South 중학교 2학년 Informatics
Chapters: 5
1. Computing systems
Components of a computing system · Physical computing · Building physical computing projects
- Basic Computer Organisation – A computer system has hardware (parts you can touch) and software (instructions). Input devices bring data in, the CPU (ALU + Control Unit + registers) processes it, and output devices give results. Memory forms a ladder: registers and cache are tiny and fastest, primary memory (RAM, ROM) holds running programs, and secondary storage (HDD, SSD, pen drive) keeps data permanently. Memory is measured in bits and bytes: 8 bits = 1 byte, and each bigger unit (KB, MB, GB, TB, PB) is 1024 times the one before.
- Physical Computing: Making Code Sense and Move – Physical computing joins code to the real world. Sensors measure something (light, temperature, distance, button presses) and turn it into a number. A microcontroller runs a program that decides what to do with that number. Actuators (LEDs, buzzers, motors, screens) act on the world. This input–process–output cycle runs again and again in a loop. Using thresholds, conditions and feedback, we build night lights, smart plant waterers, wearables and interactive art.
2. Data
Digitising real-world data · Collecting and classifying data · Structuring data · Relationships in data · Data in other subjects
- Number Systems and Encoding – A number system is a way to write numbers using a set of digits and a base. Decimal (base 10) uses 0–9, binary (base 2) uses 0 and 1, octal (base 8) uses 0–7, and hexadecimal (base 16) uses 0–9 and A–F. To go from decimal to any base, divide repeatedly by the base and read remainders bottom to top; for fractions, multiply by the base and read the integer parts top to bottom. To go to decimal, multiply each digit by its place value and add. Binary ↔ octal uses groups of 3 bits, binary ↔ hex groups of 4. Text is stored with encoding schemes: ASCII (7-bit, 128 characters), ISCII (8-bit, Indian scripts) and Unicode (every script), stored as UTF-8 (1–4 bytes) or UTF-32 (4 bytes).
- Data Handling: Collect, Organise and Show Data – Data is a set of facts, such as answers, counts or measurements. Data can be qualitative (words) or quantitative (numbers); numbers are discrete (counted) or continuous (measured). We collect data by surveys, observation, experiments or from existing sources, then organise it with tally marks into a frequency table. We show it with the right graph: bar graphs to compare groups, pie charts to show parts of a whole, line graphs for change over time and scatter graphs for links between two variables. Computers store data as structured tables or unstructured text, images and sound.
- Data Analysis – Data analysis means turning raw data into answers. It follows a cycle: ask a question, collect data, clean it (remove errors, repeats and blanks), organise and transform it, analyse it with summaries such as mean, median, range and patterns, show it with a good chart, and draw a careful conclusion. Watch for outliers, small samples and bias, and remember that a correlation between two things does not prove that one causes the other. Data must also be stored safely and used with permission.
3. Algorithms and programming
Defining and structuring a problem · Abstraction · What algorithms are · Designing algorithms · Lists and sequential data · Logic and nested control · Functions · Programming to solve real problems · Collaborative software projects
- Introduction to Problem Solving – Problem solving on a computer has stages: analyse the problem (inputs, outputs, rules), develop an algorithm (a finite, clear, ordered set of steps), code it in a programming language, test it with different inputs, and debug (find and remove errors). An algorithm can be shown as a flowchart (oval = start/stop, parallelogram = input/output, rectangle = process, diamond = decision, arrows = flow) or as pseudocode (structured plain English). Decomposition breaks a big problem into smaller sub-problems that are solved separately and then joined.
- Data Structures: Arrays, Lists, Stacks, Queues and Trees – A data structure is a way of organising data in memory so a program can use it well. Arrays keep items in numbered boxes for instant access by index. Linked lists chain nodes with pointers, so inserting is easy. Stacks work last-in-first-out, queues first-in-first-out. Dictionaries find values by key, and trees store data in levels so searching is fast. Choosing the right structure makes programs faster and simpler.
- Programming Basics: Sequence, Selection, Loops and Functions – A program is a set of exact instructions a computer follows. Every program is built from three structures: sequence (steps in order), selection (if/else choices) and iteration (loops). Variables store values. Functions group code into reusable, named blocks, which makes programs modular and easier to test, debug and maintain.
4. Artificial intelligence
What AI is · Data for machine learning · Building a simple AI system · Solving problems with AI · Ethics of AI data
- Artificial Intelligence: How Machines Learn to Think – Artificial intelligence (AI) is the skill of a computer system to do tasks that normally need human thinking: seeing, understanding speech, deciding and learning. An AI system is an agent that senses, thinks and acts. Old AI followed rules written by people. Modern AI mostly uses machine learning: it finds its own rule from many labelled examples (data). Neural networks are layers of simple units whose link strengths (weights) change during training. AI is used in maps, translation, health, farming and games. It can be wrong or unfair when its data is one-sided (bias), so people must check it, protect privacy and stay responsible.
- Machine Learning – Machine learning (ML) is a way for computers to learn a rule from examples instead of being told the rule. We give data made of features (inputs) and, in supervised learning, labels (answers). The machine fits a model: regression predicts a number, a decision tree asks yes/no questions to pick a class, and k-means clustering groups unlabelled data. We train on most of the data, test on data it never saw, and measure accuracy or error. A model that only memorises (overfits) fails on new data.
- AI Ethics: Using Artificial Intelligence Fairly and Safely – AI systems learn patterns from data and then make decisions. AI ethics asks whether those decisions are fair, safe and respectful. The main issues are bias (unfair data gives unfair results), privacy (personal data needs consent and protection), transparency (people should know why an AI decided something), accountability (a human stays responsible), safety and misuse (deepfakes, false information), and social impact (jobs, the digital divide, the environment). Responsible AI means checking all of these before and after an AI is used.
5. Digital culture
Digital society and jobs · Safe digital living · Living together online
- Digital Society: How Information Technology Changes Our Lives – A digital society (also called an information society) is a society where making, sharing and using information with computers and networks is a main part of life, work and government. Information moves fast, reaches everywhere and can be copied at almost no cost. Software has changed shopping, banking, health, school and friendship. New jobs appear (app developer, data analyst) while some old jobs shrink. Every online action leaves data, so privacy matters. Not everyone is connected (the digital divide), and too much screen time or gaming can harm health. A good digital citizen uses the benefits and manages the risks.
- Digital Footprints and Netiquette – A digital footprint is the trail of data we leave online. Active footprints are shared on purpose (posts, comments, forms); passive footprints are collected without us noticing (cookies, browsing history, location, IP address). Footprints are hard to erase and can be seen by others later. We live in a digital society where learning, banking, shopping and government services are online; a responsible user of it is a digital citizen (netizen). Net etiquette means being ethical (respect copyright, share reliable information), respectful (privacy, diversity, no bullying) and responsible (avoid oversharing, don't feed trolls). Communication etiquette asks us to be precise, polite and credible; social media etiquette asks us to choose passwords and privacy settings wisely, think before uploading, and verify before sharing.