雅思阅读机经真题解析Novice and Expert_雅思机经和真题的区别

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雅思阅读机经真题解析-Novice and Expert

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You should spend about 20 minutes on Question 14-26 which are based on Reading Paage below.Becoming an Expert

Expertise is commitment coupled with creativity.Specifically, it is the commitment of time, energy, and resources to a relatively narrow field of study and the creative energy neceary to generate new knowledge in that field.It takes a considerable amount of time and regular exposure to a large number of cases to become an expert.A

An individual enters a field of study as a novice.The novice needs to learn the guiding principles and rules of a given task in order to perform that task.Concurrently, the novice needs to be exposed to specific cases, or instances, that test the boundaries of such heuristics.Generally, a novice will find a mentor to guide her through the proce.A fairly simple example would be someone learning to play che.The novice che player seeks a mentor to teach her the object of the game, the number of spaces, the names of the pieces, the function of each piece, how each piece is moved, and the neceary conditions for winning or losing the game.B

In time, and with much practice, the novice begins to recognize patterns of behavior within cases and.thus, becomes a journeyman.With more practice and exposure to increasingly complex cases, the journeyman finds patterns not only within cases but also between cases.More importantly, the journeyman learns that these patterns often repeat themselves over time.The journeyman still maintains regular contact with a mentor to solve specific problems and learn more complex strategies.Returning to the example of the che player, the individual begins to learn patterns of opening moves, offensive and defensive game-playing strategies, and patterns of victory and defeat.C

When a journeyman starts to make and test hypotheses about future behavior based on past experiences, she begins the next transition.Once she creatively generates knowledge, rather than simply matching superficial patterns, she becomes an expert.At this point, she is confident in her knowledge and no longer needs a mentor as a guide—she becomes responsible for her own knowledge.In the che example, once a journeyman begins competing against experts, makes predictions based on patterns, and tests those predictions against actual behavior, she is generating new knowledge and a deeper understanding of the game.She is creating her own cases rather than relying on the cases of others.D

The che example is a rather short description of an apprenticeship model.Apprenticeship may seem like a restrictive 18th century mode of education, but it is still a standard method of training for many complex tasks.Academic doctoral programs are based on an apprenticeship model, as are fields like law, music, engineering, and medicine.Graduate students enter fields of study, find mentors, and begin the long proce of becoming independent experts and generating new knowledge in their respective domains.EPsychologists and cognitive scientists agree that the time it takes to become an expert depends on the complexity of the task and the number of cases, or patterns, to which an individual is exposed.The more complex the task, the longer it takes to build expertise, or, more accurately, the longer it takes to experience and store a large number of cases or patterns.F

The Power of Expertise

An expert perceives meaningful patterns in her domain better than non-experts.Where a novice perceives random or disconnected data points, an expert connects regular patterns within and between cases.This ability to identify patterns is not an innate perceptual skill;rather it reflects the organization of knowledge after exposure to and experience with thousands of cases.Experts have a deeper understanding of their domains than novices do, and utilize higher-order principles to solve problems.A novice, for example, might group objects together by color or size, whereas an expert would group the same objects according to their function or utility.Experts comprehend the meaning of data and weigh variables with different criteria within their domains better than novices.Experts recognize variables that have the largest influence on a particular problem and focus their attention on those variables.G

Experts have better domain-specific short-term and long-term memory than novices do.Moreover, experts perform tasks in their domains faster than novices and commit fewer errors while problem solving.Interestingly, experts go about solving problems differently than novices.Experts spend more time thinking about a problem to fully understand it at the beginning of a task than do novices, who immediately seek to find a solution.Experts use their knowledge of previous cases as context for creating mental models to solve given problems.H

Better at self-monitoring than novices, experts are more aware of instances where they have committed errors or failed to understand a problem.Experts check their solutions more often than novices and recognize when they are miing information neceary for solving a problem.Experts are aware of the limits of their domain knowledge and apply their domain's heuristics to solve problems that fall outside of their experience base.I

