时间:2019-02-23 作者:英语课 分类:英语语言学习


英语课
Like many of you, I'm one of the lucky people. I was born to a family where education was pervasive 1. I'm a third-generation PhD, a daughter of two academics. In my childhood, I played around in my father's university lab. So it was taken for granted that I attend some of the best universities, which in turn opened the door to a world of opportunity.
 
Unfortunately, most of the people in the world are not so lucky. In some parts of the world, for example, South Africa, education is just not readily accessible. In South Africa, the educational system was constructed in the days of apartheid for the white minority. And as a consequence, today there is just not enough spots for the many more people who want and deserve a high quality education. That scarcity 2 led to a crisis in January of this year at the University of Johannesburg. There were a handful of positions left open from the standard admissions process, and the night before they were supposed to open that for registration 3, thousands of people lined up outside the gate in a line a mile long, hoping to be first in line to get one of those positions. When the gates opened, there was a stampede, and 20 people were injured and one woman died. She was a mother who gave her life trying to get her son a chance at a better life.
 
But even in parts of the world like the United States where education is available, it might not be within reach. There has been much discussed in the last few years about the rising cost of health care. What might not be quite as obvious to people is that during that same period the cost of higher education tuition has been increasing at almost twice the rate, for a total of 559 percent since 1985. This makes education unaffordable for many people.
 
Finally, even for those who do manage to get the higher education, the doors of opportunity might not open. Only a little over half of recent college graduates in the United States who get a higher education actually are working in jobs that require that education. This, of course, is not true for the students who graduate from the top institutions, but for many others, they do not get the value for their time and their effort.
 
Tom Friedman, in his recent New York Times article, captured, in the way that no one else could, the spirit behind our effort. He said the big breakthroughs are what happen when what is suddenly possible meets what is desperately 4 necessary. I've talked about what's desperately necessary. Let's talk about what's suddenly possible.
 
What's suddenly possible was demonstrated by three big Stanford classes, each of which had an enrollment 5 of 100,000 people or more. So to understand this, let's look at one of those classes, the Machine Learning class offered by my colleague and cofounder Andrew Ng. Andrew teaches one of the bigger Stanford classes. It's a Machine Learning class, and it has 400 people enrolled 6 every time it's offered. When Andrew taught the Machine Learning class to the general public, it had 100,000 people registered. So to put that number in perspective, for Andrew to reach that same size audience by teaching a Stanford class, he would have to do that for 250 years. Of course, he'd get really bored.
 
So, having seen the impact of this, Andrew and I decided 7 that we needed to really try and scale this up, to bring the best quality education to as many people as we could. So we formed Coursera, whose goal is to take the best courses from the best instructors 9 at the best universities and provide it to everyone around the world for free. We currently have 43 courses on the platform from four universities across a range of disciplines, and let me show you a little bit of an overview 10 of what that looks like.
 
(Video) Robert Ghrist: Welcome to Calculus 11.
 
Ezekiel Emanuel: Fifty million people are uninsured.
 
Scott Page: Models help us design more effective institutions and policies. We get unbelievable segregation 12.
 
Scott Klemmer: So Bush imagined that in the future, you'd wear a camera right in the center of your head.
 
Mitchell Duneier: Mills wants the student of sociology to develop the quality of mind ...
 
RG: Hanging cable takes on the form of a hyperbolic cosine.
 
Nick Parlante: For each pixel in the image, set the red to zero.
 
Paul Offit: ... Vaccine 13 allowed us to eliminate polio virus.
 
Dan Jurafsky: Does Lufthansa serve breakfast and San Jose? Well, that sounds funny.
 
Daphne Koller: So this is which coin you pick, and this is the two tosses.
 
Andrew Ng: So in large-scale machine learning, we'd like to come up with computational ...
 
(Applause)
 
DK: It turns out, maybe not surprisingly, that students like getting the best content from the best universities for free. Since we opened the website in February, we now have 640,000 students from 190 countries. We have 1.5 million enrollments, 6 million quizzes in the 15 classes that have launched so far have been submitted, and 14 million videos have been viewed.
 
But it's not just about the numbers, it's also about the people. Whether it's Akash, who comes from a small town in India and would never have access in this case to a Stanford-quality course and would never be able to afford it. Or Jenny, who is a single mother of two and wants to hone her skills so that she can go back and complete her master's degree. Or Ryan, who can't go to school, because his immune deficient 14 daughter can't be risked to have germs come into the house, so he couldn't leave the house. I'm really glad to say -- recently, we've been in correspondence with Ryan -- that this story had a happy ending. Baby Shannon -- you can see her on the left -- is doing much better now, and Ryan got a job by taking some of our courses.
 
