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论认知语境在成功言语交际中的..
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论认知语境在成功言语交际中的作用
On the Roles of Cognitive Context in Successful Verbal Communication
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3秒自动关闭窗口Physical Context and Cognitive Context的用法和样例：
Relevance theory regards translation as a communicative process of cognitive inference, which rationally expounds the interrelation and interaction among source language intention, cognitive context and translation tactics.
而关联翻译理论则把翻译视为一个认知推理的交际过程,合理地阐释了翻译过程中源语作者的意图、文读者的认知语境和译者的翻译策略三者之间相互联系、互作用的关系。
This course offers an overview of the maintenance of psychological health in the social, behavioiral, physiological and cognitive contexts.
本课程介由社会
Relevance of Conversational Context and Cognitive Meaning
论会话语境与认知意义的相关性
Skilled readers make use of context and prediction.
阅读能力强的人会利用上下文及推测来理解文意。
Physical Context and Cognitive Context的海词问答与网友补充：
Physical Context and Cognitive Context的相关资料：
相关词典网站：&&&cognitive context 在 外国语言文字 分类中
的翻译结果:
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&在分类学科中查询
很抱歉，暂未找到该词条在当前类别下的译词。您可以查看在的译词。
&&&&Cognitive Context and Conceptual Metaphor
&&&&认知语境与概念隐喻
&&&&Intention of Source Language, Cognitive Context & Translation Tactics——Enlightenments on translation from Relevance Theory
&&&&源语意图·认知语境·翻译策略———谈关联理论对翻译的启示
&&&&Cognitive Context and Discourse Interpretation in CET-4
&&&&认知语境与CET-4语篇解读
&&&&The New Development of Context Theory——Cognitive Context
&&&&语境理论的新发展——认知语境
&&&&Cognitive Context and English Reading Comprehension
&&&&认知语境与英语阅读理解
查询“cognitive context”译词为用户自定义的双语例句&&&&我想查看译文中含有：的双语例句
为了更好的帮助您理解掌握查询词或其译词在地道英语中的实际用法，我们为您准备了出自英文原文的大量英语例句，供您参考。&&&&&&&&&&&&&&&&&&&& The two important topics in modern pragmatics are utterance produce and utterance interpretation. Grice's conversational Theory is regarded as the theoretical foundation of modern pragmatics. Sperber and Wilson's Relevance
is considered to be the base of cognitive Pragmatics .The two have influenced the linguistic field
on a large scale and drawn wide spread attention. This paper, firstly , introduces the basic views of the two ,then briefly discusses their dissimilarity CP and Relevance, implicit c... &&&&&&&&&&&&当今语用学研究的两大主题是话语生存和话语理解。Grice的会话理论是当今语用学的理论基础。Sperber & Wilson的关联理论是认知语用学的基础。两种学说在语言学界产生了空前的影响，并引起了广泛的注意。先概述两种理论的基本观点；然后初步讨论其差异：合作原则与关联性，暗含交际与暗含明说交际，隐喻、认知语境与语境假设；最后谈谈几点拙见。&&&&&&&& In accordance with Relevance Translation Theory advanced by Gutt, a cognitive pragmatist, and recent development in cognitive pragmatics, this paper explores the role of Relevance Principle in translation process. It defines the composition, comparison and interaction of reader's, translator's and writer's cognitive context in translation activity. It also makes a detailed analysis of how to convey the original writer's meaning and intention as far as possible by making flexible adju... &&&&&&&&&&&&本文根据认知语用学家 Gutt的关联翻译理论和认知语用学有关研究成果 ,探讨了关联原则在翻译过程中的体现 ,并阐述了读者、译者和作者认知语境的构成、比较以及在翻译活动中的互动 ,具体分析了如何根据关联原则和认知语用学原理 ,在翻译过程中通过灵活调整和变通机制 ,尽可能传达原文作者的意义和意图&&&&&&&& Conceptual metaphor is viewed as a very important part of contemporary metaphor study. It is based on everyday metaphors with genera ity, systematicality and productivity as its main characteristics. Mapping is an ontological correspondence in conceptual metaphor. By the analysis of cognitive context, this paper expounds the importance of cognitive cotext in producing and understanding conceptual metaphor. &&&&&&&&&&&&概念隐喻是当代隐喻研究的一个重要课题 ,概念隐喻是对日常隐喻语言的概括和总结 ,它具有概括性、系统性和生成性等特点。映射在概念隐喻中是一种本体对应的关系。本文通过对认知语境的分析 ,阐述了认知语境对生成和理解概念隐喻的重要作用。&nbsp&&&&&&&&相关查询:
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context theory是什么意思
中文翻译百科解释情境论:&&&&n. 1.上下文；文章的前后关系[脉络]。 2.(事情等 ...:&&&&n. 1.理论，学理，原理。 2.学说，论说 (opp. ...详细百科解释
