C++, Algorithms, Data Structures?
Understanding What Competitive Programming Teaches
And Why It Is So Important
Overview of the Competition System
-CSP-J/S NOIP-
-NOI APIO IOI-
The CSP-J/S certification is suitable for middle school students, while the S group is aimed at high school students. With the new regulations allowing students over 12 years old to participate starting in 2025, some regions have also introduced the CSP-X group for elementary school students. Unlike the CCF-CSP professional certification aimed at university students, the competitive programming contests at the middle school level focus more on cultivating algorithmic thinking. At the university level, there are ongoing competitions such as ICPC and CCSP.
Knowledge System Construction
-System Construction-
During the CCF NOI teacher training in September 2025, Dr. Zhao Qiyang explained the logic behind the formation of the competitive programming knowledge system. Considering the learning characteristics of middle school students, the competition content focuses on cognitive abilities that can be mastered in a short time and assessed within hours, including algorithmic thinking, mathematical thinking, and type thinking. These topics are selected from computer science knowledge that is easy to combine and effectively tests cognitive flexibility.
According to the “NOI Syllabus (2025 Revised Edition)”, the knowledge system is divided into five main modules, with knowledge points categorized into three levels: beginner, intermediate, and NOI level based on difficulty.
Four Stages of Learning Path
-Four Stages-
Stage One: Mastering Tools Learn the core of C++ language (syntax, functions, arrays, etc.) and computer fundamentals. The key in this stage is to use tools to solve practical problems and develop programming intuition. Recommended reference materials include “A Comprehensive Guide to Competitive Programming” and the “In-Depth Series on Programming Competitions”.
Stage Two: Accumulating Methods Master basic data structures (stacks, queues, trees) and classic algorithms (sorting, searching, dynamic programming). These form the “toolbox” for problem-solving, such as dynamic programming which cultivates problem decomposition skills, and greedy algorithms which train optimal decision-making thinking. New coaches are advised to adopt a thematic training model.
Stage Three: Cultivating Thinking Focus on developing mathematical modeling, problem decomposition, and algorithm optimization skills. When faced with unfamiliar problems, students should be able to analyze patterns, establish models, and choose appropriate methods. In teaching, students can first describe their thoughts in natural language before converting them into code; parents can encourage children to explain algorithm principles using real-life examples.
Stage Four: Practical Training Improve debugging skills, time management, and teamwork through simulated training. Competitive programming not only tests programming abilities but also assesses psychological quality and execution efficiency. It is recommended to participate in real problem training and monthly competitions on platforms like Luogu, and parents should focus on their children’s persistence and growth in the problem-solving process rather than just the scores.
Learning Philosophy
-programming-
Compared to robot programming, competitive programming focuses more on training algorithmic thinking, emphasizing the ability to transform complex problems into executable algorithms. It is important to be cautious not to reduce competitive programming learning to mere mechanical problem-solving. As competitions evolve, cognitive flexibility will become increasingly valued. It is hoped that everyone can transcend the utilitarian perspective of “a stepping stone for further education” and truly enjoy the joy of cognitive training.
