认知风格对归类不确定时特征推理的影响
|
摘要
当前关于类别的研究主要包括类别形成的研究与特征推理的研究。归类不确定时特征推理是特征推理的重要组成部分,因此了解归类不确定时特征推理具有重要的理论意义。
目前关于归类不确定时的特征推理的研究主要有两种观点:基于类别和基于特征联结。基于类别的特征推理存在两种理论模型:单类说和理性模型,这两种理论都认为归类不确定时,人们会先将新事物进行归类,再根据靶类别推理。两者的区别在于:单类说认为人们推理时只考虑靶类别的信息,而理性模型认为人们考虑靶类别信息的同时也会考虑非靶类别信息。基于特征联结的特征推理是依据呈现的样例的有关特征与预测特征之间联结的频次进行推理。
代表性概念首次在单类说中提出,Murphy和Ross证明影响人们特征推理的因素是代表性,而不是诊断性。张娟、莫雷的研究提出代表性包括目标内代表性和类别内代表性两个概念,目标内代表性指的是预测特征在靶类别内目标成员中的代表性,即预测特征在靶类别内的目标项目所占的比例;类别内代表性即为Murphy等人提出的代表性概念,即预测特征在靶类别内具有某种特征项目所占的比例。但是他们的研究设计却混淆了两种代表性的影响作用,未能将其分离。吴珺的研究证明了目标内代表性的存在,并将目标内代表性和类别内代表性的作用相分离。但是她的研究结果表明,一部分被试群体依据目标内代表性推理,一部分被试群体依据类别内代表性推理,两者人数没有显著差异,什么原因影响被试的选择,研究未做进一步的探讨。
有关认知风格的研究表明认知风格会对图形推理产生影响,场独立型被试解决问题时更倾向于从问题相关项出发,而场依存型被试更倾向于从整体出发,易受备选项的影响。本研究认为场独立型被试倾向于选择目标内代表性为推理依据,场依存型被试倾向于选择类别内代表性为推理依据,为此本研究设计了两个实验来证明假设。实验一分别控制目标内和类别内代表性的均衡条件,考察认知风格是否会影响特征推理。实验二采用眼动实验,通过分析被试推理过程中的眼动指标,进一步探讨认知风格对特征推理的影响机制。
结果表明:(1)当目标内代表性均衡,类别内代表性不均衡时,场独立型可能会倾向于随机挑选一种代表性作为特征推理的依据,场依存型可能会倾向于挑选类别内代表性;当目标内代表性不均衡,类别内代表性均衡时,场独立型倾向于选择目标内代表性特征推理,场依存型倾向于随机选择一种代表性作为特征推理的依据;当目标内代表性均衡,类别内代表性均衡时,两种认知风格差异不大,被试倾向于随机选择一种代表性作为特征推理的依据;当目标内代表性不均衡,类别内代表性不均衡时,场独立型更倾向于选择目标内代表性作为特征推理的依据,场依存型倾向于挑选类别内代表性特征推理。(2)在眼动指标上,被试在靶类别与非靶类别,场独立型与场依存型在目标内项目,场独立型与场依存型在类别内项目上的眼动指标均有差异。
实验证明归类不确定时特征推理确实会受到认知风格的影响,结果与预期一致。
Category research included category formation and feature prediction. And the research of feature prediction when categorization is uncertain is an important part of feature prediction. There are theoretical senses to inspect how people induce when categorization is uncertain.
At present the arguments of the feature prediction when categorization is uncertain were mainly between category-based induction and feature association induction. And category-based induction included single-category theory and rational model. Both theories agree that when categorization is uncertain, people will choose a target category, then make the induction. The difference between the two theories is that single-category theory agrees people only pay attention to the feature properties in target category, while rational model believes that people are not only concerned with the feature properties of the target category, but also the feature properties of non-target categories. Feature association induction agrees the feature associations between the feature of example and the predicted feature.
Murphy and Ross’s research put forward representativeness, proved representativeness impacted feature predicting, but diagnostic did not. Zhang Juan and Mo Lei raised representativeness included category representativeness and objective representativeness. One is the feature proportion of the objective members in target category, called objective representativeness. The other is the feature proportion of all members in target category, called category representativeness. But both of them didn’t separate the roles on feature predicting. Wu Jun certified the presence of category representativeness, and separated the roles between objective representativeness and category representativeness. But the study didn’t reveal the result of people’s chooses.
The study of cognitive style revealed that cognitive style impacted picture predicting, field independences tended to the relevant project, while field dependences tended to the whole project. Our study consider that cognitive style impact the process of prediction. Field independences will choose objective representativeness, while field dependences will choose category representativeness. Experiment One explores whether cognitive style will impact feature prediction based on under four conditions. In Eye movement experiment, we do further exploration on the role mechanism.
