Shadowing Practice: Early Computing: Crash Course Computer Science #1 - Learn English Speaking with Video
Les maken...
1
Hello world, I'm Carrie -Anne and welcome to Crash Course Computer Science.
2
Over the course of this series, we're going to go from bits, bytes, transistors and logic gates, all the way to operating systems, virtual reality and robots.
3
We're going to cover a lot, but just to clear things up, we are not going to teach you how to program.
4
Instead, we're going to explore a range of computing topics as a discipline and a technology.
5
Computers are the lifeblood of today's world.
6
If they were to suddenly turn off all at once, the power grid would shut down, cars would crash, planes would fall, water treatment plants would stop, stock markets would freeze, trucks with food wouldn't know where to deliver,
7
and employees wouldn't get paid.
8
Even many non -computer objects, like DFTBA shirts and the chair I'm sitting on, are made in factories run by computers.
9
Computing really has transformed nearly every aspect of our lives.
10
And this isn't the first time we've seen this sort of technology -driven global change.
11
Advances in manufacturing during the Industrial Revolution brought new scale to human civilization, in agriculture, industry and domestic life.
12
Mechanization meant superior harvests and more food, mass -produced goods, cheaper and faster travel and communication, and usually a better quality of life.
13
And computing technology is doing the same right now.
14
From automated farming and medical equipment, to global telecommunications and educational opportunities, and new frontiers like virtual reality and self -driving cars.
15
We are living in a time likely to be remembered as THE electronic age.
16
And with billions of transistors in just your smartphones, computers can seem pretty complicated.
17
But really, they're just simple machines that perform complex actions through many layers of abstraction.
18
So in this series, we're going to break down those layers and build up from simple ones and zeros to logic units,
19
CPUs, operating systems, the entire internet and beyond!
20
And don't worry, in the same way someone buying t -shirts on a webpage doesn't need to know how
21
that webpage was programmed, or the web designer doesn't need to know how all the packets are routed, or router engineers don't need to know about transistor logic,
22
this series will build on previous episodes but not be dependent on them.
23
By the end of this series I hope that you can better contextualize computing's role both in your own life and society, and how humanity's arguably greatest invention is just in its infancy,
24
with its biggest impact yet to come.
25
But before we get into all that, we should start at computing's origins, because although electronic computers are relatively new, the need for computation is not.
26
The earliest recognized device for computing was the Abacus, invented in Mesopotamia around 2500 BCE.
27
It's essentially a hand -operated calculator that helps add and subtract many numbers.
28
It also stores the current state of the computation, much like your hard drive does today.
29
The Abacus was created
30
because the scale of society had become greater than what a single person could keep and manipulate in their mind.
31
There might be thousands of people in a village or tens of thousands of cattle.
32
There are many variants of the abacus
33
but let's look at a really basic version with each row representing a different power of 10.
34
So each bead on the bottom row represents a single unit.
35
In the next row they represent 10, the row above 100 and so on.
36
Let's say we have three heads of cattle represented by three beads on the bottom row on the right side.
37
If we were to buy four more cattle we would just
38
slide four more beads to the right for a total of seven.
39
But if we were to add five more after the first three we would run out of beads.
40
So we would slide everything back to the left, slide one bead on the second row to the right representing 10, and then add the final two beads on the bottom row for a total of 12.
41
This is particularly useful with large numbers.
42
So if we were to add 1 ,251 we would just add one to the bottom row, five to the second row, two to the third row, and one to the fourth row.
43
We don't have to add in our head and the abacus stores the total for us.
44
Over the next 4 ,000 years, humans developed all sorts of clever computing devices like the astrolabe, which enabled ships to calculate their latitude at sea,
45
or the slide rule for assisting with multiplication and division.
46
And there are literally hundreds of types of clocks created that could be used to calculate sunrise, tides, positions of celestial bodies, and even just the time.
47
Each one of these devices made something that was previously laborious to calculate much faster, easier, and often more accurate.
48
It lowered the barrier to entry, and at the same time amplified our mental abilities.
49
Take note, this is a theme we're going to touch on a lot in this series.
50
As early computer pioneer Charles Babbage said, At each increase of knowledge, as well as on the contrivance of every new tool, human labour becomes abridged.
51
However, none of these devices were called computers.