例句与用法On austin ' s speech act theory and dynamic context theory言语行为理论与动态语境观Context theory and english reading teaching语境理论与英语阅读教学On the development of context theories语境理论发展述评This thesis will explore their semantic and structural relationship with context theory本文将通过语境理论从意义和结构两方面对他们的联系进行研究。 Cognitive context theory makes a brand - new explanation on the context from the view of cognitive science of mankind and broadens the contextual research摘要认知语境观从人类认知科学的角度对语境作了全新的解释，开拓了语境研究的思路。 It not only reflects the creativity of english teaching but also embodies english teachers " ability to apply context theories to teach english vocabulary利用语境进行词汇教学，不仅体现了英语学科教学的前沿性和创新性，又是教师个人英语教学能力的直接反映。 As long as teachers in the middle school consider the actual situation in the middle school , and employ context theories in their teaching and different method to different students , vocabulary teaching will certainly achieve good result中学教师只要从中学英语词汇教学的实际出发，做到因材施教，词汇语境教学法的路将会越走越宽The cognitive context theory thinks that the context is the result of internalization , cognition and conceptualization of pragmatic factors , and the language communication bases on cognitive context that both sides share with认知语境观认为：语境是语用因素内在化、认知化、概念化的结果，语言交际的基础是交际双方共有的认知语境，语言交际是按照一定的推理规律进行的认知活动。
相邻词汇热门词汇
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All rights reserved请大神翻译费曼技巧的原作者博文？加深对认知心理学的一些见解
请大神翻译费曼技巧的原作者博文？加深对认知心理学的一些见解
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Seven Principles of Learning Better From Cognitive Science 
I just finished one of the best books I’ve read on the science of learning. Daniel Willingham is a Harvard educated cognitive scientist who writes books and articles about how to learn and teach better.由认知科学来的七个学得更好的原理我刚刚读完了一本我读过的关于学习科学最好的书之一。Daniel Willingham 是受过哈佛教育的认知科学家， 他写的书和文章是关于怎样更好的学习和怎样教的更好。The title of his book, Why Don’t Students Like School?, is a tad unfortunate, I think, because the book isn’t really about bored students. Instead, the book is divided into principles of learning. In order to make the cut, these principles needed to fulfill a strict set of scientific criteria:Robust scientific support. In Willingham’s words, “Each principle is based on a great deal of data, not only one or two studies. If any of these principles is wrong, something close to it is right.”Doesn’t depend on circumstances. These are facts about how human brains learn, so they don’t change whether you’re learning Spanish or mathematics.Ignoring it would be costly. Using the principles versus not using them showed a big difference in results. The principles aren’t just theoretical concerns but practically significant.Suggests non-obvious applications. The final criteria was that the implications of the principle should suggest new ways of teaching and learning.The book is excellent, and I highly recommend getting a copy for yourself as Willingham explains many of the details and implications of each of these principles. I wanted to discuss each principle briefly, to share the implications it has for learning better.这本书的书名 Why Don’t Students Like School?让我觉得有点遗憾。因为这本书真的不是关于无聊的学生。反而，这本书被分类为学习原理。能符合学习原理这个分类， 这些原理需要满足一套严格的科学标准:强有力的科学支持。用 Willingham 的话，“每个原理都是基于大量的数据， 不仅仅是一两个研究， 如果这些原理有一个是错的，那么跟这个错的原理相近的是对的。“不依赖特定环境。这些事实是关于人类大脑是怎样学习的，所以不管你正在学的是西班牙语还是数学它们都不会改变。忽视它的代价是昂贵的。使用这些原理对比于不使用这些原理的结果会显示巨大的差别。这些原理不仅仅理论相关，并且是相当实用的。启发不明显的应用。最后一个标准就是原理的影响应该启发新的教学和学习方法。这是一本优秀的书，我强烈推荐为自己弄一份，因为 Willingham 解释了很多这些原理的细节和影响。我想简短地讨论一下每个原理来分享一下它们对更好的学习带来的影响。Side note: The book lists nine principles, but two were more related to teaching, so I omitted them here.编注: 这本书列了九个原理， 但是有两个是关于教学的，所以我把这两个省略了。