So what made these courses so different? After all, online course content has been available for a while. What made it different was that this was real course experience. It started on a given day, and then the students would watch videos on a weekly basis and do homework assignments. And these would be real homework assignments for a real grade, with a real deadline. You can see the deadlines and the usage graph. These are the spikes 15 showing that procrastination 16 is global phenomenon.
 
(Laughter)
 
At the end of the course, the students got a certificate. They could present that certificate to a prospective 18 employer and get a better job, and we know many students who did. Some students took their certificate and presented this to an educational institution at which they were enrolled for actual college credit. So these students were really getting something meaningful for their investment of time and effort.
 
Let's talk a little bit about some of the components 20 that go into these courses. The first component 19 is that when you move away from the constraints 21 of a physical classroom and design content explicitly 22 for an online format 23, you can break away from, for example, the monolithic 24 one-hour lecture. You can break up the material, for example, into these short, modular units of eight to 12 minutes, each of which represents a coherent concept. Students can traverse this material in different ways, depending on their background, their skills or their interests. So, for example, some students might benefit from a little bit of preparatory material that other students might already have. Other students might be interested in a particular enrichment topic that they want to pursue individually. So this format allows us to break away from the one-size-fits-all model of education, and allows students to follow a much more personalized curriculum.
 
Of course, we all know as educators that students don't learn by sitting and passively watching videos. Perhaps one of the biggest components of this effort is that we need to have students who practice with the material in order to really understand it. There's been a range of studies that demonstrate the importance of this. This one that appeared in Science last year, for example, demonstrates that even simple retrieval practice, where students are just supposed to repeat what they already learned gives considerably 25 improved results on various achievement tests down the line than many other educational interventions 27.
 
We've tried to build in retrieval practice into the platform, as well as other forms of practice in many ways. For example, even our videos are not just videos. Every few minutes, the video pauses and the students get asked a question.
 
(Video) SP: ... These four things. Prospect 17 theory, hyperbolic discounting, status quo bias 28, base rate bias. They're all well documented. So they're all well documented deviations 30 from rational behavior.
 
DK: So here the video pauses, and the student types in the answer into the box and submits. Obviously they weren't paying attention.
 
(Laughter)
 
So they get to try again, and this time they got it right. There's an optional explanation if they want. And now the video moves on to the next part of the lecture. This is a kind of simple question that I as an instructor 8 might ask in class, but when I ask that kind of a question in class, 80 percent of the students are still scribbling 31 the last thing I said, 15 percent are zoned 32 out on Facebook, and then there's the smarty pants in the front row who blurts 33 out the answer before anyone else has had a chance to think about it, and I as the instructor am terribly gratified that somebody actually knew the answer. And so the lecture moves on before, really, most of the students have even noticed that a question had been asked. Here, every single student has to engage with the material.
 
And of course these simple retrieval questions are not the end of the story. One needs to build in much more meaningful practice questions, and one also needs to provide the students with feedback on those questions. Now, how do you grade the work of 100,000 students if you do not have 10,000 TAs? The answer is, you need to use technology to do it for you. Now, fortunately, technology has come a long way, and we can now grade a range of interesting types of homework. In addition to multiple choice and the kinds of short answer questions that you saw in the video, we can also grade math, mathematical expressions as well as mathematical derivations. We can grade models, whether it's financial models in a business class or physical models in a science or engineering class and we can grade some pretty sophisticated programming assignments.
 
Let me show you one that's actually pretty simple but fairly visual. This is from Stanford's Computer Science 101 class, and the students are supposed to color-correct that blurry 34 red image. They're typing their program into the browser 35, and you can see they didn't get it quite right, Lady Liberty is still seasick 36. And so, the student tries again, and now they got it right, and they're told that, and they can move on to the next assignment. This ability to interact actively 37 with the material and be told when you're right or wrong is really essential to student learning.
 
Now, of course we cannot yet grade the range of work that one needs for all courses. Specifically, what's lacking is the kind of critical thinking work that is so essential in such disciplines as the humanities, the social sciences, business and others. So we tried to convince, for example, some of our humanities faculty 38 that multiple choice was not such a bad strategy. That didn't go over really well.
 
