Acquisition and Transfer of Automatic Skills

自动技能的获取和转移

• 批准号: 9410406
• 负责人: Gordon Logan
• 金额: $ 19.85万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1994
• 资助国家: 美国
• 起止时间: 1994-10-01 至 1997-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9410406&HistoricalAwards=false
• 关键词: Acquisition; Transfer; Automatic; Skills

The proposed research will examine the role of attention in acquiring automatic skills and transferring them within and between tasks. The main theoretical focus will be on developing a theory that explains how acts of attention during training encode traces into memory to build up a task-relevant knowledge base, and how acts of attention at transfer retrieve traces from memory to support automatic performance. The theory will build on existing theories of attention and automaticity, extending and generalizing them. The main empirical focus will be on visual search, which is a dominant paradigm in research on attention and automaticity that has important practical implications (e.g., for driving, navigation, and supervisory control). Experiments will address how automatic skills acquired during training on visual search transfer to and from other tasks (counting and categorization) performed on displays similar to and different from the ones experienced during training. The proposed research is significant theoretically and practically. The ability to perform automatically is a major factor underlying skilled performance and it is important to understand it better. The proposed research will increase our understanding by distinguishing between competing theories of automatization and integrating previously unrelated theories of automatization, attention, and categorization. The experimental and theoretical results on transfer will have important implications for education and industrial training, providing a principled way to determine whether experience gained in one setting (e.g., the classroom) will generalize to another (e.g., the workplace) and a principled way to design training programs and select training examples to maximize generalization and optimize skilled performance.

这项拟议的研究将考察注意力在获得自动技能以及在任务内部和任务之间转移这些技能方面的作用。主要的理论重点将是发展一种理论，解释训练期间的注意行为如何将痕迹编码到记忆中以建立与任务相关的知识库，以及转移时的注意行为如何从记忆中检索痕迹以支持自动执行。该理论将建立在现有的注意和自动性理论的基础上，对它们进行扩展和概括。主要的实证重点将放在视觉搜索上，这是研究注意力和自动性的主要范式，具有重要的实际意义（例如，驾驶、导航和监督控制）。实验将解决在视觉搜索训练中获得的自动技能如何转移到其他任务（计数和分类）中，这些任务在与训练期间经历的相似或不同的显示器上执行。本文的研究具有重要的理论和实践意义。自动执行的能力是熟练执行的一个主要因素，更好地理解它很重要。本文提出的研究将通过区分相互竞争的自动化理论和整合先前不相关的自动化、注意和分类理论来增加我们的理解。关于迁移的实验和理论结果将对教育和工业培训具有重要意义，为确定在一种环境（如课堂）中获得的经验是否可以推广到另一种环境（如工作场所）提供了一种原则性的方法，并为设计培训计划和选择培训实例提供了一种原则性的方法，以最大限度地推广和优化技能表现。