1. Factual knowledge precedes skill.Einstein was wrong. Knowledge is more important than imagination, because knowledge is what allows us to imagine. There is considerable research showing the importance of background knowledge to how well we learn. Without background knowledge, the kinds of insights Einstein praised are impossible.Careful studies show that having more background knowledge on a topic means we can read faster, understand more when we do and remember more of it later. This means knowledge is exponential growth, with past knowledge becoming a crucial factor in the speed at which more knowledge is acquired.This means that you cannot teach someone “how” to think, without first teaching them a considerable amount of “what” to think. Thinking well first requires knowing a lot of stuff, and there’s no way around it.事实性知识先于技能。爱因斯坦是错的。 知识比想象力更重要，因为有了知识才能想象。 有大量的研究表明背景知识对学习能力的重要性。没了背景知识， 爱因斯坦崇拜的那种洞察力是不可能有的。调查研究表明，在一个主题上拥有更多的背景知识意味着当我们以后做更多关于这个主题的时候我们可以读得更快，理解得更多。 这意味着知识是呈指数增长的，过去的知识成了获得更多知识的速度的关键因素。 这意味着你不能教某人”如何“去思考而没有先教他们足够多的“什么”来思考。思考得好要求首先知道许许多多的东西， 而关于这个是没有其它方法的。2. Memory is the residue of thought.You remember what you think about. Whatever aspect of what you’re learning your mind dwells on, will be the part that it is likely to be retained. If you, inadvertently, spend your studying time thinking about the wrong aspects of your studies you won’t remember much of use.The problem with this principle is that knowing about it is not enough. We can’t constantly self-monitor our own cognition, noticing what we’re noticing. So even if you try to pay attention to the right things, it can be easy to accidentally focus on less important details which will take precedence in memory.This is a reason why highlighting is often a lousy tactic. When you highlight, you’re not focusing on underlying meaning, but observing bolded words or particularly emphasized sentences. So you don’t remember much.I recommend tactics like paraphrasing with sparse notes while reading, the Feynman technique or taking pauses during a reading session to quickly recap what you just read. These are orienting tasks that encourage you to spend more time thinking about underlying meaning, which is almost always what you want to be learning.This also shows one of the weaknesses I’ve seen in students who misuse analogies. If the analogy you make causes you to think about a surface detail of a concept, and not the underlying structure, you’ll only remember surface details on the test. A metaphor for voltage that uses volcanoes because they both start with “V” won’t help you with problems. The metaphor that voltage is analogous to height is useful because you’re forced to think about what voltage means (in this case the relation between gravitational and electric potential).Interestingly, this also has implications for languages. The reason the “sounds like” method for memorizing vocabulary words can work is because it forces you to think about how a word sounds more exactly. Having to come up with an image that links to the sound forces you to spend a couple seconds thinking about what the word actually sounds like.2.记忆是思想的残渣。你记得你思考过什么。你脑海里仔细思考过的关于你正在学的东西的每个方面，都将有可能成为被记住的一部分。如果你不经意把你学习的时间花在思考你学习上的错误方面,你将记不到多少有用的。问题是知道这个原理是不够的。我们没办法总是能够自我检查我们的认知能力，能够注意到我们在注意什么。所以即使你总是设法把注意力集中在正确的事上， 也会很容易意外的把注意力集中在不重要的细节上，使得它们被优先记住。这就是为什么划重点经常是一个糟糕的策略。 当你划重点的时候， 你不是集中在根本的本质意义， 而只是注意到空空的单词或者被特别强调的句子。 因此你记不了多少有用东西。我推荐策略比如一边阅读一边释义，做些稀少的笔记，费曼技巧，还有可以在阅读期间暂停一下来快速概要一下刚刚所读过的。这些策略都有确定的任务来促使你花时间去思考根本的本质意义，这也经常是你学习的时候想要得到的。我曾经看到学生们错误使用类比的方法，这也显示了它其中的一个弱点。如果你做的类比使得你思考的是一个概念的表面细节， 而不是这个概念的根本结构， 在测试中你只能记住表面细节。一个用火山(Volcanoes)来比喻电压(Voltage)，因为它们都是“V”开头的比喻不能帮助你和你的问题。 电压类比于高度的比喻是有帮助的，因为在这个比喻你被强迫去思考什么是电压（在这个情况下即 重力势能和电势能的关系）有趣的是，这对语言也有影响。 用"sounds like“方法来记住单词词汇有效果的原因是因为它迫使你去思考这个单词怎么发音更准确。必须想出一个影像来和发音连接起来会迫使你花几秒钟来思考到底这个单词听起来是怎样的。