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In other words, the old approach emphasized rote memorization. Regardless of whether students understood the concepts, they were expected to memorize them. Many experienced learners simply memorized a lot of knowledge, only to suddenly understand it when they encountered a specific concept later. This "memorizing first and understanding later" model was, frankly, for rapidly cultivating talent after a crisis. It relied on good memory and high learning efficiency, essentially selecting highly intelligent individuals. The problem is that memory is not the same as comprehension. Memorizing doesn't equate to understanding.
This leads to a strange phenomenon: highly intelligent people memorize information but don't understand it. The result is that they constantly show off their knowledge, displaying their cleverness, but struggle to truly create or invent. In fact, current AI is almost a highly intelligent agent. AI can make inferences based on prompts, but that's all it does; whether it's correct or meets the requirements needs to be verified by another mechanism.
Therefore, AI's strength lies in its ability to impart knowledge and deduce desired results based on your input. However, current AI cannot perceive subtle changes in your speech or distinguish whether your meaning is comprehensible to it. In other words, it can't read between the lines; it can't understand whether you understand or not, or whether your understanding aligns with itss. The result is that you allow highly intelligent AI to constantly show off its cleverness, piling knowledge upon you, instantly providing you with a library. This leads to the real problem: if you don't understand, you can't use it. At best, you can only mimic the AI's actions. If you don't want to mimic it, you still need to understand it.
Because you can only use something after you understand it, from another perspective, understanding is what you need to remember, thus building your memory. My years of teaching experience have taught me that the key to most programming learners' sudden realization is understanding the concept of a product. In other words, previously, people first learned what a program is, gradually expanding from programs to software, and then learning product development from a software perspective. Only then did the software specifications and the overall software architecture emerge, and only then did they understand that programs are just components. So, ultimately, software development involves having basic logical concepts, writing the programs that make up the components, and then assembling those components into a product.
Therefore, this app's design philosophy takes the opposite approach, starting from a product perspective, and is divided into three parts:
Basics, Software Development, and GUI. The "Basics" section focuses on guiding learners to write small C++ programs to familiarize themselves with C++ syntax. The goal is not to master the C++ programming language, but rather to prepare for the "Software Development" section. The "Software Development" section starts with software specifications, focusing on guiding learners to further develop the Encrypt category, capable of ciphering English sentences. The Encrypt category serves as the computational core of the "GUI" section, guiding learners to create a "ciphering utility" using Dear ImGui.
In other words, the "ciphering utility" is a product developed by this app based on teaching needs. This is a macro-level approach, first understanding the software architecture, then working backward to identify areas needing reinforcement. After all, modern computers no longer require a compiler to function. The goal is to help learners understand software development first. Once that's understood, other methods, such as AI, can be used to enhance grammatical details.
Currently, AI provides a set of responses to a single prompt. While agent scheduling can be used, the prompts are similar to past commands; in other words, it hasn't moved beyond automated programming. The "GUI" section introduces using scripting to simplify the compilation process.
Have you noticed that while current AI automates tasks using natural language, maintaining these automated agents still requires programmers, particularly experienced ones? Therefore, becoming a programmer requires continuously improving your skills. If you first understand what software development entails, then delving into the syntax details of programming languages and the underlying logic of computers, what could be tedious and require rote memorization suddenly becomes interesting.
Interest makes learning meaningful, doesn't it? Besides, the sense of accomplishment comes from manually writing code that runs. Copying code from the internet or even asking AI for code doesn't generate much satisfaction and often leads to frustrating debugging. In this sense, both the internet and AI are like swords. You wield these swords to slay demons, but if they control your mind, they cannot extend your power, making them useless.
Finally, thank you for purchasing this app. However, since everyone's background is different, I hope the teaching methods designed in this app will be helpful in learning programming. Understanding is not easy, but you always need to understand to know how to do it, and only by doing it will it truly help.
Zhang Kaiqing 2026/04/28
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