Collaborative Research: Determining the Fundamental Cognitive Properties of Decision Making

项目的非技术性描述在一个人做出的几乎每一个决定中，他们都被要求组合多个，有时是相互冲突的来源信息。因此，了解人们如何使用这些多个信息源是理解和预测选择的基础。心理学中既定的方法允许在某些情况下检查这些过程。例如，为了探索决策阶段，决策者可能会被要求描述她在做出选择时的思维过程，这一描述被用来告知研究人员。在许多情况下，无法访问有关选择过程的直接信息。例如，决策者可以搜索她的记忆以找到可用于在选项之间进行选择的信息。当记忆搜索速度很快时，人们很少清楚地了解记忆是如何被访问和使用的。为了能够在最广泛的情况下根据多种信息来源调查决策，首席调查员将把基于数学认知模型的强大方法与标准决策研究方法结合起来。本研究将实现三个目标：(1)了解决策过程中多个信息源是如何组合的；(2)对不同决策任务的基本过程进行新的实证检验；(3)在新的实证结果的基础上，对顶级决策理论进行严格的比较。这些结果将为决策者提供信息，允许评估决策效率，并使更好的选择行为模型成为可能。多年来，人们提出了几个决策模型，这些模型可以解释人类决策中的许多典型结果，使用选择准确性和响应时间输出衡量标准。然而，对于潜在的认知机制还没有达成明确的一致意见。这些模型通常可以通过对导致决策的过程的强烈影响来区分。具体地说，这些模型意味着(A)如何搜索信息，(B)何时停止这种信息搜索，以及(C)如何整合所获得的信息以做出决定。尽管如此，分歧依然存在。这在一定程度上是由于模型模仿：在没有适当的实验设计和分析的情况下，不同的理论可以做出相同的预测。例如，基于传统平均响应时间(RT)分析的推论由于模型模拟而受到限制，因为不同的决策模型可能隐含完全相同的平均响应时间模式。为了克服这一局限性，我们将把强大的系统因素技术(SFT)与传统的决策方法相结合。SFT已被成功地应用于各种知觉和认知任务中，以识别加工顺序、停止规则和加工依赖性(自上而下为a、b和c)，但应用于决策的方式非常有限。我们的研究将把SFT与判断和决策的经典方法联系起来，以提高我们对决策背后的认知过程的理解。我们的项目还将有助于改善两所州立大学本科生和研究生的专业学术发展，这两所大学传统上学生的研究机会较少。这项研究项目的方方面面，从方法论到理论发展，都将在国内和国际专业人士中进行交流。此外，这项研究将提交给高质量的同行评议期刊发表。这项拟议研究的目的之一是通过我们各自的大学新闻办公室向更广泛的受众传播研究结果。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Non-technical Description of the ProjectIn nearly every decision a person makes, they are required to combine multiple, sometimes conflicting sources information. Thus, understanding how people use these multiple sources of information is fundamental to understanding and predicting choices. Established approaches within psychology allow examination these processes in some situations. For example, to explore decision stages, a decision-maker may be asked to describe her thought process when making a choice, and that description is used to inform the researcher. In many situations, direct information about the choice processes is not accessible. For example, a decision maker may search her memory to find the information that could be used for choosing between options. When memory search is fast, people rarely have clear insight into how the memories were accessed and used. To allow for investigating decisions based on multiple sources of information across the widest range of situations, the principal investigators will integrate a powerful methodology based on mathematical cognitive modelling with standard decision-making research methodologies. The research will accomplish three objectives: (1) to gain an important understanding how multiple sources of information are combined during decision making, (2) conduct new empirical tests of the fundamental process across different decision making tasks, and (3) rigorously compare among the top decision making theories based on the new empirical findings. These results will inform decision makers, allow assessment of decision making efficiency, and enable better models of choice behavior.Technical DescriptionOver the years, several decision-making models were proposed that can account for many of the typical findings in human decision making, using both choice accuracy and response time output measures. However, no clear agreement about the underlying cognitive mechanism has been reached. These models can often be distinguished by strong implications about the processes that lead to a decision. Specifically, these models imply (a) how information is searched for, (b) when this information search is stopped, and (c) how the acquired information is integrated to reach the decision. Nonetheless, the disagreement remains. In part this is due to model mimicking: Without appropriate experimental design and analysis, different theories can make equivalent predictions. For example, inferences based on traditional mean response time (RT) analysis are limited due to model mimicking, as different decision-making models can imply exactly the same mean response time patterns. To overcome this limitation, we will integrate the powerful systems factorial technology (SFT) with traditional decision-making methods. SFT has been successfully applied in a wide range of perceptual and cognitive tasks to identify processing order, stopping rule and process dependency (a, b, and c from above), but has only been applied to decision making in very limited way. Our research will link SFT to the classical methods in judgment and decision making to improve our understanding of the cognitive processes underlying decision making. Our project will also contribute to improving the professional academic development of undergraduate and graduate students at two state universities that traditionally have fewer research opportunities for students. All aspects of this research project, from methodology to theoretical development, will be communicated at national and international professional Furthermore, the research will be submitted for publication in high-quality, peer-reviewed journals. One of the aims of the proposed research is to disseminate the findings to a broader audience through our respective university press offices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.