The Paradox of Expertise

The strengths of expertise can also be weaknees.Although one would expect experts to be good forecasters, they are not particularly good at making predictions about the future.Since the 1930s, researchers have been testing the ability of experts to make forecasts.The performance of experts has been tested against actuarial tables to determine if they are better at making predictions than simple statistical models.Seventy years later, with more than two hundred experiments in different domains, it is clear that the answer is no.If supplied with an equal amount of data about a particular case, an actuarial table is as good, or better, than an expert at making calls about the future.Even if an expert is given more specific case information than is available to the statistical model, the expert does not tend to outperform the actuarial table.J

Theorists and researchers differ when trying to explain why experts are le accurate forecasters than statistical models.Some have argued that experts, like all humans, are inconsistent when using mental models to make predictions.A number of researchers point to human biases to explain unreliable expert predictions.During the last 30 years, researchers have categorized, experimented, and theorized about the cognitive aspects of forecasting.Despite such efforts, the literature shows little consensus regarding the causes or manifestations of human bias.Questions 1-5

Complete the flow chart

Choose No More Than Three Words from the Reading Paage for each answer.Write your answers in boxes 1-5on your answer sheet.From a novice to an expert

Novice:

↓need to study 1 under the guidance of a

↓start to identify 4 for cases within or between study more 5 ways of doing things

Expert:create new knowledge

perform task independently

Questions 6-10

Do the following statements agree with the information given in Reading Paage 1?

In boxes 6-10 on your answer sheet, write

TRUE if the statement is true

FALSE if the statement is false

NOT GIVEN if the information is not given in the paage

6.Novices and experts use the same system of knowledge to comprehend and claify objects.7.The focus of novices' training is necearily on long term memory

8.When working out the problems, novices want to solve them straight away.9.When handling problems, experts are always more efficient than novices in their fields.10.Expert tend to review more than novices on cases when flaws or limit on understanding took place.Questions 11-13

Complete the following summary of the paragraphs of Reading Paage, using No More Than Two Words from the Reading Paage for each answer.Write your answers in boxes 11-13 on your answer sheet.While experts outperform novices and machines in pattern recognition and problem solving, expert predictions of future behavior or events are seldom as accurate as simple actuarial tables.Why? Some have tried to explain that experts differ when using cognitive 11 to forecast.Researchers believe it is due to 12.However attempting endeavor of finding answers did not yet produce 13.文章题目：

Novice and Expert

篇章结构

体裁论说文

题目新手与专家

结构A 新手进入业界的首要任务

B 新手积累经验之后的任务

C 新手如何向专家过渡

D 学徒关系训练法的重要性

E 决定成为专家时间的因素

F 专家更善于觉察并聚焦对于特定稳定有最大影响的变脸

G 专家与新手的区别

H 专家相对新手更擅长自我检测

I 专家在预测未来方面不如数据统计

J 专家预测未来逊于统计模型的原因

试题分析

Question 1-13

题目类型：Question 1-5 Complete the flow chart

Question 6-10 TRUE, FALSE, NOT GIVEN

Question 11-13 Answer the questions below

题号定位词文中对应点题目解析

1A novice , requires to studyA段第二句本题可以根据线索词novice定位在A-C段，由requires to study可以判断A段第二句中needs to learn为同义词。

因此后面的the guiding principles and rules为答案

2Under the guidance ofA段第四句本题与上题可以判断为同一个段落，根据题目中under the guidance of判断原文中find a mentor to guide her through the proce为同义表达。

因此mentor为答案

3Grows up toB段第一句本题由流程可判断基本在B段，题目线索词grows up to可以引导我们发现B段第一句中becomes为同义词。

因此journeyman为答案

4Better understand, for casesB段第一句本题根据定位词Better understand, for cases可以判断该题仍在B段第一句，而文中thus表明了因果关系。

