906
Entities
People
- Brian C. Hayes
- Jay Elkerton
- Kim J. Vicente
- Robert C. Williges
Organizations
- Virginia Tech