52
The earliest documented use of the word computer is from 1613 in a book by Richard Braithwaite, and it wasn't a machine at all, it was a job title.
53
Braithwaite said, I have read the truest computer of times
54
and the best arithmetician that ever breathed and he reduced it by days into a short number.
55
In those days computer was a person who did calculations sometimes with the help of machines but often not.
56
This job title persisted until the late 1800s
57
when the meaning of computers started shifting to refer to devices
58
and notable among these devices was the step reckoner built by German polymath Gottfried Leibniz in 1694.
59
Leibniz said, It is beneath the dignity of excellent men to waste their time in calculation
60
when any peasant could do the work just as accurately with the aid of a machine.
61
It worked kind of like the odometer in your car, which is really just a machine for adding up the number of miles your car is driven.
62
The device had a series of gears that turned.
63
Each gear had 10 teeth to represent the digits from 0 to 9.
64
Whenever a gear bypassed 9, it rotated back to 0 and advanced the adjacent gear by 1 tooth.
65
Kind of like when hitting 10 on that basic abacus.
66
This worked in reverse when doing subtraction too.
67
With some clever mechanical tricks, the step reckoner was also able to multiply and divide numbers.
68
Multiplications and divisions are really just many additions and subtractions.
69
For example, if we want to divide 17 by 5, we just subtract 5, then 5, then 5 again, and then we can't subtract any more 5s.
70
So we know 5 goes into 17 3 times, with 2 left over.
71
The step reckoner was able to do this in an automated way, and was the first machine that could do all 4 of these operations.
72
And this design was so successful, it was used for the next three centuries of calculator design.
73
Unfortunately, even with mechanical calculators, most real -world problems required many steps of computation before an answer was determined.
74
It could take hours or days to generate a single result.
75
Also, these handcrafted machines were expensive and not accessible to most of the population.
76
Before the 20th century, most people experienced computing through pre -computated tables, assembled by those amazing human computers we talked about.
77
So if you needed to know the square root of 8 ,675 ,309, instead of spending all day hand -cranking your step -reckoner,
78
you could look it up in a huge book full of square root tables in a minute or so.
79
Speed and accuracy is particularly important on the battlefield, and so militaries were among the first to apply computing to complex problems.
80
A particularly difficult problem is accurately firing artillery shells, which by the 1800s could travel well over a kilometre, or a bit more than half a mile.
81
Add to this, varying wind conditions, temperature, and atmospheric pressure, and even hitting something as large as a ship was difficult.
82
Range tables were created that allowed gunners to look up environmental conditions and the distance they wanted to fire, and the table would tell them the angle to set the cannon.
83
These range tables worked so well, they were used well into World War II.
84
The problem was, if you changed the design of the cannon or of the shell, a whole new table had to be computed, which was massively time consuming and inevitably led to errors.
85
Charles Babbage acknowledged this problem in 1822 in a paper to
86
the Royal Astronomical Society entitled Note on the application of machinery to the computation of astronomical and mathematical tables.
87
Let's go to the thought bubble.
88
Charles Babbage proposed a new mechanical device called the difference engine, a much more complex machine that could approximate polynomials.
89
Polynomials describe the relationship between several variables, like range and air pressure, or amount of pizza Carrie -Anne eats and happiness.
90
Polynomials could also be used to approximate logarithmic and trigonometric function, which are a real hassle to calculate by hand.
91
Babbage started construction in 1823, and over the next two decades tried to fabricate and assemble the 25 ,000 components, collectively weighing around 15 tons.
92
Unfortunately, the project was ultimately abandoned.
93
But in 1991, historians finished constructing a difference engine based on Babbage's drawings and writings.
94
And it worked!
95
But more importantly, during construction of the difference engine, Babbage imagined an even more complex machine, the Analytical Engine.
96
Unlike the Difference Engine, Step Reckon and all other computational devices before it, the Analytical Engine was a general purpose computer.
97
It could be used for many things, not just one particular computation.
98
It could be given data and run operations in sequence, it had memory and even a primitive printer.
99
Like the Difference Engine, it was ahead of its time and was never fully constructed.
100
However, the idea of an automatic computer, one that could guide itself through a series of operations automatically was a huge deal and would foreshadow computer programs.