因此可以判断better understand的同义词recognize后的patterns of behavior为答案

5However, tackle particular problem, tacticsB段第四句本题中however表转折，题干中needs help to tackle particular problems and study可以作为线索词，由此可发现B段第四句中still为段内转折，此后的contact with a mentor可定位在题干中的needs help.因此后面与solve problems并列的learn more complex strategies为题目所需信息，根据题目需求提出定语complex即为答案

6Solve problemsG段第三句根据线索词solve problems可以定位在G段，该段第三句明确提到Experts go about solving problems differently than novices。

因此答案为False

7Novices, experts，do their jobsG段第二句根据题干中表意可以判断该题在分析新手与专家之间的区别，因此可大致定位在F, G, H三段，但G段中提到专家在专业领域执行速度更快，并未提到do their jobs，与原文不符。

因此答案为NOT GIVEN

8Working out the problemG段第四句根据题干中线索词可定位题目信息在原文中G段第四句，该句明确提到新手immediately seek to find a solution。

因此答案为TRUE

9Efficient, handling problemsG段第四句根据线索词可以定位该题目在G段，该段第三局提到新手专家解决问题方式不同，第四句说明专家需要先弄清楚问题的实质才开始解决，而新手往往一开始就想直接找到解决方案，可以判断专家解决问题相对更慢。

因此答案为FALSE

10Novices, reviewing solution, faultsH段第二句根据题干中when faults occur in the proce可以定位在原文中H段第一句committed errors, 此后第二句说明此时专家比新手更经常地检查自己的解决方案，也就意味着新手在犯错误时也会检查解决方案。

因此答案为TRUE

11Prediction, cognitive, inconsistencyJ段第二句根据prediction可判断该题大致在I段或J段，但cognitive和inconsistency可以帮助我们准确定位在J段第二句，而mental为cognitive近义词。

因此models为答案

12In the last 3 decades, fewJ段第四句根据题目中in the last 3 decades可定位到J段第3句或第4句，而第4句中说明没有足够的数据表明上述问题与human biases有直接联系，符合题意。

因此答案为human biases

13between and, causesJ段第四句与上题直接相关, between and说明题目与causes相关，而原文中regarding表明了关联性。

因此前面提到的consensus为答案。

参考译文：

菜鸟与专家

专业知识总是离不开创造性，具体来看，讲时间，精力和资源投入到一个相对小的领域进行研究，需要创造性在该领域获得新的知识。要成为一名专家需要大量的时间和接触大量的实战实例。

A每个人都是以菜鸟的身份进入一个新的领域。菜鸟需要学习最基本的原理以及既定任务的法则来完成该项任务。与此同时，菜鸟还需要面对具体的实例或是情况，这也能够测出启发式教育的成果。一般来说，菜鸟需要找一个导师来帮助他顺利进行这个过程。举一个最简单的例子，如果又热要学习下象棋，菜鸟就需要找一个导师告诉他象棋的目标，棋盘的棋子的总数，每一枚棋子的名字，每一枚棋子的功能，怎么移动以及最后决定输赢的必要条件。

B随着时间的投入和不断的练习，菜鸟开始能够识别实例内部行为的类型，成为一个熟练学徒，通过更多的练习和接触更为复杂的实例，使得已经成为熟练学徒的学徒不仅能识别实例内部的类型也能够看出不同实例之间的联系。更为重要的是，成熟的工人发现这些实例的类型会重复出现。成熟工人仍然需要和导师保持联系来解决一些具体的问题并且学习更加复杂的策略。回到刚才讲的学习下棋的例子，菜鸟开始慢慢学习怎样开棋，进攻以及防守这类的下棋策略，以及判断输赢的情况。

