Related Experiment Videos
Effects of diversity in cognitive restructuring skills on human-computer performance
1University of Central Florida, Industrial Engineering and Management Systems Department, Orlando 32816.
Ergonomics
|April 1, 1994
Summary
Field-dependent individuals can improve computer performance by structuring information. Providing time to learn system structure helps control for task information organization effects on performance.
Area of Science:
- Human-Computer Interaction
- Cognitive Psychology
- Information Science
Background:
- Field-dependent individuals often exhibit lower technical aptitude in hierarchical computer environments.
- Differences in memory organization may explain variations in computer performance.
- Information structuring requirements can influence task performance.
Purpose of the Study:
- To investigate methods for enhancing computer performance in field-dependent individuals.
- To explore the impact of manipulated information structuring on task efficiency.
- To test a conceptual model explaining memory organization and computer performance differences.
Main Methods:
- A conceptual model with three dimensions (task complexity, integration quality, differentiation level) was proposed.
- Thirty-six subjects (18 field-dependent, 18 field-independent) participated.
- Subjects performed information search tasks under experimenter-defined and self-defined structure conditions.
Main Results:
- The study confirmed that task information organization significantly affects computer performance time.
- Providing dedicated time for system structure acquisition mitigated performance differences.
- Field-independent individuals did not show significant performance changes across conditions.
Conclusions:
- Computer performance in hierarchical environments can be optimized for field-dependent users through structured learning.
- Acquiring a system's structure is crucial for mitigating performance disparities.
- The proposed conceptual model provides a framework for understanding cognitive factors in human-computer interaction.