101
English mathematician Ada Lovelace wrote hypothetical programs for the Analytical Engine, saying a new, a vast and a powerful language is developed for the future use of analysis.
102
For her work, Ada is often considered the world's first programmer.
103
The Analytical Engine would go on to inspire arguably the first generation of computer scientists, who incorporated many of Babbage's ideas in their machines.
104
This is why Babbage is often considered the father of computing.
105
Thanks Sportbubble!
106
So, by the end of the 19th century, computing devices were used for special purpose tasks in the sciences and engineering, but rarely seen in business, government or domestic life.
107
However, the US government faced a serious problem for its 1819 census
108
that demanded the kind of efficiency that only computers could provide.
109
The US Constitution requires that a census be conducted every 10 years, for the purposes of distributing federal funds, representation in Congress and good stuff like that.
110
And by 1880, the US population was booming, mostly due to immigration.
111
That census took 7 years to manually compile, and by the time it was completed, it was already out of date.
112
And it was predicted that the 1819 census would take 13 years to compute.
113
That's a little problematic when it's required every decade.
114
The Census Bureau turned to Herman Hollerith, who built a tabulating machine.
115
His machine was electromechanical.
116
It used traditional mechanical systems for keeping count.
117
like Liebenitz's step reckoner, but coupled them with electrically powered components.
118
Holleriff's machine used punch cards, which were paper cards with a grid of locations that could be punched out to represent data.
119
For example, there was a series of holes for marital status.
120
If you were married, you would punch out the married spot.
121
Then when the card was inserted into Holleriff's machine, little metal pins would come down over the card.
122
If a spot was punched out, the pin would pass through the hole in the paper and into a little vial of mercury, which completed the circuit.
123
This now -completed circuit powered an electric motor, which turned a gear to add one, in this case, to the married total.
124
Holleriff's machine was roughly 10 times faster than manual tabulations, and the census was completed in just two and a half years, saving the census office millions of dollars.
125
Businesses began recognizing the value of computing, and saw its potential to boost profits by improving labor and data -intensive tasks, like accounting, insurance appraisals and inventory management.
126
To meet this demand, Holleriff founded the Tabulating Machine Company, which later merged with other machine makers in 1924 to become the International Business Machines Corporation,
127
or IBM, which you've probably heard of.
128
These electromechanical business machines were a huge success, transforming commerce and government, and by the mid -1900s,
129
the explosion in world population and the rise of globalized trade demanded even faster and more flexible tools for processing data, setting the stage for digital computers,
130
which we'll talk about next week.
131
Crash Course Computer Science is produced in association with PBS Digital Studios.
132
At their channel you can check out a playlist of shows like PBS Idea Channel, Physics Girl and It's OK To Be Smart.
133
This episode was filmed at the Chad and Stacey Emmergoltz Studio in Indianapolis, Indiana.
134
And it was made with the help of all these nice people and our wonderful graphics team Thought Cafe.
135
Thanks for watching, I'll see you later.
136
Thank you.
📺 Zelfde Kanaal
C11
Vectors and 2D Motion: Crash Course Physics #4
TOEFL PrepCambridge Exam PrepUniversity Students
C11
How Often do Asteroids Hit the Earth?: Crash Course Geology #20
IELTS PrepTOEFL PrepUniversity Students
C1What's all the Yellen About? Monetary Policy and the Federal Reserve: Crash Course Economics #10
IELTS PrepBusiness EnglishUniversity Students
C12
Unit Conversion & Significant Figures: Crash Course Chemistry #2
Business EnglishUniversity StudentsWorking Adults
C11
What Is Myth? Crash Course World Mythology #1
Cambridge Exam PrepUniversity Students
B25
Mesopotamia: Crash Course World History #3
Cambridge Exam PrepHigh School StudentsUniversity Students
B210
Crash Course Sex Ed Preview
Daily ConversationUniversity StudentsWorking Adults
C110
The Agricultural Revolution: Crash Course World History #1
IELTS PrepTOEFL PrepCambridge Exam Prep
C12
Derivatives: Crash Course Physics #2
Cambridge Exam PrepUniversity StudentsWorking Adults
B23
Indus Valley Civilization: Crash Course World History #2
Cambridge Exam PrepHigh School StudentsUniversity Students
B22
Ancient Egypt: Crash Course World History #4
Cambridge Exam PrepHigh School StudentsUniversity Students
C12
What is Engineering?: Crash Course Engineering #1
Business EnglishUniversity StudentsWorking Adults
B22
The Persians & Greeks: Crash Course World History #5
Cambridge Exam PrepHigh School StudentsUniversity Students
C12
Supervised Learning: Crash Course AI #2
Business EnglishUniversity StudentsWorking Adults
C13
The Periodic Table: Crash Course Chemistry #4
IELTS PrepTOEFL PrepCambridge Exam Prep
B22
Where Do Diamonds Come From?: Crash Course Geology #8
IELTS PrepTOEFL PrepCambridge Exam Prep
B29
Why You Need Trust to Do Business: Crash Course Business - Soft Skills #1
Business EnglishUniversity StudentsWorking Adults
C13
Where Did Democracy Come From, and Does It Still Work?