C当一个熟练学徒开始通过以往的经验来预测未来的情况是，他开始了向下一个阶段的过渡。一旦熟练学徒开始创造性地获取知识而不是简单地根据类型来将实例进行匹配的时候，他就成为了一名专家。在这个阶段，他开始自信与自己所掌握的知识，不再需要一名导师——他自己可以自由运用自己的知识。在刚才举的下棋的例子中，一旦一个熟练学徒开始和专家进行竞争，根据掌握的类型来做出预测，并且根据实际的行为来检验该预测，他就获取了新的知识，并且对象棋有了更深的理解。他开始创造出自己的下棋攻略而不是依赖于别人的经验。

D刚列举的下棋的例子只是一个简短的描述来说明学徒关系的模型。学徒关系可能看起来像严格的18世纪教育模式，但是现在仍然是许多复杂任务训练的标准方法。学术博士项目就是建立在这样的学徒模型上的，比如说法律，音乐，工程学和医学。毕业生进入研究领域，寻找导师，开始成为独立专家的漫长过程，并且在它们各自的领域产生新的知识。

E心理学家和认知学家一直认为成为专家所需的时间取决于任务的复杂程度以及实例的数量或是需要面对的实例的类型。任务越复杂，所需的时间就越多来学习专业知识，或者更准确地说，需要更长的时间来增加经验并且储存大量的实例。

专业知识的力量

F以为专家比非专家能在专业领域觉察更有意义的行为类型，而菜鸟只能随意地观察没有关联的数据，专家将实例内部和实例之间的有规律的类型联系起来。这种分辨类型的能力并不是一个先天就具备的技能，而是在接触了成百上千的实例后获得的知识的结晶。专家对于该领域比菜鸟有更深的理解，使用高位的原则来解决问题。比如说菜鸟可能会根据颜色和大小来进行分组，然而专家会更具功能或是用处来进行分组。专家理解数据的含义，通过比菜鸟更为合理的方法运用行业的标准来衡量不同的变量。专家能够认出对特定问题有最大影响的变量，并且聚焦在这些变量上。

G专家比菜鸟在长期和短期方面具备更好地专业性知识，并且专家比菜鸟在专业领域执行速度跟快，而且在问题解决地时候犯较少的错误。有趣的是，专家和菜鸟相比，解决问题的方式不同，并且会先弄清楚问题的实质才开始解决问题，而菜鸟一开始就想直接找到解决方案。专家运用他从过往经验作为背景获取的知识来建立一个头脑中的模型来解决特定问题。

H专家和菜鸟相比，更擅长于自我检测，他们更容易意识到自己曾经犯过错的地方或是没能理解的问题，在他们察觉到自己可能错过一些信息时，会比菜鸟更频繁地检查自己的解决方案。专家总是能意识到他们领域知识的有限，并将它们专业领域的启发式学习应用出来来解决他们专业领域之外的问题。

I专业知识的悖论

专家的长处也是他们的弱点，尽管人们都期待专家是一个成功的预言家，但是他们并不是特别擅长对未来做出预测。自1930年代，研究者一直在测试专家做出预测的能力。专家的表现是根据数据统计来检测的，来确定他们的预测不仅仅是一句简单的数据模型。70年后，在不同领域进行了200多个实验，实验结果表明答案答案是否定的，如果一个实例中有相同量的数据，数据统计比专家更能对未来做出正确的预测。及时专家能获得比数据模型更加具体的实例信息，也不见得回避数据统计表在预测方面做得更好。

J理论学家和研究者在试图解释为什么专家在做预测方面逊于统计模型，一些人认为专家像其他所有人一样，在做预测时运用不同的头脑中的模型，大量的研究者指出在解释不可靠的专家预测时人们存在的偏差。在过去的30年，研究者已经分类，实验并提出相关理论来认知预测的各个方面。尽管研究者做了各种努力，历史资料显示，没有足够的数据显示上述问题和人类认知偏差之间有直接的联系。

参考答案：

Version 21211 主题 新手和专家

1principles and rules2mentor3journeyman

4patterns of behavior5complex6FALSE

7NOT GIVEN8TRUE9FALSE

10TRUE11models12human biases

13consensus

雅思阅读机经真题解析-Novice and Expert