So we had to come up with a different solution. And the solution we ended up using is peer grading. It turns out that previous studies show, like this one by Saddler and Good, that peer grading is a surprisingly effective strategy for providing reproducible grades. It was tried only in small classes, but there it showed, for example, that these student-assigned grades on the y-axis are actually very well correlated with the teacher-assigned grade on the x-axis. What's even more surprising is that self-grades, where the students grade their own work critically -- so long as you incentivize them properly so they can't give themselves a perfect score -- are actually even better correlated with the teacher grades. And so this is an effective strategy that can be used for grading at scale, and is also a useful learning strategy for the students, because they actually learn from the experience. So we now have the largest peer-grading pipeline 39 ever devised, where tens of thousands of students are grading each other's work, and quite successfully, I have to say.
 
But this is not just about students sitting alone in their living room working through problems. Around each one of our courses, a community of students had formed, a global community of people around a shared intellectual endeavor. What you see here is a self-generated map from students in our Princeton Sociology 101 course, where they have put themselves on a world map, and you can really see the global reach of this kind of effort.
 
Students collaborated 40 in these courses in a variety of different ways. First of all, there was a question and answer forum 41, where students would pose questions, and other students would answer those questions. And the really amazing thing is, because there were so many students, it means that even if a student posed a question at 3 o'clock in the morning, somewhere around the world, there would be somebody who was awake and working on the same problem. And so, in many of our courses, the median response time for a question on the question and answer forum was 22 minutes. Which is not a level of service I have ever offered to my Stanford students.
 
(Laughter)
 
And you can see from the student testimonials that students actually find that because of this large online community, they got to interact with each other in many ways that were deeper than they did in the context of the physical classroom. Students also self-assembled, without any kind of intervention 26 from us, into small study groups. Some of these were physical study groups along geographical 42 constraints and met on a weekly basis to work through problem sets. This is the San Francisco study group, but there were ones all over the world. Others were virtual study groups, sometimes along language lines or along cultural lines, and on the bottom left there, you see our multicultural 43 universal study group where people explicitly wanted to connect with people from other cultures.
 
There are some tremendous opportunities to be had from this kind of framework. The first is that it has the potential of giving us a completely unprecedented 44 look into understanding human learning. Because the data that we can collect here is unique. You can collect every click, every homework submission 45, every forum post from tens of thousands of students. So you can turn the study of human learning from the hypothesis-driven mode to the data-driven mode, a transformation 46 that, for example, has revolutionized biology. You can use these data to understand fundamental questions like, what are good learning strategies that are effective versus 47 ones that are not? And in the context of particular courses, you can ask questions like, what are some of the misconceptions that are more common and how do we help students fix them?
 
So here's an example of that, also from Andrew's Machine Learning class. This is a distribution of wrong answers to one of Andrew's assignments. The answers happen to be pairs of numbers, so you can draw them on this two-dimensional plot. Each of the little crosses that you see is a different wrong answer. The big cross at the top left is where 2,000 students gave the exact same wrong answer. Now, if two students in a class of 100 give the same wrong answer, you would never notice. But when 2,000 students give the same wrong answer, it's kind of hard to miss. So Andrew and his students went in, looked at some of those assignments, understood the root cause of the misconception, and then they produced a targeted error message that would be provided to every student whose answer fell into that bucket, which means that students who made that same mistake would now get personalized feedback telling them how to fix their misconception much more effectively.
 
So this personalization is something that one can then build by having the virtue 48 of large numbers. Personalization is perhaps one of the biggest opportunities here as well, because it provides us with the potential of solving a 30-year-old problem. Educational researcher Benjamin Bloom, in 1984, posed what's called the 2 sigma problem, which he observed by studying three populations. The first is the population that studied in a lecture-based classroom. The second is a population of students that studied using a standard lecture-based classroom, but with a mastery-based approach, so the students couldn't move on to the next topic before demonstrating mastery of the previous one. And finally, there was a population of students that were taught in a one-on-one instruction using a tutor. The mastery-based population was a full standard deviation 29, or sigma, in achievement scores better than the standard lecture-based class, and the individual tutoring gives you 2 sigma improvement in performance.
 