The results indicate that when objective representativeness balanced and category representativeness discord, field dependents prior to choosing either of them randomly, field independents prior to choosing category representativeness; when objective representativeness discord and category representativeness balanced, field dependents prior to choosing category representativeness, field independents prior to choosing either of them randomly; when both objective representativeness and category representativeness balanced, both field independents and field dependents choose one of them randomly; when both objective representativeness and category representativeness discord, field dependents prior to choosing category representativeness, field independents prior to choosing category representativeness. In Eye movement experiment, there exists difference between target categories and non-target categories, objective items and category items. The study indicate that cognitive style will impact feature prediction when categorization is uncertain, it meets anticipations.
目前关于归类不确定时的特征推理的研究主要有两种观点:基于类别和基于特征联结。基于类别的特征推理存在两种理论模型:单类说和理性模型,这两种理论都认为归类不确定时,人们会先将新事物进行归类,再根据靶类别推理。两者的区别在于:单类说认为人们推理时只考虑靶类别的信息,而理性模型认为人们考虑靶类别信息的同时也会考虑非靶类别信息。基于特征联结的特征推理是依据呈现的样例的有关特征与预测特征之间联结的频次进行推理。
代表性概念首次在单类说中提出,Murphy和Ross证明影响人们特征推理的因素是代表性,而不是诊断性。张娟、莫雷的研究提出代表性包括目标内代表性和类别内代表性两个概念,目标内代表性指的是预测特征在靶类别内目标成员中的代表性,即预测特征在靶类别内的目标项目所占的比例;类别内代表性即为Murphy等人提出的代表性概念,即预测特征在靶类别内具有某种特征项目所占的比例。但是他们的研究设计却混淆了两种代表性的影响作用,未能将其分离。吴珺的研究证明了目标内代表性的存在,并将目标内代表性和类别内代表性的作用相分离。但是她的研究结果表明,一部分被试群体依据目标内代表性推理,一部分被试群体依据类别内代表性推理,两者人数没有显著差异,什么原因影响被试的选择,研究未做进一步的探讨。
有关认知风格的研究表明认知风格会对图形推理产生影响,场独立型被试解决问题时更倾向于从问题相关项出发,而场依存型被试更倾向于从整体出发,易受备选项的影响。本研究认为场独立型被试倾向于选择目标内代表性为推理依据,场依存型被试倾向于选择类别内代表性为推理依据,为此本研究设计了两个实验来证明假设。实验一分别控制目标内和类别内代表性的均衡条件,考察认知风格是否会影响特征推理。实验二采用眼动实验,通过分析被试推理过程中的眼动指标,进一步探讨认知风格对特征推理的影响机制。
结果表明:(1)当目标内代表性均衡,类别内代表性不均衡时,场独立型可能会倾向于随机挑选一种代表性作为特征推理的依据,场依存型可能会倾向于挑选类别内代表性;当目标内代表性不均衡,类别内代表性均衡时,场独立型倾向于选择目标内代表性特征推理,场依存型倾向于随机选择一种代表性作为特征推理的依据;当目标内代表性均衡,类别内代表性均衡时,两种认知风格差异不大,被试倾向于随机选择一种代表性作为特征推理的依据;当目标内代表性不均衡,类别内代表性不均衡时,场独立型更倾向于选择目标内代表性作为特征推理的依据,场依存型倾向于挑选类别内代表性特征推理。(2)在眼动指标上,被试在靶类别与非靶类别,场独立型与场依存型在目标内项目,场独立型与场依存型在类别内项目上的眼动指标均有差异。
实验证明归类不确定时特征推理确实会受到认知风格的影响,结果与预期一致。
Category research included category formation and feature prediction. And the research of feature prediction when categorization is uncertain is an important part of feature prediction. There are theoretical senses to inspect how people induce when categorization is uncertain.
At present the arguments of the feature prediction when categorization is uncertain were mainly between category-based induction and feature association induction. And category-based induction included single-category theory and rational model. Both theories agree that when categorization is uncertain, people will choose a target category, then make the induction. The difference between the two theories is that single-category theory agrees people only pay attention to the feature properties in target category, while rational model believes that people are not only concerned with the feature properties of the target category, but also the feature properties of non-target categories. Feature association induction agrees the feature associations between the feature of example and the predicted feature.
Murphy and Ross’s research put forward representativeness, proved representativeness impacted feature predicting, but diagnostic did not. Zhang Juan and Mo Lei raised representativeness included category representativeness and objective representativeness. One is the feature proportion of the objective members in target category, called objective representativeness. The other is the feature proportion of all members in target category, called category representativeness. But both of them didn’t separate the roles on feature predicting. Wu Jun certified the presence of category representativeness, and separated the roles between objective representativeness and category representativeness. But the study didn’t reveal the result of people’s chooses.
