Through my learning of computational thinking, as I said earlier. It was my key to unlocking the key to writing computer code. I think that if I hadn't learned this lesson, I would still not have established a proper logic of thinking about writing code difficult and complicated. This would have been intimidating to my learning of the course and dertrimental to my learning of programming. But when I got exposed to it, I felt as if code wasn't so hard for me! I feel excited because I'm going to start designing a web page of my own.
Of course, apart from all these exciting things, I also encountered a lot of difficulties during the learning process. For example, I was always unable to make the page jump in the pre-production of the wbe page, and when I kept trying to do this, it always ended up in failure. I kept looking for information, modifying the code, and trying, eventually I succeeded. As I continued to learn, I deepened my understanding of computational thinking in the process. I think it is more than just a way of computing, it's about first making a problem abstract, the decomposing it, devising a solution, and finally solving the abstract problem through appropriate computer science. Computational thinking literally means using mathematical and computational approaches to solve problems, but essentially means that humans apply their own solutions to rational computer behavior to explain the problem. It includes, but is not limited to, 'computation', similar to 'sets' and 'subsets' in mathematics. It's inextricably linked to mathematical thinking, computational thinking, etc., and even to engineering thinking. As I mentioned on the first page, computational thinking allows me to be more efficient. Then it plays a subtle role noyt only in computing but in all aspects. For example, 'computational + mathematics' leads to 'artifical intelligence', 'computing + engineering' leads to 'automation', 'computing + life(APP)' leads to 'Google Map'. This shows that we're all using computational thinking. It's important to create models that make sense and simplify the steps because this is what humans have. When we write code, we use our knowledge of mathematics to build a good model, our knowledge of programming to write a language that the computer can recognize, and finally the computer output.
Combining what I have found out, when computer thinking and mathematics are combined to design a new algorithm and apply the algorithm to artificial intelligence, it may solve the concerns we have been having about artificial intelligence in terms of whether or not it has human thinking. Continuing to build on what we have now, designing a new computer language that will be simpler and easier to learn, but designing more powerful models, in terms of artificial intelligence, we need to enhance predictive analysis, then advance predictions will be faster and the analysis will be more comprehensive. And I have found that the various apps I use in my life are not accurate when it comes to voice recognition, due to the accent of each person leading to inaccurate and inaccurate recognition, with the result that when I want to go to place A, I end up arriving at place B. When I don't understand what someone means using translation software, what it translates to is ambiguous. At the same time, people around me will have their own dissatisfaction. As a developer, if it doesn't make users happy, it won't get enough downloads, and ultimately the developer of this software won't have a satisfactory financial income and at the same time it won't have a need to exist. All in all, we still need to keep exploring.
Reference:
Turing,Sara.; Davis, Martin.; Turing, John. 2012. Alan M.Turing. Centenary ed. Cambridge : Cambridge University Press.
Shieber, Stuart M. 2004. The Turing test : verbal behavior as the hallmark of intelligence. Stuart M. Shieber. Cambridge, Massachusetts : Mit Press.
Boden, Margaret A. C1996. Artificial intelligence. 2nd ed. San Diego : Academic Press.
Ahmed, Mohiuddin.; Islam, Sheikh Rabiul.; Anwar, Adnan, (Computer scientist).; Moustafa, Nour.; Pathan, Al-Sakib Khan. 2022. Explainable Artificial Intelligence for Cyber Security : Next Generation Artificial Intelligence. 1st edition. Cham : Springer International Publishing AG.
CT-BBC introductory of CT(BBC)
CT-wikipedia introductory of CT(wiki)