IELTS PrepTOEFL PrepUniversity Students
C12
The Nucleus: Crash Course Chemistry #1
IELTS PrepTOEFL PrepUniversity Students
B21
Defense Against the Dark Arts of Influence: Crash Course Business Soft Skills #2
Business EnglishUniversity StudentsWorking Adults
✨ Aanbevolen Video
C12
14 zinnen
CS50x 2026 - Introduction
Business EnglishUniversity StudentsWorking Adults
C11
40 zinnen
The Engineering that Runs the Digital World 🛠️⚙️💻 How do CPUs Work?
Business EnglishUniversity StudentsWorking Adults
C15
106 zinnen
A Career in IT
Business EnglishUniversity StudentsWorking Adults
C12
162 zinnen
Crypto Agility Explained: Protect Data from Quantum Computing Threats
Business EnglishUniversity StudentsWorking Adults
C11
162 zinnen
Introduction to PLC | Siemens PLC Training Course
Business EnglishUniversity StudentsWorking Adults
C117
118 zinnen
Computational Linguistics: Crash Course Linguistics #15
Business EnglishUniversity StudentsWorking Adults
C13
81 zinnen
Everything You Need to Know About DNS: Crash Course System Design #4
Business EnglishUniversity StudentsWorking Adults
C1155 zinnen
Every Hardware Protocol Explained Simply in 10 Minutes!
Business EnglishUniversity StudentsWorking Adults
C11
12 zinnen
Rapid Engineering With AI
Business EnglishUniversity StudentsWorking Adults
C1105 zinnen
100+ Docker Concepts you Need to Know
American AccentBusiness EnglishUniversity StudentsWorking Adults
C185 zinnen
Is Embedded Systems Still a Good Career in 2026?
Business EnglishUniversity StudentsWorking Adults
Woordenschat en spreektips bij deze les
Deze spreekles op niveau C1 is gebaseerd op de video “Early Computing: Crash Course Computer Science”. Deze woorden komen het vaakst terug: computer, machine, row, computing, device. Deze video bevat 136 zinnen en 2258 woorden om na te spreken. Het gesproken deel duurt 11:49. De spreker praat snel, ongeveer 191 woorden per minuut, dus reken op verbonden en ingeslikte klanken. Slechts 79% van de woorden hoort bij de 3.000 meest gebruikte Engelse woorden, dus de woordenschat is pittig.