The study of cognitive style revealed that cognitive style impacted picture predicting, field independences tended to the relevant project, while field dependences tended to the whole project. Our study consider that cognitive style impact the process of prediction. Field independences will choose objective representativeness, while field dependences will choose category representativeness. Experiment One explores whether cognitive style will impact feature prediction based on under four conditions. In Eye movement experiment, we do further exploration on the role mechanism.
The results indicate that when objective representativeness balanced and category representativeness discord, field dependents prior to choosing either of them randomly, field independents prior to choosing category representativeness; when objective representativeness discord and category representativeness balanced, field dependents prior to choosing category representativeness, field independents prior to choosing either of them randomly; when both objective representativeness and category representativeness balanced, both field independents and field dependents choose one of them randomly; when both objective representativeness and category representativeness discord, field dependents prior to choosing category representativeness, field independents prior to choosing category representativeness. In Eye movement experiment, there exists difference between target categories and non-target categories, objective items and category items. The study indicate that cognitive style will impact feature prediction when categorization is uncertain, it meets anticipations.
引文
陈琳. (2007).类别不确定下的特征推理方式研究.硕士学位论文,华南师范大学.
陈琳,莫雷. (2007).归类不确定时人们的推理方式研究.心理学探新,1, 34-40.
陈琳,莫雷. (2009).类别不确定下的特征推理是基于类别还是基于特征联结.心理学报,2, 103-113.
何燕. (2009).大学生进行归类不确定时特征推理过程的眼动研究.硕士学位论文,湖南师范大学.
黄晓霞. (2002).认知方式的实验研究——场依存性特征对计算机辅助教学与常规教学效果的影响硕士学位论文,天津师范大学.
靖新巧. (2008).大学生场认知方式对图形推理影响的眼动研究.硕士学位论文,贵州师范大学.
李路荣. (2008).中小学生进行几何图形推理过程的眼动研究.硕士学位论文,湖南师范大学.
李寿欣,宋广文. (1999).西方认知方式研究概观.国外社会科学, 1, 19-24.
刘志雅. (2008).不同维度特征的共存对归类不确定性特征推理的影响.心理学报,1, 37-46.
莫雷,赵海燕. (2002).维度的结合与分离对归类不确定性预测的影响.心理学报, 34, 470-479.
王有智. (2003).认知风格、内外向性、情绪稳定性与图形推理效果的关系.心理科学, 26, 1077-1081.
王有智,欧阳仑. (2004).大学生不同认知方式对图形推理水平的影响——兼谈认知过程中的人格作用.心理科学, 27, 389-391.
王峻. (2001).初中学生场认知方式特点的研究.硕士学位论文,苏州大学.
王墨耘,莫雷. (2005).归类不确定情景下特征推理的综合条件概率模型.心理学报,4, 482-490.
沃建中,李琪,田宏杰. (2006).不同推理水平儿童在图形推理任务中的眼动研究.心理发展与教育, 3.
沃建中,闻莉,周少贤. (2004).认知风格理论研究的进展.心理与行为研究, 2, 597-602.
吴珺. (2009).归类不确定情境下特征推理的简捷启发式策略研究.硕士学位论文,江西师范大学.
谢斯骏,张厚粲. (1988).认知方式:一个人格维度的实验研究.北京:北京师范大学出版社
张娟,莫雷. (2008).归类不确定情境下特征预测的理性模型研究.心理科学,1, 40-44.
张琳. (2009).类别学习中的类别使用效应.硕士学位论文,天津师范大学.
张卫东. (1995).大学生场依存型——场独立性认知方式分析.心理科学, 18, 29-33.
郑海燕. (2006).类别特征的相似性与竞争性对特征推理的影响研究.博士学位论文,华南师范大学.
Anderson. (1991). The adaptive nature of human categorization. Psychological Review, 23(1), 409-429.
Wisniewski,E J. (1995). Prior knowledge and functionally relevant features in concept learning. Journal of Experimental Psychology:Learning, Memory, and Cognition,21, 449-468.
Murphy, G L. (1982). Cue validity and levels of categorization. Psychological Bulletin, 91, 174-177.
Lagnado ,D. A.,& Shanks, D. R. (2003). The Influence of Hierarchy on Probability Judgment. Cognition, 89, 157-178.
Malt, B. C., & Murphy, G. L. (1995). Predicting features for members of natural categories when categories is uncertain. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 646-661.
Medin. (1982). Correlated symptoms and simulated medical classification. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 37-50.
