跟讀練習: The Map of Mathematics - 通過影片學習英語口語
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86 句
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The mathematics we learn in school doesn’t quite do the field of mathematics justice.
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We only get a glimpse at one corner of it, but the mathematics as a whole is a huge and wonderfully diverse subject.
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My aim with this video is to show you all that amazing stuff.
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We’ll start back at the very beginning.
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The origin of mathematics lies in counting.
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In fact counting is not just a human trait, other animals are able to count as well and e vidence for human counting goes back to prehistoric times with check marks made in bones.
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There were several innovations over the years with the Egyptians having the first equation, the ancient Greeks made strides in many areas like geometry and numerology, and negative numbers were invented in China.
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And zero as a number was first used in India.
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Then in the Golden Age of Islam Persian mathematicians made further strides and the first book on algebra was written.
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Then mathematics boomed in the renaissance along with the sciences.
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Now there is a lot more to the history of mathematics then what I have just said, but I’m gonna jump to the modern age and mathematics as we know it now.
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Modern mathematics can be broadly be broken down into two areas, pure maths: the study of mathematics for its own sake, and applied maths: when you develop mathematics to help solve some real world problem.
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But there is a lot of crossover.
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In fact, many times in history someone’s gone off into the mathematical wilderness motivated purely by curiosity and kind of guided by a sense of aesthetics.
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And then they have created a whole bunch of new mathematics which was nice and interesting but doesn’t really do anything useful.
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But then, say a hundred hears later, someone will be working on some problem at the cutting edge of physics or computer science and they’ll discover that this old theory in pure maths is exactly what they need to solve their real world problems!
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Which is amazing, I think!
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And this kind of thing has happened so many times over the last few centuries.
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It is interesting how often something so abstract ends up being really useful.
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But I should also mention, pure mathematics on its own is still a very valuable thing to do because it can be fascinating and on its own can have a real beauty and elegance that almost becomes like art.
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Okay enough of this highfalutin, lets get into it.
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Pure maths is made of several sections.
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The study of numbers starts with the natural numbers and what you can do with them with arithmetic operations.
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And then it looks at other kinds of numbers like integers, which contain negative numbers, rational numbers like fractions, real numbers which include numbers like pi which go off to infinite decimal points, and then complex numbers and a whole bunch of others.
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Some numbers have interesting properties like Prime Numbers, or pi or the exponential.
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There are also properties of these number systems, for example, even though there is an infinite amount of both integers and real numbers, there are more real numbers than integers.
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So some infinities are bigger than others.
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The study of structures is where you start taking numbers and putting them into equations in the form of variables.
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Algebra contains the rules of how you then manipulate these equations.
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Here you will also find vectors and matrices which are multi-dimensional numbers, and the rules of how they relate to each other are captured in linear algebra.
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Number theory studies the features of everything in the last section on numbers like the properties of prime numbers.
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Combinatorics looks at the properties of certain structures like trees, graphs, and other things that are made of discreet chunks that you can count.
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Group theory looks at objects that are related to each other in, well, groups.
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A familiar example is a Rubik’s cube which is an example of a permutation group.
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And order theory investigates how to arrange objects following certain rules like, how something is a larger quantity than something else.
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The natural numbers are an example of an ordered set of objects, but anything with any two way relationship can be ordered.
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Another part of pure mathematics looks at shapes and how they behave in spaces.
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The origin is in geometry which includes Pythagoras, and is close to trigonometry, which we are all familiar with form school.
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Also there are fun things like fractal geometry which are mathematical patterns which are scale invariant, which means you can zoom into them forever and the always look kind of the same.
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Topology looks at different properties of spaces where you are allowed to continuously deform them but not tear or glue them.
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For example a Möbius strip has only one surface and one edge whatever you do to it.
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And coffee cups and donuts are the same thing - topologically speaking.
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Measure theory is a way to assign values to spaces or sets tying together numbers and spaces.
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And finally, differential geometry looks the properties of shapes on curved surfaces, for example triangles have got different angles on a curved surface, and brings us to the next section, which is changes.
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The study of changes contains calculus which involves integrals and differentials which looks at area spanned out by functions or the behaviour of gradients of functions.
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And vector calculus looks at the same things for vectors.
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Here we also find a bunch of other areas like dynamical systems which looks at systems that evolve in time from one state to another, like fluid flows or things with feedback loops like ecosystems.
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And chaos theory which studies dynamical systems that are very sensitive to initial conditions.
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Finally complex analysis looks at the properties of functions with complex numbers.
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This brings us to applied mathematics.
