计算机科学
结构化
信息过载
背景(考古学)
相关性(法律)
认知负荷
任务(项目管理)
认知
人机交互
光学(聚焦)
软件
万维网
心理学
工程类
系统工程
古生物学
物理
财务
光学
政治学
法学
经济
生物
程序设计语言
神经科学
作者
Paula Gauselmann,Yannick Runge,Christian Jilek,Christian Frings,Heiko Maus,Tobias Tempel
标识
DOI:10.1080/10447318.2022.2041882
摘要
Information overload resulting from the ever faster-growing mass of digital data makes knowledge work more and more complex. Being able to not get distracted and focus on what is currently relevant consumes valuable cognitive resources. Support by intelligent assistance software might alleviate this problem. We report two experiments that addressed this challenge by examining how context-based assistance may provide more available cognitive resources. Experiment 1 focused on work within a single context. Results indicate that external relevance classification can improve memory for content classified as currently more relevant. Experiment 2 focused on switching between two different contexts and shows that cognitive performance after context switches can be enhanced by context-specific structuring and saving a previous task status. Taken together, these results clearly demonstrate that automatic external information structuring by intelligent assistance software can protect knowledge workers from information overload by lightening their cognitive load and, thus, help improve cognitive performance.
科研通智能强力驱动
Strongly Powered by AbleSci AI