Signal Detection-Based Analyses of Stimulus Control

基于信号检测的刺激控制分析

• 批准号: 6822425
• 负责人: RICHARD W SERNA
• 金额: $ 13.03万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-05-01 至 2009-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6822425
• 关键词: behavior test; behavioral /social science research tag; choice; clinical research; decision making; discrimination learning; human subject; mental retardation; motivation; sensory signal detection

Project 3 will focus on as yet incompletely understood interactions between stimulus variables and motivational variables in the development of stimulus control. Making use of classic paradigms in discrimination learning, our research will investigate variables and variable interactions that may help to account for the slow and/or inconsistent learning outcomes that are frequently observed in persons with intellectual disabilities. Whereas such deficits have historically been attributed to inattention, overly broad and/or narrow attending, and/or lack of motivation, our hypothesis is that protracted discrimination learning failures can occur in individuals who would be classified as both attentive and well-motivated by traditional standards. We propose that protracted failures result when teachers/experimenters program contingencies that are indiscriminable from the perspective of the learner. The proposed project is inspired by numerous findings from our laboratories and by current quantitative theoretical analyses of learning processes that have their roots in signal detection theory (SDT). Such quantitative approaches are virtually unstudied in disability research, but we believe that they have at least two significant advantages. First, they offer a highly structured, empirically verified method for analyzing the degree to which cdtical elements of programmed contingencies are discriminable. Second, there are effective quantitative techniques for assessing the degree to which learning failures are the result of biases due to stimulus and/or reinforcer variables. Together, we believe that these two features of SDT-based analyses will help to shed light on certain longstanding problems in the analysis of learning processes of individuals with intellectual disabilities. We suggest also that a quantitative SDT-based methodology has natural advantages for supporting more effective teaching interactions for such individuals. To demonstrate these advantages, we will employ another quantitative method, the percentile-scheduling approach. By combining SDT-based analyses with percentile approaches, our goal is to establish a foundation for effective computer-based management of discrimination learning procedures of the type that are now used in educational intervention for persons with disabilities.

项目3将集中在尚未完全理解的刺激变量和动机变量之间的相互作用，在刺激控制的发展。利用歧视学习的经典范例，我们的研究将调查变量和变量的相互作用，可能有助于解释智力残疾人士经常观察到的缓慢和/或不一致的学习结果。虽然这种赤字历来被归因于注意力不集中，过于广泛和/或狭窄的出席，和/或缺乏动机，我们的假设是，长期的歧视学习失败可能发生在个人谁将被归类为既注意和良好的动机，传统标准。我们建议，长期失败的结果时，教师/实验程序的偶然性，是不可区分的学习者的角度来看。该项目的灵感来自于我们实验室的众多发现，以及目前对信号检测理论（SDT）的学习过程的定量理论分析。这种定量方法在残疾研究中几乎没有研究过，但我们相信它们至少有两个显著的优势。首先，他们提供了一个高度结构化的，经验验证的方法来分析的程度，其中的关键因素的程序意外是可辨别的。第二，有有效的量化技术来评估程度 学习失败是由于刺激和/或干扰变量引起的偏差的结果。总之，我们相信，这两个特点的SDT为基础的分析将有助于阐明某些长期存在的问题，在分析个人的学习过程中，智力残疾。我们还建议，定量SDT为基础的方法有自然的优势，支持更有效的教学互动，为这些人。为了证明这些优点，我们将采用另一种定量方法，即战斗调度方法。通过将基于SDT的分析与百分位数方法相结合， 我们的目标是建立一个基础，以便对歧视学习程序进行有效的计算机管理，这种程序目前正用于对残疾人的教育干预。