首页> 外文期刊>The Quarterly journal of experimental psychology, A. Human experimental psychology >Generation of hypotheses in Wason's 2-4-6 task: an information theory approach
【24h】

Generation of hypotheses in Wason's 2-4-6 task: an information theory approach

机译:Wason 2-4-6任务中的假设生成:一种信息论方法

获取原文
获取原文并翻译 | 示例
       

摘要

We explored the "context of discovery" in Wason's 2-4-6 task, focusing on how the first hypothesis is generated. According to Oaksford and Chater (1994a) people generate hypotheses extracting "common features", or regularities, from the available triples, but their model does not explain why some regularities contribute to the hypothesis more than do other regularities. Our conjecture is that some regularities contribute to the hypothesis more than do other regularities because people estimate the amount of information in the perceived regularities and try to preserve as much information as possible in their initial hypotheses. Experiment 1, which used two initial triples, showed that the presence of high-information relational regularities in the initial triples affected the information in the initial hypotheses more than did the presence of low-information object regularities. Experiment 2 extended the results to the classic situation in which only one initial triple is given. It also suggested that amount of information is the only aspect of the structure of the triple that affects hypotheses generation. Experiment 3 confirmed the latter finding: Although relations are commonly distinguished between first-order and higher order relations, the latter being most important for generating hypotheses (Gentner, 1983), higher order relations do have an effect on Wason's 2-4-6 task only if their presence increases information. In the conclusion we discuss the statistical soundness of human hypotheses generation processes, and we ask an unanswered question: Amount of information explains why some regularities are preferred to others, but only within a set of "nonarbitrary" regularities; there are object regularities that are rich in information content, but are considered "arbitrary", and are not used in generating hypotheses. Which formal property can distinguish between these two sets of regularities?
机译:我们探讨了Wason 2-4-6任务中的“发现背景”,重点研究了第一个假设的产生方式。根据Oaksford和Chater(1994a)的观点,人们生成了从可用三元组中提取“共同特征”或规律性的假设,但他们的模型并未解释为什么某些规律性对假设的贡献要大于其他规律性。我们的推测是,某些规则对假设的贡献要大于其他规则,因为人们会估算感知规则中的信息量,并尝试在其初始假设中保留尽可能多的信息。使用两个初始三元组的实验1表明,在初始三元组中高信息关系规则性的存在比在低信息对象规则性中的存在对信息的影响更大。实验2将结果扩展到经典情况,其中只给出了一个初始三元组。这也表明,信息量是影响假设生成的三元组结构的唯一方面。实验3证实了后者的发现:尽管通常将一阶关系与高阶关系区分开,但后者对于产生假设最为重要(Gentner,1983年),但高阶关系确实会对Wason的2-4-6任务产生影响仅当他们的存在增加信息时。在结论中,我们讨论了人类假设生成过程的统计稳健性,并且提出了一个未解决的问题:大量的信息说明了为什么某些规律性相对于其他规律性更受偏爱,而仅在一组“非任意”规律性内;有些对象规则具有丰富的信息内容,但被认为是“任意的”,不用于生成假设。哪一个形式属性可以区分这两组规则?

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号