To understand what that means, let's look at the lecture-based classroom, and let's pick the median performance as a threshold. So in a lecture-based class, half the students are above that level and half are below. In the individual tutoring instruction, 98 percent of the students are going to be above that threshold. Imagine if we could teach so that 98 percent of our students would be above average. Hence, the 2 sigma problem.
 
Because we cannot afford, as a society, to provide every student with an individual human tutor. But maybe we can afford to provide each student with a computer or a smartphone. So the question is, how can we use technology to push from the left side of the graph, from the blue curve, to the right side with the green curve? Mastery is easy to achieve using a computer, because a computer doesn't get tired of showing you the same video five times. And it doesn't even get tired of grading the same work multiple times, we've seen that in many of the examples that I've shown you. And even personalization is something that we're starting to see the beginnings of, whether it's via the personalized trajectory 49 through the curriculum or some of the personalized feedback that we've shown you. So the goal here is to try and push, and see how far we can get towards the green curve.
 
So, if this is so great, are universities now obsolete 50? Well, Mark Twain certainly thought so. He said that, "College is a place where a professor's lecture notes go straight to the students' lecture notes, without passing through the brains of either."
 
(Laughter)
 
I beg to differ with Mark Twain, though. I think what he was complaining about is not universities but rather the lecture-based format that so many universities spend so much time on. So let's go back even further, to Plutarch, who said that, "The mind is not a vessel 51 that needs filling, but wood that needs igniting." And maybe we should spend less time at universities filling our students' minds with content by lecturing at them, and more time igniting their creativity, their imagination and their problem-solving skills by actually talking with them.
 
So how do we do that? We do that by doing active learning in the classroom. So there's been many studies, including this one, that show that if you use active learning, interacting with your students in the classroom, performance improves on every single metric -- on attendance, on engagement and on learning as measured by a standardized 52 test. You can see, for example, that the achievement score almost doubles in this particular experiment. So maybe this is how we should spend our time at universities.
 
So to summarize, if we could offer a top quality education to everyone around the world for free, what would that do? Three things. First it would establish education as a fundamental human right, where anyone around the world with the ability and the motivation could get the skills that they need to make a better life for themselves, their families and their communities.
 
Second, it would enable lifelong learning. It's a shame that for so many people, learning stops when we finish high school or when we finish college. By having this amazing content be available, we would be able to learn something new every time we wanted, whether it's just to expand our minds or it's to change our lives.
 
And finally, this would enable a wave of innovation, because amazing talent can be found anywhere. Maybe the next Albert Einstein or the next Steve Jobs is living somewhere in a remote village in Africa. And if we could offer that person an education, they would be able to come up with the next big idea and make the world a better place for all of us.
 
Thank you very much.

