Shadowing Practice: 1. Apa Itu COMPUTATIONAL THINKING? - Learn English Speaking with Video
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Hello everyone, welcome back to the channel WPU with me Sandika Gali.
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And in this video, we will start a new series.
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Series that I think is important to learn, especially for you who will learn programming, you are a business or a IT,
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or you will learn to learn to learn programming.
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Series is called Computational Thinking, or the way to computer computer.
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And in the first video of the series, we will begin to talk about computational thinking.
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But before we talk about the definition, we will see why we have the ability to think about computational thinking.
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Why computational thinking is important to learn?
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Why?
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So, let's see how important is this, and that computational thinking is a skill for the whole community,
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from young people to young people.
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There are several reasons that are behind the important computational thinking.
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First of all, score PISA.
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What is score PISA?
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So score PISA is the program for international student assessment,
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Sebuah study yang diselenggarakan oleh OECD Atau Organization for Economic Cooperation and Development Jadi ceritanya,
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ada survey yang dilakukan secara internasional Untuk mengetahui tingkat literasi dasar
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dari siswa usia 15 tahun Jadi sebuah tes yang dilakukan terhadap
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seluruh siswa yang ada di dunia Di umur 15 tahun Yang
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soal-soalnya terkait dengan reading atau membaca matematika dan juga sains Dan PISA ini dilaksanakan setiap 3 tahun sekali
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and Indonesia has been followed from the beginning of the year 2000.
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The last thing is done in the year 2018, the last thing is done by 12.000 more people or more people,
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which are the ones who have been involved in 3,7 people from 7 to 12.
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And it must have been done in the year 2021, but because of the pandemic, the test is still still in the year 2022.
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And the result will be released in 2023.
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So, it's not a result of the year.
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If we look at the results of 2018,
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we can see that the ability of Indonesia is in the lower countries of Indonesia is in the lower countries of Asia.
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For the countries of Asia, we have in 413, while we have in 371.
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So, it's pretty sad that the score is still in the lower countries.
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What is the result of the score of PISA?
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Nah, kalau kita lihat di sini, jadi akibatnya adalah keahlian dasar dari tenaga kerja di Indonesia itu sangat rendah.
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Keahlian dasar loh ini ya.
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Terus juga, kalau misalkan kita bandingkan keahlian tenaga kerja lulusan pendidikan tinggi,
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universitas dan setara ya, di Indonesia itu setara dengan keahlian tenaga kerja lulusan SMA ke bawah di negara lain.
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Ini contohnya di Denmark.
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Jadi, lulusan kuliah kita itu kemampuan dasarnya disamakan dengan lulusan SMA di Denmark.
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So it's quite a bit, because the value of the PISA is less.
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So the target of the future is that we want to increase the value of the PISA.
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So that the value of the PISA is also increased.
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That's what we can achieve if, for example, if we have the ability to think about the PISA's ability to think about.
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That's the first one.
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The second one, many research or research that's important that the ability to think about the PISA's ability to think about.
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If you look at the UNESCO, So, skill that's the basic communication of humans, starting from the skills of thinking, then communication in the oral,
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then literacy, the skill that's becoming higher, then speaking, then listening, then literacy,
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then reading, then writing, then skills-skills of the other.
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Then, then into ICT, Information Communication Technology Skills, or media literacy, using digital technology, using communication,
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Jaringan dan lain sebagainya Baru naik lagi ke information literacy
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Nah ini semuanya kemampuan Komunikasi dasar manusia ini diawali Dengan skill
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reasoning atau Skill berpikir dan ini juga berpengaruh Ke kemampuan computational
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thinking Semakin bagus computational thinking kita Maka kemampuan berpikir kita akan
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semakin Baik ya ini juga sejalan dengan Higher order thinking skills
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Atau HOTS ya kalau kita lihat diagram Dari Bloom's taxonomy atau
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Taxonomy Bloom ini adalah tingkatan Dari skill berpikir manusia Mulai dari
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skill yang paling dasar itu remembering Bagaimana kita mengingat Yang kedua
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itu understanding Bagaimana kita memahami Terus ada applying Menerapkan Dan seterusnya ada creating, evaluating, dan analyzing
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Ini juga yang mempengaruhi tingkatan dari Cara berpikir manusia Ya jadi
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itu yang kedua Bahwa kemampuan berpikir itu penting Sebuah alasan lain
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Dimana kita harus mempelajari computational thinking Alasan yang ketiga Adalah sekarang we are currently in the 4.0 industry.