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At this point it is worth mentioning that everything here is a lot more interrelated than I have drawn.
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In reality this map should look like more of a web tying together all the different subjects but you can only do so much on a two dimensional plane so I have laid them out as best I can.
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Okay we’ll start with physics, which uses just about everything on the left hand side to some degree.
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Mathematical and theoretical physics has a very close relationship with pure maths.
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Mathematics is also used in the other natural sciences with mathematical chemistry and biomathematics which look at loads of stuff from modelling molecules to evolutionary biology.
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Mathematics is also used extensively in engineering, building things has taken a lot of maths since Egyptian and Babylonian times.
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Very complex electrical systems like aeroplanes or the power grid use methods in dynamical systems called control theory.
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Numerical analysis is a mathematical tool commonly used in places where the mathematics becomes too complex to solve completely.
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So instead you use lots of simple approximations and combine them all together to get good approximate answers.
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For example if you put a circle inside a square, throw darts at it, and then compare the number of darts in the circle and square portions, you can approximate the value of pi.
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But in the real world numerical analysis is done on huge computers.
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Game theory looks at what the best choices are given a set of rules and rational players and it’s used in economics when the players can be intelligent, but not always, and other areas like psychology, and biology.
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Probability is the study of random events like coin tosses or dice or humans, and statistics is the study of large collections of random processes or the organisation and analysis of data.
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This is obviously related to mathematical finance, where you want model financial systems and get an edge to win all those fat stacks.
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Related to this is optimisation, where you are trying to calculate the best choice amongst a set of many different options or constraints, which you can normally visualise as trying to find the highest or lowest point of a function.
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Optimisation problems are second nature to us humans, we do them all the time: trying to get the best value for money, or trying to maximise our happiness in some way.
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Another area that is very deeply related to pure mathematics is computer science, and the rules of computer science were actually derived in pure maths and is another example of something that was worked out way before programmable computers were built.
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Machine learning: the creation of intelligent computer systems uses many areas in mathematics like linear algebra, optimisation, dynamical systems and probability.
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And finally the theory of cryptography is very important to computation and uses a lot of pure maths like combinatorics and number theory.
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So that covers the main sections of pure and applied mathematics, but I can’t end without looking at the foundations of mathematics.
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This area tries to work out at the properties of mathematics itself, and asks what the basis of all the rules of mathematics is.
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Is there a complete set of fundamental rules, called axioms, which all of mathematics comes from?
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And can we prove that it is all consistent with itself?
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Mathematical logic, set theory and category theory try to answer this and a famous result in mathematical logic are Gödel’s incompleteness theorems which, for most people, means that Mathematics does not have a complete and consistent set of axioms, which mean that it is all kinda made up by us humans.
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Which is weird seeing as mathematics explains so much stuff in the Universe so well.
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Why would a thing made up by humans be able to do that?
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That is a deep mystery right there.
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Also we have the theory of computation which looks at different models of computing and how efficiently they can solve problems and contains complexity theory which looks at what is and isn’t computable and how much memory and time you would need, which, for most interesting problems, is an insane amount.
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Ending So that is the map of mathematics.
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Now the thing I have loved most about learning maths is that feeling you get where something that seemed so confusing finally clicks in your brain and everything makes sense: like an epiphany moment, kind of like seeing through the matrix.
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In fact some of my most satisfying intellectual moments have been understanding some part of mathematics and then feeling like I had a glimpse at the fundamental nature of the Universe in all of its symmetrical wonder.
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It’s great, I love it.
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Ending Making a map of mathematics was the most popular request I got, which I was really happy about because I love maths and its great to see so much interest in it.
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So I hope you enjoyed it.
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Obviously there is only so much I can get into this timeframe, but hopefully I have done the subject justice and you found it useful.
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So there will be more videos coming from me soon, here’s all the regular things and it was my pleasure se you next time.
