Conflict Paradigms and the Instance Theory of Automatization

这项研究将探讨注意力在 控制和克服自动化带来的冲突 处理无关信息。 自动冲突 处理在现实世界的情况下是显而易见的， 当前的目标与已建立的习惯背道而驰，例如 从通常的回家路线出发，在商店停下来。 的 Stroop任务提供了一个实验室的例子：人们被要求 名称的颜色，其中的话，必须克服的 自动阅读反应时，这个词本身的名称 冲突的颜色（例如，红色用绿色书写）。 性能 Stroop任务及其许多变体（例如，决定是否3 + 4 = 12为真）提供了一个主要的数据库， 注意力和自动性必须解释。 这项研究将 应用洛根的自动性实例理论，发展到 解释技能的获得，冲突的范式。 实例理论假设新手的表现是基于 用于执行任务的通用算法， 实践中，该算法逐渐被内存所取代， 具体的解决方案。 此学习过程在 用精确的数学方式来描述理论。 实例理论 比其他技能理论更能解释学习 收购，因为它占整个变化 反应时间的分布，而不仅仅是平均表现。 就目前而言，实例理论在以下方面做出了错误的预测： 冲突范式，预测反应时间不会减慢， 错误率接近100%，与大量的 实验表明反应时间显著减慢， 错误率略有增加。 这项研究将开发 理论来克服这个问题，然后测试新的 发展理念 理论发展将涉及假设两个 不同的表征，感知表征和 概念性的表达，这些表达通过过程结合在一起， 注意力。 这项研究将包括三个系列的实验。 第一 将研究将知觉表征与 概念表征;第二个将分离知觉 第三个是概念性的表达;第三个是长期的研究。 通过检查学习的约束过程的长期后果 方面的影响. 本研究将研究结合过程 理论上使用计算机模拟学习过程 将实例理论与其他现有的 技能获取

This research will investigate the role of attention in controlling and overcoming conflict engendered by automatic processing of irrelevant information. Conflict from automatic processing is apparent in real-world situations in which our current goals run counter to established habits, such as departing from the usual route home to stop at the store. The Stroop task provides a laboratory example: People are asked to name the color in which words are presented and must overcome the automatic reading response when the word itself names a conflicting color (e.g., RED written in green). Performance on the Stroop task and its many variations (e.g., deciding whether 3 + 4 = 12 is true) provides a major data base which theories of attention and automaticity must explain. This research will apply Logan's instance theory of automaticity, developed to account for skill acquisition, to conflict paradigms. The instance theory assumes that novice performance is based on a general algorithm for performing the task and that, with practice, the algorithm is gradually replaced by memory for specific solutions. This learning process is modeled in the theory in a precise mathematical fashion. The instance theory accounts for learning better than other theories of skill acquisition because it accounts for changes in the entire distribution of reaction times, not just average performance. As it stands, the instance theory makes incorrect predictions in conflict paradigms, predicting no slowing of reaction time and an error rate close to 100%, in contrast to vast numbers of experiments which show a substantial slowing in reaction time and a slight increase in error rate. This research will develop the theory to overcome this problem and then test the new developments. Theory development will involve assuming two different representations, a perceptual representation and a conceptual representation, that are bound together by the process of attention. The research will involve three series of experiments. The first will examine the process that binds perceptual representations to conceptual representations; the second will separate perceptual and conceptual representations; and the third will examine long- term consequences of the binding process by examining learning effects. The research will investigate the binding process theoretically using computer simulations of the learning process that compare the instance theory with other current theories of skill acquisition.