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If you look at this, we are now already in computer and automation.
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Now we are now in cyber physical system.
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Now we are now in AI.
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Where now we are now in AI.
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So if we don't have the ability to think about computing, we will be left.
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The next thing is that we already have curriculum.
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Merdeka.
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Jadi pemerintah kita juga Sudah memasukkan computational thinking Ini masuk ke dalam kurikulum Bahkan kalau teman-teman lihat Di diagram ini ya,
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ini adalah karakteristik Kurikulum di setiap jenjang pendidikan Di Indonesia, mulai dari PAUD sampai Dengan SMK dan SLB.
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Nah kalau teman-teman Baca, computational thinking ini Sudah masuk dari sejak SD Dan SMP itu mata pelajaran Informatika itu menjadi mata pelajaran Wajib.
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Jadi punya pola pikir Computational itu harus dari sejak Dini kita
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pelajari atau terapkan Lalu juga pemahaman mengenai informatika juga sudah mulai dipelajari sejak dini ya, sejak SMP
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Nah jadi kalau misalnya teman-teman baru mengetahui apa itu computational thinking
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Terus bagaimana cara mempelajari computational thinking Sedangkan kita udah ada di
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jenjang yang lebih tinggi Sebetulnya itu agak sedikit terlambat Karena yang
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namanya computational thinking itu harusnya sudah kita pelajari sedini mungkin Ya tapi nggak apa-apa ya,
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nggak ada salahnya kalau kita pelajari kembali Meskipun kita sudah lewat dari jenjang pendidikan dasar ini Ya teman-teman,
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jadi sekali lagi itu adalah alasan-alasan why we have to have the ability to do computational thinking
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and why we have to learn about computational thinking that is a lot and important thing.
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Now we are going to go to the topic next, what is computational thinking?
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What is it?
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Let's see, in the definition, we read it together, computational thinking is a process of thinking that happens when we formulate a question
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and will be strategic to find Atau memilih solusi yang efektif, efisien, dan optimal
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Nah ini penting banget nih Ya jadi sekali lagi dia adalah proses berpikir Saat kita memformulasikan persoalan Mencari akar permasalahan,
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mencari solusi Dan berstrategi terhadap solusi tadi Sehingga solusinya tidak cuma efektif Naik jadi efisien,
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naik lagi jadi optimal Ya karena efektif aja itu kan hanya ngefek aja ya Do the right things,
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kalau efektif If efficient, do the right things right.
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Add to optimal.
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Definitioning is that computational thinking is the ability to think with the technology or computer as a help.
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So if we find a problem, after we find a problem, when we find a solution,
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we think we need tools or technology to finish.
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I have a simple example of that, that we can do in the daily lives.
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For example, you can do a simple example.
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You can do a good example, you can do a good example, then you can do a good example, and when you do a good example,
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all of them like, then you can do a good example.
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It must be thought that we had to do a little bit, using tools that are in our house, we must think about how we can do a good example,
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so that we can make a sample with more and then the time is maybe shorter.
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So we have to think about the next step.
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Maybe from the manual, we need a blender
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so that we can make a blender faster because we need a lot of more.
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After we give it to our family, then our family will be like, then our family will tell us that they will make a sample that they will make a sample.
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Then our family will also want to think about it.
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So that you can think about it, more than a lot of things, maybe more than a lot of things, maybe with a faster time.
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How can it be made to make it easier, longer, longer, more than a lot, and so on.
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Next, if you want more than a lot of things, you must think about automation, machine, how to sell, and so on.
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The case of the sederhana that can be used to use computational thinking as a help to help to solve problems,
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so that solution is effective, efficient, and optimal.
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Atau contoh lain lah, misalkan kalian digigit nyamuk nih, di rumah.
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Nah, terus kan berikutnya gimana caranya kita akan menghilangkan nyamuk ini?
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Kan solusinya macam-macam.
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Kalau nyamuknya cuma satu, ditepuk aja lah.
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Kalau nyamuknya banyak gimana?
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Mungkin solusinya bisa pakai raket nyamuk.
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Tapi kalau misalkan kalian pengen tidurin nyanyakan, nggak mungkin terjaga semalaman megangin raket nyamuk.
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Mungkin pakai ubat nyamuk.
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Jadi solusinya harus tepat sesuai dengan masalahnya apa.
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Ya nggak mungkin kalian melakukan ini ya.