adj.普遍的;遍布的,(到处)弥漫的;渗透性的
  • It is the most pervasive compound on earth.它是地球上最普遍的化合物。
  • The adverse health effects of car exhaust are pervasive and difficult to measure.汽车尾气对人类健康所构成的有害影响是普遍的,并且难以估算。
n.缺乏,不足,萧条
  • The scarcity of skilled workers is worrying the government.熟练工人的缺乏困扰着政府。
  • The scarcity of fruit was caused by the drought.水果供不应求是由于干旱造成的。
n.登记,注册,挂号
  • Marriage without registration is not recognized by law.法律不承认未登记的婚姻。
  • What's your registration number?你挂的是几号?
adv.极度渴望地,绝望地,孤注一掷地
  • He was desperately seeking a way to see her again.他正拼命想办法再见她一面。
  • He longed desperately to be back at home.他非常渴望回家。
n.注册或登记的人数;登记
  • You will be given a reading list at enrollment.注册时你会收到一份阅读书目。
  • I just got the enrollment notice from Fudan University.我刚刚接到复旦大学的入学通知书。
adj.入学登记了的v.[亦作enrol]( enroll的过去式和过去分词 );登记,招收,使入伍(或入会、入学等),参加,成为成员;记入名册;卷起,包起
  • They have been studying hard from the moment they enrolled. 从入学时起,他们就一直努力学习。 来自《简明英汉词典》
  • He enrolled with an employment agency for a teaching position. 他在职业介绍所登了记以谋求一个教师的职位。 来自《简明英汉词典》
adj.决定了的,坚决的;明显的,明确的
  • This gave them a decided advantage over their opponents.这使他们比对手具有明显的优势。
  • There is a decided difference between British and Chinese way of greeting.英国人和中国人打招呼的方式有很明显的区别。
n.指导者,教员,教练
  • The college jumped him from instructor to full professor.大学突然把他从讲师提升为正教授。
  • The skiing instructor was a tall,sunburnt man.滑雪教练是一个高高个子晒得黑黑的男子。
指导者,教师( instructor的名词复数 )
  • The instructors were slacking on the job. 教员们对工作松松垮垮。
  • He was invited to sit on the rostrum as a representative of extramural instructors. 他以校外辅导员身份,被邀请到主席台上。
n.概观,概述
  • The opening chapter gives a brief historical overview of transport.第一章是运输史的简要回顾。
  • The seminar aims to provide an overview on new media publishing.研讨会旨在综览新兴的媒体出版。
n.微积分;结石
  • This is a problem where calculus won't help at all.对于这一题,微积分一点也用不上。
  • After studying differential calculus you will be able to solve these mathematical problems.学了微积分之后,你们就能够解这些数学题了。
n.隔离,种族隔离
  • Many school boards found segregation a hot potato in the early 1960s.在60年代初,许多学校部门都觉得按水平分班是一个棘手的问题。
  • They were tired to death of segregation and of being kicked around.他们十分厌恶种族隔离和总是被人踢来踢去。
n.牛痘苗,疫苗;adj.牛痘的,疫苗的
  • The polio vaccine has saved millions of lives.脊髓灰质炎疫苗挽救了数以百万计的生命。
  • She takes a vaccine against influenza every fall.她每年秋季接种流感疫苗。
adj.不足的,不充份的,有缺陷的
  • The crops are suffering from deficient rain.庄稼因雨量不足而遭受损害。
  • I always have been deficient in selfconfidence and decision.我向来缺乏自信和果断。
n.穗( spike的名词复数 );跑鞋;(防滑)鞋钉;尖状物v.加烈酒于( spike的第三人称单数 );偷偷地给某人的饮料加入(更多)酒精( 或药物);把尖状物钉入;打乱某人的计划
  • a row of iron spikes on a wall 墙头的一排尖铁
  • There is a row of spikes on top of the prison wall to prevent the prisoners escaping. 监狱墙头装有一排尖钉,以防犯人逃跑。 来自《简明英汉词典》
n.拖延,耽搁
  • Procrastination is the father of failure. 因循是失败的根源。
  • Procrastination is the thief of time. 拖延就是浪费时间。
n.前景,前途;景色,视野
  • This state of things holds out a cheerful prospect.事态呈现出可喜的前景。
  • The prospect became more evident.前景变得更加明朗了。
adj.预期的,未来的,前瞻性的
  • The story should act as a warning to other prospective buyers.这篇报道应该对其他潜在的购买者起到警示作用。
  • They have all these great activities for prospective freshmen.这会举办各种各样的活动来招待未来的新人。
n.组成部分,成分,元件;adj.组成的,合成的
  • Each component is carefully checked before assembly.每个零件在装配前都经过仔细检查。
  • Blade and handle are the component parts of a knife.刀身和刀柄是一把刀的组成部分。
(机器、设备等的)构成要素,零件,成分; 成分( component的名词复数 ); [物理化学]组分; [数学]分量; (混合物的)组成部分
  • the components of a machine 机器部件
  • Our chemistry teacher often reduces a compound to its components in lab. 在实验室中化学老师常把化合物分解为各种成分。
强制( constraint的名词复数 ); 限制; 约束