3. We understand new things in the context of what we already know.Abstract subjects like math, physics, finance or law, can often be hard for people to learn. The reason why is that the we learn things by their relation to other things we already know (sound familiar?). Willingham here suggests using many examples to ground a particular abstraction in concrete terms before moving on.I would also add that I believe people overestimate their ability to learn abstract things. As such, we tell ourselves we understand an idea without first grounding it in numerous examples or analogies. Smart learners correctly understand the brains weakness for abstraction and build scaffolding to support new ideas before they fully set.Occasionally when I recommend to students metaphors or analogies for learning a subject, they come up blank. I admit, it can be a tricky technique. But I believe part of the difficulty is that it points out when you don’t really understand a concept. If you understand a concept but can’t put it into a single example or analogy, you don’t really understand it at all (and should first do something like the Feynman technique to get that understanding).3.我们在熟悉的环境下理解新的事物。人们经常有困难学习像数学，物理，金融或者法学这种抽象的学科。原因是我们是通过我们已经知道的事物来学习新的事物（听起来很熟悉?)。 Willingham 建议在继续学习之前先用许多的例子把一个特别的抽象概念树立在具体的项目上。我相信人们也高估他们学习抽象事物的能力。就这样， 我们对自己说我们理解了一个概念而没有先用许多的例子和类比来为这个概念打基础。聪明的学习者正确理解大脑在抽象方面的弱点，在他们完全建立起概念之前他们会构造许多框架来支撑新的概念。偶尔有时候当我建议学生用比喻或者类比来学习一个科目的时候， 他们一片空白。我承认这是有点难的技巧。 但是我相信部分的困难是因为你没有完全理解一个概念。 如有你理解一个概念却一个例子都举不出来或者一个类比都比不来， 那你根本没有完全理解它。（并且首先应该做些什么比如费曼技巧来理解）4. Proficiency requires practice.The only way to become good at skills is to practice them. Additionally, some basic skills require thorough practice in order to be successful at more complicated skills.Math is an excellent example: you may have a conceptual understanding of calculus, but if you aren’t fully fluent with algebra, it will take you hours to do a simple problem. The only way to make algebra automatic is to practice a lot of problems.I’ve certainly
of downplaying the importance of repetitive practice in some of my early writing. But there’s no way I could have completed the or
without extensive time spent practicing the basic tools for each subject. Merely understanding isn’t enough.4. 精通需要练习。擅长某项技能的唯一方法是练习。 而且，一些基本的技能需要全面充分的练习才能掌握更复杂的技能。数学是一个好的例子：你可能概念上理解了微积分， 但是如果你对代数不熟练，做一个简单的问题也会花费你几个小时。对代数能做到不下意识的唯一方法是练习大量的问题。我的确对自己早期写作时低估重复性练习的重要性很愧疚。但是没有花费大量时间练习每个科目基础我是不可能完成MIT挑战和这个语言项目的。 仅仅理解是不够的。5. Cognition is fundamentally different early and late in training.Should you
For that matter, should you learn science like a scientist, making hypothesis, testing experiments, revising your theory to fit the data? Willingham offers substantial evidence that the answer is no.I think there’s merit in understanding how scientists perform their work, but it’s also clear that knowledge creation and knowledge acquisition are very different. Because they are different, the learner needs to weigh them against each other. For most disciplines, understanding scientific facts is more important than scientific process, for the simple reason that scientific facts will inform our lives, but few of us will ever do scientific research. The same applies to history, philosophy and nearly any other discipline of knowledge.5. 认知能力在训练早期和晚期本质上是不同的。你应该像牛顿那样学习物理吗？同样的，你应该像科学家那样，做假设，测试实验，修改理论来与数据相符来学习科学吗？Willingham 提供大量的证明来说明答案是否定的。我认为理解科学家怎么做他们的工作是有好处的。 但是创造知识和获取知识明显是不同的。因为它们是不同的，学习者需要权衡它们它们的不同。对于大多领域， 理解科学事实比理解科学进程更重要。 简单的原因就是科学事实可以引导我们的生活，但是很少人会去做科学研究。历史， 哲学和其他几乎所有知识的领域都是一样的道理。6. People are more alike than different in how we learn.Learning styles . There is no such thing as visual, auditory or kinesthetic learners. This is also true for every serious theory of different cognitive styles for learning.Defending this conclusion takes a bit of thought, because to most people the idea that people learn differently is obviously true, even though research says otherwise.Part of the confusion stems from the fact that different abilities can exist while styles do not. Meaning Johnny might be really good at processing visual information and Mary might be good at processing auditory information. Show Johnny a map and he’ll remember where everything is better than Mary. Play Mary a tune, and she can hum it back a week later.But this isn’t what a theory of learning styles suggests. It suggests that if you taught the same subject to both Johnny and Mary, and played Johnny a slideshow and Mary an audiobook, they would learn better than if Johnny had listened and Mary had watched. The experiments simply don’t find that.6.