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Kalian nggak mungkin bakar rumahnya.
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Mungkin nyamuknya hilang.
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But it will cause a new problem.
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So, the solution is not like this.
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Or, for example, if you choose a road when you go to home, or to home, or to school.
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When you say Google Maps, a road that is different, this is probably what you think.
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I think, if I'm not going to follow the road, it's not a good idea of Google Maps.
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Maybe the time is short, but you know if you go to the road, it's not a good idea.
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If you go to the road, there's a road that's not a bad idea.
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So, know, there's a lot of people sleeping, so you can just take a seat.
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So you can just choose a little bit of a path, but you feel comfortable.
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And that you must do in a quick time.
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You can go on the Google Maps, you can use a different route.
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You must make sure to decide.
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With the ability of computational thinking, it will help you give a good solution.
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For example, if we make a recipe for a meal or a meal, computational thinking akan membantu membuat itu menjadi lebih runut,
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menjadi lebih detail atau misalkan saat kalian ingin membuat mind map
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pada sebuah topic atau kalau misalkan sudah masuk ke aplikasi atau
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pengelolaan data computational thinking juga dipakai untuk memecahkan masalahnya menggunakan tools
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yang ada kira-kira bagaimana cara kita pakai software spreadsheet seperti Excel
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misalnya ketika kita punya data yang banyak sampai dengan kalian masuk
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ke programming computational thinking akan membantu ketika kalian memecahkan masalah menggunakan programming That's it in some examples.
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You can see that when we put computational thinking, we can find solutions that are more efficient, more efficient, and more optimal.
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Even if you have done all this, and you don't feel like you already have done computational thinking.
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But with what we know, we will be able to get more efficient, so that the solution is more efficient and optimal.
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So with computational thinking, it will help us to ask questions.
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So, if we already understand computational thinking, we will ask this example.
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Is that a question that is done with easier than humans or computers?
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Can we not have a computer in problems?
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Then, the next question is, is there a question between the question that we have to face with the same or similar or similar?
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That we have to have a question before?
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We think like this, Oh, it's like we've done a lot of problems before.
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Although it's not the same, but we can get a question.
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So computational thinking is going to be able to know the following.
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Next question is if we are looking at data, how can data can be used to solve the problem for the question?
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So we are going to ask for questions like that.
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Then how can we make a solution for a common question with a different input?
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So if we are using input, output is how?
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Atau misalnya pertanyaan berikutnya, apa aja sih langkah-langkah yang runut yang bisa kita gunakan untuk menyelesaikan persoalan yang dihadapi?
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Jadi saat kita menghadapi persoalan itu yang kepikir langsung langkah yang runutnya seperti apa?
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Terus ada strategi komputasi nggak nih yang bisa kita gunakan ke persoalan yang lagi kita hadapi?
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Dan pertanyaan berikutnya adalah, kira-kira apa aja keterbatasan kompromi dan kendala yang dihadapi ketika kita lagi menyelesaikan persoalan?
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So computational thinking will always be able to ask questions this.
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Why?
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Because in computational thinking there are elements that make us ask questions.
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There are some decomposing, there are abstraction, pattern recognition, and algorithms.
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This is computational thinking known as AADP.
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That we will talk more detail in the next video.
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Pokoknya tadi, why can we ask that question?
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Because we are usually used to be able to do component or component of computational thinking.
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Maybe the question is, how do we do?
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How do we do?
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Because the computational thinking is not just to learn and understand.
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The answer is to be with the latihan, latihan, and latihan.
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The first thing is, it's the most easy to do.
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And even the most easy to do is to do it.
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It's a problem solving We can use the problem solving We can use the problem solving
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We can use analysis data We can use modeling and simulation And also programming For problem solving,
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you can use the problem solving We can use the problem solving So,
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the problem solving is a international organization For computational thinking You can visit www.bebras.org Or in Indonesia,
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there is www.bebras.org.id If you want to see the problem solving What you can see here.
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We can see some examples.
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This is the level.
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Even from SD.
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Let's see.
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Now, this is the video.
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Let's see.
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Pause the video.
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Let's work.
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Maybe we can talk about how to work.
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And also the solution.
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In the next video.
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This is the first.
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This is the first one. From Canada.
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So, Simon Says.
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Atau, D. So, Simon. So, Simon. So, Simon.
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So, if you press.
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If you press.
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If you press the button, the button is in the middle, the color will be changed like the video.