Belangrijke woorden in deze video
De 15 moeilijkste woorden uit de video, met uitspraak en betekenis:
| Woord | Uitspraak | Betekenis |
|---|---|---|
| compute werkwoord | /kəmˈpjuːt/ | uitrekenen, berekenen |
| abacus zelfstandig naamwoord | /ˈæb.ə.kəs/ | abacus, telraam |
| computation zelfstandig naamwoord | /ˌkɑmpjʊˈteɪʃn̩/ | berekening |
| bead zelfstandig naamwoord | /ˈbiːd/ | kraal |
| calculate werkwoord | /ˈkælkjʊleɪt/ | berekenen, uitwerken |
| polynomial zelfstandig naamwoord | /ˌpɑliˈnoʊmiəl/ | polynoom, veelterm |
| subtract werkwoord | /səbˈtɹækt/ | aftrekken, in mindering brengen |
| astronomical bijvoeglijk naamwoord | /ˌæs.tɹəˈnɑm.ɪ.kəl/ | astronomisch |
| automate werkwoord | /ˈɔ.təˌmeɪt/ | automatiseren |
| transistor zelfstandig naamwoord | /tɹænˈzɪs.tɚ/ | transistor |
| calculator zelfstandig naamwoord | /kæl.kjə.leɪ.tɚ/ | rekenmachine, zakrekenmachine |
| assemble werkwoord | /əˈsɛm.bəl/ | in elkaar zetten |
| approximate bijvoeglijk naamwoord | /əˈpɹɑk.sə.mət/ | benaderend |
| calculation zelfstandig naamwoord | /ˌkælkjuˈleɪʃn̩/ | berekening |
| arguably bijwoord | /ˈɑɹɡjuəbli/ | onderbouwbaar, verdedigbaar |
Phrasal verbs die je zult horen
| Woord | Uitspraak | Betekenis |
|---|---|---|
| break down werkwoord | stukgaan, kapot gaan | |
| check out werkwoord | onderzoeken | |
| look up werkwoord | /ˌlʊk ˈʌp/ | opkijken |
| shut down werkwoord | afsluiten, uitzetten | |
| turn off werkwoord | uitzetten, uitschakelen |
Grammatica in deze video
De structuren die de spreker het meest gebruikt, met de exacte woorden uit de video:
| Structuur | In de video |
|---|---|
| Voorwaardelijke zinnen if + zin, will/would + werkwoord — een voorwaarde en het gevolg | If you were married, you would punch |
| Lijdende vorm be + voltooid deelwoord — het gaat om wat er gebeurt, niet om wie het doet | are made · be remembered · was programmed |
| Betrekkelijke bijzinnen who / which + zin — extra informatie over een persoon of ding | person who did · car, which is · computed, which was |
| Present perfect have/has + voltooid deelwoord — iets uit het verleden dat nu nog telt | has transformed · we've seen · have read |
Uitspraak om op te letten
De spreker gebruikt 22 samentrekkingen en verkorte vormen, zoals we're, don't, doesn't. Spreek ze kort uit, zoals je ze hoort.
- De “th”-klanken: hypothetical /ˌhaɪpəˈθɛtɪkəl/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/, tooth /tuθ/
- De klanken “sh” en “zh”: computation /ˌkɑmpjʊˈteɪʃn̩/, calculation /ˌkælkjuˈleɪʃn̩/, abstraction /æbˈstɹæk.ʃn̩/, telecommunication /ˌtɛləkəˌmjunɪˈkeɪʃən/, computational /ˌkɑmpjʊˈteɪʃənəl/
- Lange woorden — let op de klemtoon: polynomial /ˌpɑliˈnoʊmiəl/, astronomical /ˌæs.tɹəˈnɑm.ɪ.kəl/, calculator /kæl.kjə.leɪ.tɚ/, approximate /əˈpɹɑk.sə.mət/, accurately /ˈæk.jə.ɹɪt.li/
Zo oefen je met deze video
- Luister de hele video één keer zonder te spreken en noteer de woorden die je niet kent.
- Begin op 0,75× snelheid, spreek zin voor zin na en ga terug naar normale snelheid zodra het makkelijk gaat.
- Neem jezelf op en vergelijk met het origineel; let daarbij op woorden als compute, abacus, computation.
Wat is de Shadowing-techniek?
Shadowing is een wetenschappelijk onderbouwde taalleermethode die oorspronkelijk is ontwikkeld voor professionele tolkentraining en gepopulariseerd door polyglot Dr. Alexander Arguelles. De methode is eenvoudig maar krachtig: je luistert naar native Engelse audio en herhaalt het onmiddellijk hardop — als een schaduw die de spreker volgt met slechts 1–2 seconden vertraging. In tegenstelling tot passief luisteren of grammaticadrills, dwingt shadowing je hersenen en mondspieren om echte spraakpatronen tegelijkertijd te verwerken en te reproduceren. Onderzoek toont aan dat het de uitspraaknauwkeurigheid, intonatie, ritme, verbonden spraak, luisterbegrip en spreekvaardigheid aanzienlijk verbetert — waardoor het een van de meest effectieve methoden is voor IELTS Speaking-voorbereiding en echte Engelse communicatie.