人们学习的方式是大同小异的。学习模式是骗人的鬼话。 并没什么视觉模式，听觉模式或者动觉模式的学习者。这对于任何不同学习认知方式的严肃理论也是一样。为这个结论辩护需要花点心思，因为对于大多数人来说人们学习方式不一样明显是对的，尽管研究表明不是这样。部分困惑源于存在不同的能力但是不存在不同模式这个事实。 意思是Johnny可能真的很擅长处理视觉上的信息而Mary可能很擅长处理听觉上的信息。 给Johnny看一个地图他比Mary能更好记住每个地方在哪里。给Mary放个曲， 她可以再一周后哼唱出来。但是这不是学习模式理论所要说明的。 学习模式理论暗示如果你教Johnny和Mary相同的学科，并且给Johnny看幻灯片，给Mary听有声的书，这样学比给Johnny听，给Mary看这样学看学得更好。不过实验就是没有发现如此。7. Intelligence can be changed through sustained hard work.This was probably my favorite part of the entire book because it validates much of what . Intelligence is partially genetic and partially environmental. Innate differences do matter and some people are born with more talent than others.However, Willingham argues that intelligence is malleable. Psychologists used to believe that intelligence was mostly genes. Twin studies and other natural experiments seemed to bear that out. Adopted children turn out more like their biological parents than their adoptive parents in many dimensions.However, now the consensus has turned far more towards nurture, rather than nature. One of the biggest pieces of evidence is the , which is the observation that people, over the last century, have gotten smarter (and the effect is too large to be from natural selection). Genes may have an important role in intelligence, but most of that role is played out through the environment, not independent of it.If you re-read the first principle I listed, that shouldn’t be surprising. Knowledge being exponential growth means that a small initial advantage can quickly compound. If genes gave you a 5% headstart in math in kindergarten, there may not be much difference between you and a similar child. However, expand that small initial advantage over thirty years and you may have someone who has done a PhD in physics and someone who stopped at high-school.From a population standpoint the difference between these two people may be “explained” by differences in genes. However, genes only created a small headstart. Sustained hard work can help set off your own exponential growth of learning in a domain as well.7.通过长期的努力可以改变智力。这可能是整本书中我最喜欢的部分了，因为它证实了大多我在这()所说的。 智力一部分因为基因一部分因为环境。天生的差异的确有影响，一些人生下来就是比别人有天赋。然而，Willingham 主张智力是可以被提高的。心理学家过去相信智力主要是基因决定的。孪生子研究和其他自然实验似乎也证实了这个。被收养的孩子在各个方面结果也是比养父母更像亲生父母。然而， 现在的共识主要对着环境因素，而不是自然因素（基因方面的）。最大的一个证明是弗林效应，这个效应观察到在人们过去的一个世纪变得越来越聪明（并且这个效应太大了，不会是因为自然选择）。基因在智力方面也许扮演了一个很重要的角色，但是大多数的角色是通过环境方面扮演的，而不是不相干的。如果你重读一下我上面列的第一个原理，应该不会感到惊讶。知识是呈指数式增长意味着最初小小的优势可以快速复合。 如果基因给了你在幼儿园数学方面5%的优势，可能这在你和差不多的孩子间没有很到的差别。但是，发展那最初小小的优势过个30年之后你可能看到谁谁在物理学完成了博士学位而一些人高中读完就没读了。从总体的观点来看这两类人的差异可能可以用基因的不同来“解释”。 但是，基因仅仅只是创造了最开始的那个小小优势。 长期的努力可以帮助你在一个领域的学习开始你自己的指数式增长。Concluding ThoughtsI thoroughly enjoyed this book, and don’t let my brief summary and insights spoil it for you. It’s a fairly easy read while still being smart and insightful. What’s more, the book is based on robust research and science.In terms of my own, more informal, writing about learning, I was happy that most of the principles discussed in the book reflected my own thinking. It’s comforting to see when the experience I’ve gained from my own learning challenges converges on the serious work scientists are doing to understand the brain and how we learn.思想总结从头到尾我都很享受这本书，别让我这简短的总结和见解成了剧透。这是一本相当容易阅读却又聪明且很有见解的书。而且，这本书是基于强有力地研究和科学上的。就我而言，比较随意的写关于学习的，我很高兴书中讨论的大多原理反应了我的心思，思想。看到科学家们为了理解大脑和我们是怎么学习的而做的那些严肃的工作包括了我自己从学习挑中获得经验,感觉很舒服。
原文：Seven Principles of Learning Better From Cognitive ScienceI just finished one of the best books I’ve read on the science of learning. Daniel Willingham is a Harvard educated cognitive scientist who writes