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So if we have the beginning of the video, when the button is pressed, it will be changed like this.
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So, the red button is to the right, the yellow button is to the right, and then.
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If you press the button again, then the question is, if we press the button again, where will you let it blue, blue, green, and green?
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Now, this is the answer.
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The answer is with a red button, and then we drag or move the white color.
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This is about the computational thinking for SD.
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So, this can be done by playing.
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Next, if we look at the SMP.
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So, from Turkey.
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It's called by Turkey.
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Let's see if you want to work.
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Please pause the video.
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Ingenieur Bebras, Berang-Berang, wants to maintain the banjir.
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He has a set-up of tree tree.
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Like this one.
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like this.
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He wants to make a bend like this.
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So, the result is like this.
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Diagonal.
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He needs one jam to move the set of the baton to the vertical.
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So, if I want to make a bend like this, he needs one jam.
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One time, one time.
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If he needs to be left, he needs two hours.
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Now, let's see.
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Minimal how many hours needed by the engineer this to build bend.
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Nah, silahkan dihitung ya.
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Cari yang paling optimal, kira-kira paling cepat dia butuh untuk jadi begini itu berapa jam.
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Itu soal untuk SMP.
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Dan berikutnya kita lihat ini soal untuk SMA.
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Soalnya Infinite Ice Cream.
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Jadi ceritanya gini, ada dua kiosk penjual es krim warna-warni.
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Dua-duanya sama, dua kiosk ini jual es krim warna-warni dengan warna yang sama.
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Merah, kuning, ungu, dan hijau.
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The ice cream on the stand first, the first one has a policy to make ice cream.
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Where is the policy?
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First, it's the first one.
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It's always starting with the cone.
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Next, it's the first one.
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If you choose the color, then add the color.
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So, if you choose the color, it will add the color.
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Okay, next, we add one bullet with a different color.
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So, if the three is not the same color.
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If the three is already according to the customer, then it's already.
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But if not, we'll do it again from the beginning of the first.
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So, we'll take a random one again, add one one, add one one, add one one.
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That's the first one.
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Or the first one.
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Now, the question is, what is the first one?
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Atau istilahnya, manakah dari 4 es krim berikut ini yang bukan buatan toko yang pertama?
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Nah, silahkan.
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Kalian bisa nebak kan nih kira-kira.
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Ya, jadi latihan-latihan Bebras tuh seperti itu untuk melatih cara berpikir komputasi kita.
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Atau kalau misalkan kalian udah mau masuknya ke programming, kan kalau ini melatih cara berpikir ya.
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Kalau udah masuk ke programming, kalian bisa latihan melalui website-website Coding Challenge ini.
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Ya, ada Code Wars, Lead Code, Hacker Rank, Code Chef.
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Cuman memang ini yang udah jelas mau melatih logika pemrograman.
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Contohnya seperti ini, kita kasih soal, disuruh ngerjain di website-nya langsung.
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Jadi itu mungkin latar belakang singkat mengenai computational thinking.
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Kita bacakan dulu kesimpulannya.
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Yang pertama, computational thinking adalah kemampuan berpikir fundamental.
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Jadi dia cara berpikir dasar yang harus dimiliki oleh siapapun.
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Yang tujuannya adalah untuk menuju ke solusi.
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Jadi computational thinking adalah proses berpikir menuju ke solusi.
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Dari mulai mencari akar permasalahan sampai dengan menentukan solusi.
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Computational thinking adalah konseptualisasi bukan programming.
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Jadi konsepnya dulu.
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Apakah bermanfaat untuk kita saat melakukan programming?
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Ya.
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Ya kan bahkan ada istilah yang bilang, First solve the problem, then write the code.
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Jadi sebenarnya permasalahannya harus selesai dulu.
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Baru kita nulis baris-baris kodenya.
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Nah itu adalah computational thinking.
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Jadi dia konseptualisasi dulu bukan programmingnya.
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Lalu berikutnya, computational thinking itu bisa diterapkan di semua bidang.
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Kalau bidangnya IT, dia akan menghasilkan solusi yang terprogram.
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Sedangkan kalau bidangnya non-IT, computational thinking itu berfungsi untuk mendekatkan kalau misalnya solusinya membutuhkan komputasi.
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Jadi pakai computational thinking akan membuat solusinya jadi lebih efisien.
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Lalu berikutnya, computational thinking itu adalah literasi juga.
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Jadi nggak lepas dari membaca, menulis, dan juga berbicara.
