Collaborative Research: Action Dynamics as an Index of Learning and Generalization

协作研究：行动动力学作为学习和泛化的指标

• 批准号: 0912496
• 负责人: Michael Spivey
• 金额: $ 7.87万
• 依托单位: University of California - Merced
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-17 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0912496&HistoricalAwards=false
• 关键词: Collaborative; Research; Action; Dynamics; Index

Traditional theories in cognitive science often see mental processing and motor execution as separate domains of psychological investigation. In opposition to this, the past half-century has seen a resurgence of continuous and dynamical approaches to the mind, arguing for a smooth transition from cognitive into motor subsystems. This predicts that the dynamic characteristics of observable action will directly reflect underlying thought processes. In support of this, much recent research has shown that continuous tracking of motor movement can provide rich information about the mental processing giving rise to it. With support of the National Science Foundation, Drs. Rick Dale and Michael Spivey will explore how action dynamics can shed light on human learning. By tracking computer-mouse trajectories, Dale and Spivey aim to uncover how action dynamics evolve as people learn. Several multi-choice, computer-based experiments will employ tasks of varying complexity, from simple associative learning (e.g., pairing symbols) to acquiring knowledge from text. Such measures would supplement traditional performance variables based on discrete answers. These studies can also provide a further understanding of the intimate connection between thought and action. In addition, the work can provide insights about how best to adapt computer systems for education: Through automatic analysis of computer-mouse movements, these adapted systems could detect such states as lack of learner confidence or deep understanding, and could appropriately respond to these potential deficits in real time, and thereby enhance learning.

认知科学的传统理论通常将心理加工和运动执行视为心理研究的独立领域。与此相反，在过去的半个世纪里，连续和动态的思维方法重新兴起，主张从认知子系统到运动子系统的平稳过渡。这预示着可观察到的行为的动态特征将直接反映潜在的思维过程。为了支持这一点，最近的许多研究表明，对运动动作的持续跟踪可以提供有关导致运动动作的心理处理的丰富信息。在美国国家科学基金会的支持下，Rick Dale博士和Michael Spivey博士将探索动作动力学如何揭示人类学习。通过跟踪计算机鼠标轨迹，Dale和Spivey旨在揭示人们学习时动作动态是如何演变的。几个多选择，基于计算机的实验将采用不同复杂性的任务，从简单的联想学习（例如，配对符号）从文本中获取知识。这些措施将补充基于离散答案的传统业绩变量。这些研究还可以进一步了解思想和行动之间的密切联系。此外，这项工作可以提供有关如何最好地适应计算机系统的教育见解：通过计算机鼠标运动的自动分析，这些适应系统可以检测到学习者缺乏信心或深度理解等状态，并可以在真实的时间内适当地应对这些潜在的缺陷，从而提高学习效果。