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本課的詞彙與口語要點
這節 C1 級別的口語課以影片“The Map of Mathematics”為素材。 影片中反覆出現的詞有：mathematics, theory, maths, pure, systems。 這段影片共有 86 個句子、1855 個單詞可供跟讀。 講話部分時長為 11:03。 說話人語速自然，每分鐘約 168 個詞，接近日常對話。 只有 81% 的單詞屬於英語最常用的 3,000 詞，詞彙難度較高。
影片中的重點詞彙
影片中最難的 15 個單詞，附發音和釋義：
| 單詞 | 發音 | 釋義 |
|---|---|---|
| algebra 名詞 | /ˈæl.d͡ʒɪ.bɹə/ | 代數 /代數 |
| geometry 名詞 | /d͡ʒiˈɑ.mə.tɹi/ | 幾何 /幾何, 幾何學 /幾何學 |
| integer 名詞 | /ˈɪn.tɪ.d͡ʒə(ɹ)/ | 整數 /整數 |
| optimization 名詞 | /ˌɑptəmaɪˈzeɪʃən/ | 最佳化 /最佳化 |
| vector 名詞 | /ˈvɛktɚ/ | 向量, 向量 |
| equation 名詞 | /ɪˈkweɪ.ʒən/ | 方程式, 方程 |
| axiom 名詞 | /ˈæk.si.əm/ | 原則 /原則 |
| combinatorics 名詞 | /ˌkɑm.bɪn.əˈtɔɹ.ɪks/ | 組合數學 /組合數學 |
| stride 動詞 | /stɹaɪd/ | 跨 |
| calculus 名詞 | /ˈkæl.kjə.ləs/ | 微積分學 /微積分學 |
| numerical 形容詞 | /n(j)uːˈmɛɹ.ɪ.kəl/ | 數值的 /數值的 |
| probability 名詞 | /ˌpɹɑ.bəˈbɪl.ə.ti/ | 可能性 |
| dimensional 形容詞 | /daɪˈmɛn.ʃə.nəl/ | 維的 /維的 |
| rational 形容詞 | /ˈɹæʃ(ə)nəl/ | 合理的, 理性的 |
| arithmetic 名詞 | /æɹɪθˈmɛtɪk/ | 算術 /算術 |
影片中出現的短語動詞
| 單詞 | 發音 | 釋義 |
|---|---|---|
| make up 動詞 | /ˌmeɪk ˈʌp/ | 組成 /組成 |
| end up 動詞 | 到達 | |
| see through 動詞 | 看透 | |
| work out 動詞 | /ˌwɝk ˈaʊt/ | 計算 /計算, 算出 |
影片中的語法
說話人最常用的結構，並附上影片中的原話：
| 結構 | 影片中的用法 |
|---|---|
| 被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的 | were invented · was written · be broken |
| 現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事 | have just said · have created · has happened |
| 定語從句 who / which + 從句 — 補充說明人或事物 | mathematics which was · matrices which are · cube which is |
需要注意的發音
說話人用了 10 次縮略和弱讀形式，例如 doesn't, we'll, can't。請按聽到的簡短形式來說。
- “th” 音: mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, arithmetic /æɹɪθˈmɛtɪk/, mathematician /ˌmæθ.(ə.)məˈtɪʃ.ən/, aesthetics /ɛsˈθɛt.ɪks/, theorem /ˈθiərəm/
- “sh” 和 “zh” 音: optimization /ˌɑptəmaɪˈzeɪʃən/, equation /ɪˈkweɪ.ʒən/, computation /ˌkɑmpjʊˈteɪʃn̩/, differential [dɪfəˈɹənʃəɫ], dimensional /daɪˈmɛn.ʃə.nəl/
- 長單詞——注意重音位置: mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, geometry /d͡ʒiˈɑ.mə.tɹi/, optimization /ˌɑptəmaɪˈzeɪʃən/, combinatorics /ˌkɑm.bɪn.əˈtɔɹ.ɪks/, approximate /əˈpɹɑk.sə.mət/
中文母語者容易讀錯的音：
- /v/ — 不要讀成 /w/，上齒輕觸下唇: vector /ˈvɛktɚ/, derive /dɪˈɹaɪv/, invent /ɪnˈvɛnt/, motivate /ˈmoʊ.tɪ.veɪt/, evolve /ɪˈvɑlv/
- 詞尾子音 — 要讀清楚，後面不要加母音: combinatorics /ˌkɑm.bɪn.əˈtɔɹ.ɪks/, stride /stɹaɪd/, dart /dɑɹt/, calculus /ˈkæl.kjə.ləs/, approximate /əˈpɹɑk.sə.mət/
- /r/ 和 /l/ 的區別: algebra /ˈæl.d͡ʒɪ.bɹə/, numerical /n(j)uːˈmɛɹ.ɪ.kəl/, differential [dɪfəˈɹənʃəɫ], probability /ˌpɹɑ.bəˈbɪl.ə.ti/, rational /ˈɹæʃ(ə)nəl/
如何用這段影片練習
- 先完整聽一遍影片，不要開口，記下不認識的單詞。
- 先用 0.75 倍速逐句跟讀，熟練之後再回到正常速度。
- 錄下自己的聲音並與原聲對比，特別注意 algebra, geometry, integer 這類單詞。
什麼是跟讀法？
跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。