表扬与内在动机关系的三种观点

目前表扬与内在动机的关系共有三种观点：一种观点认为表扬对内在动机有促进作用,另外一些观点则认为表扬会对内在动机产生损害。Henderlong和Lepper对这两类观点进行了整合,提出了第三种观点,他们认为不能简单地说表扬会促进还是损害内在动机,他们引入了5个概念变量(conceptual variables)：自主性(perceived autonomy)、归因方式(performance attributions)、自我效能感(competence self—efficacy)、真诚性(sincerity)、成就标准(standards and expectations),并认为这5个变量决定着表扬对内在动机的影响效果。     

内隐自尊与外显自尊对自我妨碍的影响

采用实验和问卷法研究了内隐自尊与外显自尊对自我妨碍的影响。结果表明：内隐自尊和外显自尊对自我妨碍有不同的影响。内隐自尊对行动式自我妨碍和自陈式自我妨碍均有影响,外显自尊与性别在自陈式自我妨碍上有显着的交互作用,高外显自尊的男生更倾向于做自陈式自我妨碍。     

The Case for Psychologism in Default and Inheritance Reasoning

Default reasoning occurs whenever the truth of the evidence available to the reasoner does not guarantee the truth of the conclusion being drawn. Despite this, one is entitled to draw the conclusion “by default” on the grounds that we have no information which would make us doubt that the inference should be drawn. It is the type of conclusion we draw in the ordinary world and ordinary situations in which we find ourselves. Formally speaking, ‘nonmonotonic reasoning’ refers to argumentation in which one uses certain information to reach a conclusion, but where it is possible that adding some further information to those very same premises could make one want to retract the original conclusion. It is easily seen that the informal notion of default reasoning manifests a type of nonmonotonic reasoning. Generally speaking, default statements are said to be true about the class of objects they describe, despite the acknowledged existence of “exceptional instances” of the class. In the absence of explicit information that an object is one of the exceptions we are enjoined to apply the default statement to the object. But further information may later tell us that the object is in fact one of the exceptions. So this is one of the points where nonmonotonicity resides in default reasoning. The informal notion has been seen as central to a number of areas of scholarly investigation, and we canvass some of them before turning our attention to its role in AI. It is because ordinary people so cleverly and effortlessly use default reasoning to solve interesting cognitive tasks that nonmonotonic formalisms were introduced into AI, and we argue that this is a form of psychologism, despite the fact that it is not usually recognized as such in AI. We close by mentioning some of the results from our empirical investigations that we believe should be incorporated into nonmonotonic formalisms.     

生命科学家的社会伦理责任

生命科学的发展导致了复杂的伦理道德问题,对传统的社会道德观念形成了强烈的冲击.为了最大限度地避免和消除生命科学技术的负面效应,必须制定相应的科技政策和强有力的社会伦理道德规范来约束生命科学家的行为,增强生命科学家的社会责任感,使生命科学更好地为人类造福.     

人=机器人论题的困境与出路——评勃克斯的逻辑机器哲学

计算机科学与信息技术的迅猛发展,必然引起哲学范式的转换,从而提出具有创新意义的研究纲领.逻辑机器哲学是传统哲学与现代计算机科学、信息技术的哲学思考相结合的产物.它通过人与计算机的类比,探讨用计算机模拟人类心智的可能性以及有关的哲学问题.从本质上看,勃克斯的逻辑机器哲学及其人=机器人论题建基于心智的计算观,而心智的计算观不断地受到了严重的质疑.人工生命的进化研究成果表明,心智的计算观的困境是可以摆脱的."人工意识"的计算机生成和进化系统的动力学研究,将为拯救和发展心智的计算观开辟了新的道路.     

儿童对空间位置协变的外显学习和内隐学习的比较研究

内隐学习是无意识地获得关于刺激环境的复杂知识的过程,是不同于外显学习模式的另一种学习模式。空间位置协变是一种复杂的关系,能被人们加工、储存、运用却不被意识。本研究采用反应时和预估正确率两个指标,通过实验比较了儿童对空间位置协变的外显学习和内隐学习的效果。结果表明,儿童在面临像空间位置协变这样的复杂任务时有内隐学习模式出现,并且内隐学习的效果优于外显学习。     

成就目标导向对创业行动效能的影响研究

在调查基础上,本文研究了成就目标导向对创业行动效能的影响。研究结果表明,学习目标导向与自我效能感及创业行动效能存在正相关,业绩接近目标导向与自我效能感及创业行动效能存在较弱的负相关．业绩回避目标导向与自我效能感及创业行动效能存在较高的负相关;自我效能感对创业行动效能具有显著影响;自我效能感在成就目标导向对创业行动效能的影响中起中介作用。     

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares

Data in psychology are often collected using Likert‐type scales, and it has been shown that factor analysis of Likert‐type data is better performed on the polychoric correlation matrix than on the product‐moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real‐data example indicates that estimates by ridge GLS are 9–20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich‐type standard errors following the ridge GLS methods also perform reasonably well.     

Evaluating increased effort for item disposal to improve recycling at a university

An evaluation of increased response effort to dispose of items was conducted to improve recycling at a university. Signs prompting individuals to recycle and notifying them of the location of trash and recycling receptacles were posted in each phase. During the intervention, trashcans were removed from the classrooms, and one large trashcan was available in the hallway next to the recycling receptacles. Results showed that correct recycling increased, and trash left in classrooms increased initially during the second intervention phase before returning to baseline levels.