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Plus menghitung tadi ya.
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And the last thing, computational thinking must be done.
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So it's not just to learn, to learn, to learn, to learn, to learn, to learn, to learn.
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It's not just to learn, to learn.
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So, it's always to learn.
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So, it's a quick explanation about computational thinking and why computational thinking is important for us to be.
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It's really important to know.
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So, in the episode or in the next episode, we will talk about more detail about the component-component that has in computational thinking.
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That's what we call AADP.
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Or, Abstraction, Algorithm, Decomposition, and Pattern Recognition.
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So, maybe that's it for this video.
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Thank you for your time.
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We'll see you in the next episode.
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I'm Sadiq Gali.
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And as always, don't forget to comment.
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I'm going to go to the next one.
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Vocabulario y notas de pronunciación para esta lección
Esta lección de conversación de nivel B1 se basa en el vídeo “1. Apa Itu COMPUTATIONAL THINKING?”. Las palabras que más se repiten: thinking, computational, yang, kita, jadi. Este vídeo tiene 290 frases y 3208 palabras para practicar shadowing. La parte hablada dura 19:58. El hablante habla a un ritmo natural de unas 161 palabras por minuto, cercano a una conversación cotidiana. Solo el 62 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es exigente.
Vocabulario clave de este vídeo
Las 15 palabras más avanzadas del vídeo, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| computational adjetivo | /ˌkɑmpjʊˈteɪʃənəl/ | computacional |
| optimal adjetivo | /ˈɑptɪməl/ | óptimo, en fa |
| literacy sustantivo | /ˈlɪtəɹəsi/ | alfabetismo, alfabetización |
| sole sustantivo | /səʊl/ | planta, planta del pie |
| component sustantivo | /kəmˈpoʊ.nənt/ | componente |
| pale adjetivo | /peɪl/ | pálido |
| bend verbo | /bɛnd/ | cimbrar, cimbrear |
| abstraction sustantivo | /æbˈstɹæk.ʃn̩/ | abstracción |
| blender sustantivo | /ˈblɛn.dɚ/ | licuadora |
| kiosk sustantivo | /ˈkiˌɑsk/ | quiosco, kiosco |
| taxonomy sustantivo | /tækˈsɑnəmi/ | taxonomía |
| prose sustantivo | /ˈpɹoʊz/ | prosa |
| automation sustantivo | /ˌɔ.təˈmeɪ.ʃən/ | automatización |
| diagram sustantivo | /ˈdaɪ.ə.ɡɹæm/ | diagrama |
| pause sustantivo | /pɔːz/ | pausa |
Frases que vale la pena repetir
Frases cortas y completas del vídeo que puedes reutilizar en la conversación diaria:
- Can we not have a computer in problems?
- That we have to have a question before?
- Pokoknya tadi, why can we ask that question?
- Maybe the question is, how do we do?
- How do we do?
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Oraciones condicionales if + oración, will/would + verbo — una condición y su resultado | if you choose the color, it will add |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | is called · has been followed · have been involved |
| Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora | has been followed · have been involved · have done |
Pronunciación a tener en cuenta
El hablante usa 10 contracciones y formas reducidas, como don't, I'm, we'll. Dilas en su forma corta, tal como las oyes.
- Los sonidos de “sh” y “zh”: computational /ˌkɑmpjʊˈteɪʃənəl/, abstraction /æbˈstɹæk.ʃn̩/, automation /ˌɔ.təˈmeɪ.ʃən/, simulation /ˌsɪm.jəˈleɪ.ʃn̩/
- Palabras largas — cuida el acento: computational /ˌkɑmpjʊˈteɪʃənəl/, literacy /ˈlɪtəɹəsi/, taxonomy /tækˈsɑnəmi/, automation /ˌɔ.təˈmeɪ.ʃən/, curriculum /kəˈɹɪk.jə.ləm/
Sonidos difíciles para hispanohablantes:
- /v/ — no es /b/: los dientes tocan el labio inferior: evaluate /ɪˈvaljʊeɪt/, vertical /ˈvɝ.tɪ.kəl/
- /z/ — sonora, no /s/: prose /ˈpɹoʊz/, pause /pɔːz/, analyze /ˈæn.əˌlaɪz/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Empieza a velocidad 0,75×, haz shadowing frase por frase y vuelve a la velocidad normal cuando te resulte fácil.
- Grábate y compara con el original, prestando atención a palabras como computational, optimal, literacy.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.