Cognitive Mechanisms and Optimization Strategies in Interactive Evolutionary Design Based on Cognitive Load Theory

Abstract

AbstractThe interactive evolutionary design (IED) approach is a human-centered design method with the design domain, which requires users to evaluate their overall satisfaction with evolutionary individuals. However, due to repeated and continuous interactions, users experience varying degrees of physical and psychological fatigue. How to alleviate user fatigue has become an important research topic. Some researchers focus on algorithm mechanisms, evaluation methods, and interface design improvements, whereas the relationship between user cognitive characteristics and interaction design has been less studied. This paper analyzed users’ cognitive mechanisms and proposed optimization strategies for the IED based on cognitive load theory. First, user cognitive activities were identified during different stages, and the type of cognitive load was determined in each cognitive task. Second, combined with cognitive load effects, we proposed the optimization strategies for intrinsic, extraneous, and germane cognitive loads. Third, we adopted two existing algorithms and developed corresponding design systems to discuss the effectiveness of the proposed strategies. To achieve this, ten subjects were invited to operate systems, with experimental data recorded and cognitive load levels measured. The main findings from this paper highlighted that the proposed strategies effectively reduce the extraneous cognitive load and improve the efficiency of germane cognitive load.KeywordsCognitive load theoryInteractive evolutionary designHuman-computer interaction