  • Data and constraints can easily be changed to test theories. 信息库中的数据和限制条件可以轻易地改变以检验假设。 来自英汉非文学 - 科学史
  • What are the constraints that each of these imply for any design? 这每种产品的要求和约束对于设计意味着什么? 来自About Face 3交互设计精髓
ad.明确地,显然地
  • The plan does not explicitly endorse the private ownership of land. 该计划没有明确地支持土地私有制。
  • SARA amended section 113 to provide explicitly for a right to contribution. 《最高基金修正与再授权法案》修正了第123条,清楚地规定了分配权。 来自英汉非文学 - 环境法 - 环境法
n.设计,版式;[计算机]格式,DOS命令:格式化(磁盘),用于空盘或使用过的磁盘建立新空盘来存储数据;v.使格式化,设计,安排
  • Please format this floppy disc.请将这张软盘格式化。
  • The format of the figure is very tasteful.该图表的格式很雅致。
adj.似独块巨石的;整体的
  • Don't think this gang is monolithic.不要以为这帮人是铁板一块。
  • Mathematics is not a single monolithic structure of absolute truth.数学并不是绝对真理的单一整体结构。
adv.极大地;相当大地;在很大程度上
  • The economic situation has changed considerably.经济形势已发生了相当大的变化。
  • The gap has narrowed considerably.分歧大大缩小了。
n.介入,干涉,干预
  • The government's intervention in this dispute will not help.政府对这场争论的干预不会起作用。
  • Many people felt he would be hostile to the idea of foreign intervention.许多人觉得他会反对外来干预。
n.介入,干涉,干预( intervention的名词复数 )
  • Economic analysis of government interventions deserves detailed discussion. 政府对经济的干预应该给予充分的论述。 来自辞典例句
  • The judge's frequent interventions made a mockery of justice. 法官的屡屡干预是对正义的践踏。 来自互联网
n.偏见,偏心,偏袒;vt.使有偏见
  • They are accusing the teacher of political bias in his marking.他们在指控那名教师打分数有政治偏见。
  • He had a bias toward the plan.他对这项计划有偏见。
n.背离,偏离;偏差,偏向;离题
  • Deviation from this rule are very rare.很少有违反这条规则的。
  • Any deviation from the party's faith is seen as betrayal.任何对党的信仰的偏离被视作背叛。
背离,偏离( deviation的名词复数 ); 离经叛道的行为
  • Local deviations depend strongly on the local geometry of the solid matrix. 局部偏离严格地依赖于固体矩阵的局部几何形状。
  • They were a series of tactical day-to-day deviations from White House policy. 它们是一系列策略上一天天摆脱白宫政策的偏向。
n.乱涂[写]胡[乱]写的文章[作品]v.潦草的书写( scribble的现在分词 );乱画;草草地写;匆匆记下
  • Once the money got into the book, all that remained were some scribbling. 折子上的钱只是几个字! 来自汉英文学 - 骆驼祥子
  • McMug loves scribbling. Mama then sent him to the Kindergarten. 麦唛很喜欢写字,妈妈看在眼里,就替他报读了幼稚园。 来自互联网
adj.划成区域的,束带的v.(飞机、汽车等)急速移动( zoom的现在分词 );(价格、费用等)急升,猛涨
  • This small town has been zoned as a shopping area. 这个小镇已划作商业区。 来自《简明英汉词典》
  • They zoned the house into sleeping, sitting and dining rooms. 他们将房子区分成卧室、客厅和餐厅。 来自《简明英汉词典》
v.突然说出,脱口而出( blurt的第三人称单数 )
  • He blurts out all he hears. 他漏嘴说出了他听到的一切。 来自辞典例句
  • If a user blurts out an interesting idea, ask "What problem would that solve for you?" 如果用户不假思索地冒出一个有趣的想法,则询问他:“这可以解决哪些问题?” 来自互联网
adj.模糊的;污脏的,污斑的
  • My blurry vision makes it hard to drive. 我的视力有点模糊,使得开起车来相当吃力。 来自《简明英汉词典》
  • The lines are pretty blurry at this point. 界线在这个时候是很模糊的。 来自《简明英汉词典》
n.浏览者
  • View edits in a web browser.在浏览器中看编辑的效果。
  • I think my browser has a list of shareware links.我想在浏览器中会有一系列的共享软件链接。
adj.晕船的
  • When I get seasick,I throw up my food.我一晕船就呕吐。
  • He got seasick during the voyage.在航行中他晕船。
adv.积极地,勤奋地
  • During this period all the students were actively participating.在这节课中所有的学生都积极参加。
  • We are actively intervening to settle a quarrel.我们正在积极调解争执。
n.才能;学院,系;(学院或系的)全体教学人员
  • He has a great faculty for learning foreign languages.他有学习外语的天赋。
  • He has the faculty of saying the right thing at the right time.他有在恰当的时候说恰当的话的才智。
n.管道,管线
  • The pipeline supplies Jordan with 15 per cent of its crude oil.该管道供给约旦15%的原油。
  • A single pipeline serves all the houses with water.一条单管路给所有的房子供水。
合作( collaborate的过去式和过去分词 ); 勾结叛国
  • We have collaborated on many projects over the years. 这些年来我们合作搞了许多项目。
  • We have collaborated closely with the university on this project. 我们与大学在这个专案上紧密合作。