and about how to learn and teach better.The title of his book, , is a tad unfortunate, I think, because the book isn’t really about bored students. Instead, the book is divided into principles of learning. In order to make the cut, these principles needed to fulfill a strict set of scientific criteria:Robust scientific support. In Willingham’s words, “Each principle is based on a great deal of data, not only one or two studies. If any of these principles is wrong, something close to it is right.”Doesn’t depend on circumstances. These are facts about how human brains learn, so they don’t change whether you’re learning Spanish or mathematics.Ignoring it would be costly. Using the principles versus not using them showed a big difference in results. The principles aren’t just theoretical concerns but practically significant.Suggests non-obvious applications. The final criteria was that the implications of the principle should suggest new ways of teaching and learning.The book is excellent, and I highly recommend getting a copy for yourself as Willingham explains many of the details and implications of each of these principles. I wanted to discuss each principle briefly, to share the implications it has for learning better.Side note: The book lists nine principles, but two were more related to teaching, so I omitted them here.1. Factual knowledge precedes skill.Einstein . Knowledge is more important than imagination, because knowledge is what allows us to imagine. There is considerable research showing the importance of background knowledge to how well we learn. Without background knowledge, the kinds of insights Einstein praised are impossible.Careful studies show that having more background knowledge on a topic means we can read faster, understand more when we do and remember more of it later. This means knowledge is , with past knowledge becoming a crucial factor in the speed at which more knowledge is acquired.This means that you cannot teach someone “how” to think, without first teaching them a considerable amount of “what” to think. Thinking well first requires knowing a lot of stuff, and there’s no way around it.2. Memory is the residue of thought.You remember what you think about. Whatever aspect of what you’re learning your mind dwells on, will be the part that it is likely to be retained. If you, inadvertently, spend your studying time thinking about the wrong aspects of your studies you won’t remember much of use.The problem with this principle is that knowing about it is not enough. We can’t constantly self-monitor our own cognition, noticing what we’re noticing. So even if you try to pay attention to the right things, it can be easy to accidentally focus on less important details which will take precedence in memory.This is a reason why highlighting is often a lousy tactic. When you highlight, you’re not focusing on underlying meaning, but observing bolded words or particularly emphasized sentences. So you don’t remember much.I recommend tactics like paraphrasing with sparse notes while reading, the or taking pauses during a reading session to quickly recap what you just read. These are orienting tasks that encourage you to spend more time thinking about underlying meaning, which is almost always what you want to be learning.This also shows one of the weaknesses I’ve seen in students who misuse analogies. If the analogy you make causes you to think about a surface detail of a concept, and not the underlying structure, you’ll only remember surface details on the test. A metaphor for voltage that uses volcanoes because they both start with “V” won’t help you with problems. The metaphor that voltage is analogous to height is useful because you’re forced to think about what voltage means (in this case the relation between gravitational and electric potential).Interestingly, this also has implications for languages. The reason the “sounds like” method for memorizing