China 高一 Information Technology
Chapters: 8
1. Comp.1 Ch.1 Data and big data
Data, information, knowledge · Digitisation; binary; encoding; compression · Data science and big data
- Data Representation: How Computers Store Numbers, Text, Images and Sound – Data is raw facts; information is data given meaning; knowledge is information we can use. A computer stores all data as bits (0 or 1). 8 bits make a byte, and 1 kB = 1000 bytes, 1 MB = 1000 kB, 1 GB = 1000 MB, 1 TB = 1000 GB. Numbers are stored in binary, where place values double: 1, 2, 4, 8 and so on. Text uses a character set: in ASCII 'A' is 65; Unicode covers every script. A bitmap image is a grid of pixels; size = width × height × colour depth. Sound is sampled: size = sample rate × bit depth × seconds. Vector images store shapes instead of pixels. Compression makes files smaller: lossless keeps every bit, lossy throws some detail away.
- 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).
- Big Data – Big data is data that is too big, too fast or too mixed to store and process on one ordinary computer with normal tools. We describe it with Volume (how much), Velocity (how fast it arrives) and Variety (how many kinds). To handle it, the work is split across many machines that run at the same time (distributed processing, for example MapReduce). Big data is often stored as simple facts or as a graph of nodes and links, and it is used for weather forecasts, maps, health, shopping and training AI. It also raises questions about privacy and fairness.
2. Comp.1 Ch.2 Algorithms and programs
Problem-solving with computers · Algorithms and their description · Programming basics (types, variables, statements, structures) · Analytic and enumeration algorithms; efficiency; debugging
- 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.
- Python Basics: Modes, Variables, Data Types and Operators – Python runs in interactive mode (one line at a time) or script mode (a saved .py file). Blocks are shown by indentation. Variables are names tied to values; every value has a data type, and some types are mutable. Operators build expressions that Python works out by precedence. input() reads text, int()/float()/str() convert types, and debugging fixes syntax, runtime and logical errors.
3. Comp.1 Ch.3 Data processing
Collection, cleaning, security · Analysis and visualisation · Analysis reports
- 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.
- Data Visualisation: Turning Numbers into Pictures – Data visualisation means showing data as a picture so patterns are easy to see. Use a bar chart to compare categories, a pie chart for parts of a whole, a line chart for change over time, a scatter plot for the relationship between two numbers, and a histogram for how values are spread. A good chart has a title, labelled axes with units, and an honest scale that starts at 0 for bars.
4. Comp.1 Ch.4 Intelligent era
AI origins and development · Using AI tools; calling AI APIs in code · Impact of AI
- 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.
- Using AI Tools and Calling an AI API from Python Code – An AI tool is a ready-made app (chat, image, voice, translation) that you use by typing or clicking. An AI API lets your own program ask the same kind of AI service for help. The program sends a request (address, secret key and a question in JSON) and receives a response (status code and an answer in JSON). With Python this takes about six lines using the requests library. Good use means clear prompts, checking answers, protecting your key and respecting cost and limits.
- 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. Comp.2 Ch.1 IT and society
Development and trends of IT · Information society
- Development and Trends of Information Technology – Information technology (IT) is the use of machines to sense, send, process, store and show information. Over about 80 years computers moved from room-size machines with vacuum tubes to transistors, chips, personal computers, the internet, smartphones and now AI chips: smaller, cheaper and stronger each time. Four key technologies (sensing, communication, computing and control) work together. Current trends are AI, cloud, IoT, big data, 5G and early quantum computing, and each brings duties such as privacy, saving energy and learning new skills.
- 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.
6. Comp.2 Ch.2 Information systems
Components and functions; development process; strengths and limits
- Information Systems – An information system (IS) is a set of people, hardware, software, data, networks and procedures that work together to collect, store, process and share information. It turns raw data into useful information through a chain: capture, encode, send, store, process and present. Systems are built in a cycle (plan, analyse, design, build, test, run and improve). They make work faster and let many people share knowledge, but they cost money, can fail, can be hacked and can make an organisation rigid.
7. Comp.2 Ch.3 Infrastructure
Computers and mobile terminals · Networks: LAN/WAN, topology, IP, domain names, wireless LAN · Software; simple networked apps · Sensing and control (IoT)
- Computers and Computing: Evolution, Parts and I/O Devices – A computer is an electronic machine that takes input, processes it under the control of a program, stores data and gives output. Computing devices grew from the abacus to smartphones. Every computer has an input unit, a CPU, memory and an output unit, joined by buses and ports.
- Computer Networks: Types, Devices and Topologies – A computer network is a group of devices connected to share data and resources. By area, networks are PAN, LAN, MAN and WAN. Devices do different jobs: a modem converts digital and analog signals, a repeater boosts a weak signal, a hub sends data to all ports, a switch sends it only to the right device, a router joins networks and chooses a path, and a gateway joins networks that use different protocols. Topology is the layout of connections: star, bus, tree and mesh, each with its own strengths and weaknesses.
- Software and Simple Networked Apps: Chat and Email – Software is the set of instructions that makes hardware useful. A networked app such as chat or email has a client (on your device) and a server (always on, far away). They pass addressed messages; the server forwards them at once (chat) or keeps them in a mailbox until you come online (email).
- Sensors: How Machines Sense the World – A sensor turns a physical quantity (light, temperature, distance, moisture, sound, pressure) into an electrical signal. Analogue sensors give a smooth voltage; an ADC turns it into a number the computer can use. A controller compares the number with a threshold and switches an actuator, often through a relay. Readings taken at regular times are data logging. Good sensors have the right range, sensitivity, accuracy and response time.
8. Comp.2 Ch.4 Security and ethics
Security risks and protection · Laws, ethics, responsible use
- Cybersecurity: Threats and How We Stop Them – Cybersecurity protects computers, networks and data. It aims for confidentiality, integrity and availability (the CIA triad). Common threats are malware, phishing and social engineering, brute-force password attacks and denial of service. Defences include strong authentication, encryption, firewalls, anti-malware software, updates, access control and backups.
- 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.