n.论坛,讨论会
  • They're holding a forum on new ways of teaching history.他们正在举行历史教学讨论会。
  • The organisation would provide a forum where problems could be discussed.这个组织将提供一个可以讨论问题的平台。
adj.地理的;地区(性)的
  • The current survey will have a wider geographical spread.当前的调查将在更广泛的地域范围內进行。
  • These birds have a wide geographical distribution.这些鸟的地理分布很广。
adj.融合多种文化的,多种文化的
  • Children growing up in a multicultural society.在多元文化社会中长大的孩子们。
  • The school has been attempting to bring a multicultural perspective to its curriculum.这所学校已经在尝试将一种多元文化视角引入其课程。
adj.无前例的,新奇的
  • The air crash caused an unprecedented number of deaths.这次空难的死亡人数是空前的。
  • A flood of this sort is really unprecedented.这样大的洪水真是十年九不遇。
n.服从,投降;温顺,谦虚;提出
  • The defeated general showed his submission by giving up his sword.战败将军缴剑表示投降。
  • No enemy can frighten us into submission.任何敌人的恐吓都不能使我们屈服。
n.变化;改造;转变
  • Going to college brought about a dramatic transformation in her outlook.上大学使她的观念发生了巨大的变化。
  • He was struggling to make the transformation from single man to responsible husband.他正在努力使自己由单身汉变为可靠的丈夫。
prep.以…为对手,对;与…相比之下
  • The big match tonight is England versus Spain.今晚的大赛是英格兰对西班牙。
  • The most exciting game was Harvard versus Yale.最富紧张刺激的球赛是哈佛队对耶鲁队。
n.德行,美德;贞操;优点;功效,效力
  • He was considered to be a paragon of virtue.他被认为是品德尽善尽美的典范。
  • You need to decorate your mind with virtue.你应该用德行美化心灵。
n.弹道,轨道
  • It is not difficult to sketch the subsequent trajectory.很容易描绘出它们最终的轨迹。
  • The path followed by a projectile is called its trajectory.抛物体所循的路径称为它的轨道。
adj.已废弃的,过时的
  • These goods are obsolete and will not fetch much on the market.这些货品过时了,在市场上卖不了高价。
  • They tried to hammer obsolete ideas into the young people's heads.他们竭力把陈旧思想灌输给青年。
n.船舶;容器,器皿;管,导管,血管
  • The vessel is fully loaded with cargo for Shanghai.这艘船满载货物驶往上海。
  • You should put the water into a vessel.你应该把水装入容器中。
adj.标准化的
  • We use standardized tests to measure scholastic achievement. 我们用标准化考试来衡量学生的学业成绩。
  • The parts of an automobile are standardized. 汽车零件是标准化了的。
学英语单词
abrielle
actual measurement on the drawing
Ailanthus Desf.
air-sucking water ejector
albert hall
algebraic cofactor
aminoconanene
arnolds cove
assignment priority
bacony degeneration
basic subsystem module
Brazey
bubble separation(techinque)
buproprion
chain base period
chalasia
Chrome OS
comparative utility
costmaries
courbed
cross nerve
difenolan
discordant injection(transgressive intrusion)
dual system locomotive
elinac
end place
face recognitions
finite difference equation model
flashing of a dynamo
Fortezza
free of damage absolutely
funboy
furrey
Ghats
gouri
hand reamer
harzia verrucosa
hay-jack
hotmelts
hydrogen gas cylinder
hydroxy stearate
igneous accumulate
improved crown grafting
impurple
intermedian cubital vein
Langoon
leucospis japonica
Leyden phial
Longdan Xiegan Wan
magnesium pyrophosphate
medium steels
membrane permeability
moonshiners
morphometrically
myeloangiography
new mercantilism
normally closed
Old Man Jenkins
one-idead
Open bracket
osteosis cutis
partial solid solution
pejo
peperinos
phonetised
ponomaryov
potamogetons
preemption capability
profitable
proximity problem
pub-crawl
pump operated sprayer
pyrophones
radium jaw
ray displacement
reconnaissance balloon
referrent
retaining screw
Sabinov
saltation ash
servility
set of complex features
sheet-musics
Shore hardness number
sidewhisker
sled connector
slop room
speed to pressure transducer
stat padder
straight-reamer
Sukhoy Log
sulfapyridine sodium
superaudio
tassinari
TCA
to bob
topograghy
twisted form
uptails
vake
water borne disease
zerofuel weight