vocabulary words can work is because it forces you to think about how a word sounds more exactly. Having to come up with an image that links to the sound forces you to spend a couple seconds thinking about what the word actually sounds like.3. We understand new things in the context of what we already know.Abstract subjects like math, physics, finance or law, can often be hard for people to learn. The reason why is that the we learn things by their relation to other things we already know (). Willingham here suggests using many examples to ground a particular abstraction in concrete terms before moving on.I would also add that I believe people overestimate their ability to learn abstract things. As such, we tell ourselves we understand an idea without first grounding it in numerous examples or analogies. Smart learners correctly understand the brains weakness for abstraction and build scaffolding to support new ideas before they fully set.Occasionally when I recommend to students metaphors or analogies for learning a subject, they come up blank. I admit, it can be a tricky technique. But I believe part of the difficulty is that it points out when you don’t really understand a concept. If you understand a concept but can’t put it into a single example or analogy, you don’t really understand it at all (and should first do something like the Feynman technique to get that understanding).4. Proficiency requires practice.The only way to become good at skills is to practice them. Additionally, some basic skills require thorough practice in order to be successful at more complicated skills.Math is an excellent example: you may have a conceptual understanding of calculus, but if you aren’t fully fluent with algebra, it will take you hours to do a simple problem. The only way to make algebra automatic is to practice a lot of problems.I’ve certainly
of downplaying the importance of repetitive practice in some of my early writing. But there’s no way I could have completed the or
without extensive time spent practicing the basic tools for each subject. Merely understanding isn’t enough.Willinham suggests an alternative to repetitive practice which can be painfully dull: learn harder subjects that require practicing earlier material. One study showed that those who took an algebra class showed rapid and predictable decline of their skills. The one group that didn’t? Those who learned calculus.5. Cognition is fundamentally different early and late in training.Should you
For that matter, should you learn science like a scientist, making hypothesis, testing experiments, revising your theory to fit the data? Willingham offers substantial evidence that the answer is no.I think there’s merit in understanding how scientists perform their work, but it’s also clear that knowledge creation and knowledge acquisition are very different. Because they are different, the learner needs to weigh them against each other. For most disciplines, understanding scientific facts is more important than scientific process, for the simple reason that scientific facts will inform our lives, but few of us will ever do scientific research. The same applies to history, philosophy and nearly any other discipline of knowledge.Another implication of this is that the ideal method for learning a subject and creating knowledge within a subject will be different. Learning calculus and inventing calculus bear little resemblance, so don’t worry if you can’t learn calculus the way Newton did. You don’t have to.6. People are more alike than different in how we learn.Learning styles . There is no such thing as visual, auditory or kinesthetic learners. This is also true for every serious theory of different cognitive styles for learning.Defending this conclusion takes a bit of thought, because to most people the idea that people learn differently is obviously true, even though research