Murphy, G. L., & Ross, B. H. (1994). Predietions from uncertain categorization. Cognitive Psychology, 27, 148-193.
Murphy, G. L.,& Ross, B. H. (2005). The two faces of typicality in category-based induction. Cognition, 95, 175-200.
Rosch, E., & Mervis, C. B. (1975). Family resemblance: Studies in the internal structure of categories. Cognitive Psychology, 7, 573-605.
Ross, B. H., & Murphy,G. L. (1996). Category based predictions: Influences of uncertainty and feature associations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22.
Verde, M .F., & Ross, B. H. (2005). Influnce of multiple categories in inductive inference. Memory&Cognition, 33, 479.
陈琳,莫雷. (2007).归类不确定时人们的推理方式研究.心理学探新,1, 34-40.
陈琳,莫雷. (2009).类别不确定下的特征推理是基于类别还是基于特征联结.心理学报,2, 103-113.
何燕. (2009).大学生进行归类不确定时特征推理过程的眼动研究.硕士学位论文,湖南师范大学.
黄晓霞. (2002).认知方式的实验研究——场依存性特征对计算机辅助教学与常规教学效果的影响硕士学位论文,天津师范大学.
靖新巧. (2008).大学生场认知方式对图形推理影响的眼动研究.硕士学位论文,贵州师范大学.
李路荣. (2008).中小学生进行几何图形推理过程的眼动研究.硕士学位论文,湖南师范大学.
李寿欣,宋广文. (1999).西方认知方式研究概观.国外社会科学, 1, 19-24.
刘志雅. (2008).不同维度特征的共存对归类不确定性特征推理的影响.心理学报,1, 37-46.
莫雷,赵海燕. (2002).维度的结合与分离对归类不确定性预测的影响.心理学报, 34, 470-479.
王有智. (2003).认知风格、内外向性、情绪稳定性与图形推理效果的关系.心理科学, 26, 1077-1081.
王有智,欧阳仑. (2004).大学生不同认知方式对图形推理水平的影响——兼谈认知过程中的人格作用.心理科学, 27, 389-391.
王峻. (2001).初中学生场认知方式特点的研究.硕士学位论文,苏州大学.
王墨耘,莫雷. (2005).归类不确定情景下特征推理的综合条件概率模型.心理学报,4, 482-490.
沃建中,李琪,田宏杰. (2006).不同推理水平儿童在图形推理任务中的眼动研究.心理发展与教育, 3.
沃建中,闻莉,周少贤. (2004).认知风格理论研究的进展.心理与行为研究, 2, 597-602.
吴珺. (2009).归类不确定情境下特征推理的简捷启发式策略研究.硕士学位论文,江西师范大学.
谢斯骏,张厚粲. (1988).认知方式:一个人格维度的实验研究.北京:北京师范大学出版社
张娟,莫雷. (2008).归类不确定情境下特征预测的理性模型研究.心理科学,1, 40-44.
张琳. (2009).类别学习中的类别使用效应.硕士学位论文,天津师范大学.
张卫东. (1995).大学生场依存型——场独立性认知方式分析.心理科学, 18, 29-33.
郑海燕. (2006).类别特征的相似性与竞争性对特征推理的影响研究.博士学位论文,华南师范大学.
Anderson. (1991). The adaptive nature of human categorization. Psychological Review, 23(1), 409-429.
Wisniewski,E J. (1995). Prior knowledge and functionally relevant features in concept learning. Journal of Experimental Psychology:Learning, Memory, and Cognition,21, 449-468.
Murphy, G L. (1982). Cue validity and levels of categorization. Psychological Bulletin, 91, 174-177.
Lagnado ,D. A.,& Shanks, D. R. (2003). The Influence of Hierarchy on Probability Judgment. Cognition, 89, 157-178.
Malt, B. C., & Murphy, G. L. (1995). Predicting features for members of natural categories when categories is uncertain. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21, 646-661.
Medin. (1982). Correlated symptoms and simulated medical classification. Journal of Experimental Psychology: Learning, Memory, and Cognition, 8, 37-50.
Murphy, G. L., & Ross, B. H. (1994). Predietions from uncertain categorization. Cognitive Psychology, 27, 148-193.
Murphy, G. L.,& Ross, B. H. (2005). The two faces of typicality in category-based induction. Cognition, 95, 175-200.
Rosch, E., & Mervis, C. B. (1975). Family resemblance: Studies in the internal structure of categories. Cognitive Psychology, 7, 573-605.
Ross, B. H., & Murphy,G. L. (1996). Category based predictions: Influences of uncertainty and feature associations. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22.
Verde, M .F., & Ross, B. H. (2005). Influnce of multiple categories in inductive inference. Memory&Cognition, 33, 479.