says otherwise.Part of the confusion stems from the fact that different abilities can exist while styles do not. Meaning Johnny might be really good at processing visual information and Mary might be good at processing auditory information. Show Johnny a map and he’ll remember where everything is better than Mary. Play Mary a tune, and she can hum it back a week later.But this isn’t what a theory of learning styles suggests. It suggests that if you taught the same subject to both Johnny and Mary, and played Johnny a slideshow and Mary an audiobook, they would learn better than if Johnny had listened and Mary had watched. The experiments simply don’t find that.This suggests that the ways we learn are more similar than different. Some people might be better at learning certain types of things than others, but given a particular subject, science hasn’t different ways of learning it that are consistently better for some people but not others.Side note: Willingham also debunks holistic versus linear thinkers. However the only thing it shares with my idea of “holistic” learning is the name. My version of holistic learning is not a learning style in the sense Willingham debunks here, but a strategy and one that happens to closely correspond with the third cognitive principle listed above. The nomenclature is my mistake, owing to my being unaware of the other learning theory that used the same name at the time. I’ve since used tried to use the word less, preferring “learning by connections” to avoid confusion.7. Intelligence can be changed through sustained hard work.This was probably my favorite part of the entire book because it validates much of what . Intelligence is partially genetic and partially environmental. Innate differences do matter and some people are born with more talent than others.However, Willingham argues that intelligence is malleable. Psychologists used to believe that intelligence was mostly genes. Twin studies and other natural experiments seemed to bear that out. Adopted children turn out more like their biological parents than their adoptive parents in many dimensions.However, now the consensus has turned far more towards nurture, rather than nature. One of the biggest pieces of evidence is the , which is the observation that people, over the last century, have gotten smarter (and the effect is too large to be from natural selection). Genes may have an important role in intelligence, but most of that role is played out through the environment, not independent of it.If you re-read the first principle I listed, that shouldn’t be surprising. Knowledge being exponential growth means that a small initial advantage can quickly compound. If genes gave you a 5% headstart in math in kindergarten, there may not be much difference between you and a similar child. However, expand that small initial advantage over thirty years and you may have someone who has done a PhD in physics and someone who stopped at high-school.From a population standpoint the difference between these two people may be “explained” by differences in genes. However, genes only created a small headstart. Sustained hard work can help set off your own exponential growth of learning in a domain as well.Concluding ThoughtsI thoroughly enjoyed this book, and don’t let my brief summary and insights spoil it for you. It’s a fairly easy read while still being smart and insightful. What’s more, the book is based on robust research and science.In terms of my own, more informal, writing about learning, I was happy that most of the principles discussed in the book reflected my own thinking. It’s comforting to see when the experience I’ve gained from my own learning challenges converges on the serious work scientists are doing to understand the brain and how we learn.
有中文版的《为什么学生不喜欢上学》，的确是本精彩的书，爱不释手，名字不适合营销策略。
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