Grade 10 Computer Science Worksheets

Learning Objectives

• Explain how bias can enter AI systems through unbalanced or incomplete training data
• Evaluate common fairness concerns and describe practical ways to reduce unequal outcomes
• Use fairness vocabulary (e.g., bias, data, testing, evaluation) to justify design choices

Learning Objectives

• Explain how variables store information that a program can use and update while it runs.
• Match common data types (integers, strings, booleans, lists) to suitable kinds of values.
• Predict whether a statement is correct based on data type rules.

Learning Objectives

• Identify common HTML elements and describe what they do in a web page.
• Use semantic HTML elements to organize content logically.
• Recognize correct element hierarchy for typical page sections.

Learning Objectives

• Explain how version control helps teams track changes, compare versions, and restore earlier work
• Describe how collaboration tools support shared editing, feedback, and organized teamwork
• Identify common rules for coordinating edits to avoid overwriting and reduce merge conflicts

Learning Objectives

• Explain how accessibility features help users with different abilities and devices.
• Identify changes that improve readability, navigation, and understanding on a website.
• Evaluate accessibility statements as true or false based on web design principles.

Learning Objectives

• Explain what variables are and how programs use them while running
• Match common data types (integer, string, boolean, list) to appropriate values and operations
• Choose correct statements for type-related logic and comparisons

Learning Objectives

• Identify the roles of fields, records, and primary keys in a relational database table.
• Compare table structures and explain how organized data supports searching, sorting, filtering, and updating.
• Match common database questions to appropriate query actions.

Learning Objectives

• Explain how mean, median, and mode describe the center of a data set
• Use range and spread ideas to compare how variable two data sets are
• Determine which measure (center or spread) is most useful when outliers are present

Learning Objectives

• Apply safe browsing habits by checking URLs, avoiding suspicious downloads, and keeping software updated.
• Explain how strong, unique passwords and safe account settings protect digital accounts and personal information.
• Evaluate risky online scenarios and choose the safest response.

Learning Objectives

• Explain how protocols define rules for communication between network devices.
• Describe how data packets move across a network and how they are reassembled at the destination.
• Identify why network standards and common protocol rules improve reliability and interoperability.

Learning Objectives

• Explain how functions group reusable instructions in a program
• Differentiate parameters from arguments used in function calls
• Describe how return values send results back to a caller+ Show more

Learning Objectives

• Explain how recommendation systems use data and patterns to suggest content.
• Compare common recommendation approaches and describe their strengths and limits.
• Evaluate how recommendations can differ for users and affect choices.

Learning Objectives

• Explain how input devices collect data and how programs process that data.
• Differentiate between input and output in a computer system using examples.
• Evaluate statements about signals, devices, and the flow of information.

Learning Objectives

• Identify how CSS selectors and properties work together to style HTML elements.
• Interpret simple CSS rules and predict how they affect the look of a webpage.
• Choose readable styling choices using font, color, spacing, and borders.

Learning Objectives

• Explain how linear search works and when it is efficient.
• Describe how binary search works and why it requires a sorted list.
• Compare searching algorithms by time efficiency and suitability for different data sets.

Learning Objectives

• Explain how training data and labels help a machine learning model learn patterns
• Describe how the size and variety of a training dataset affect prediction quality
• Evaluate statements about model training, feedback, and generalization

Learning Objectives

• Explain how labeled training data helps a model learn patterns
• Identify how dataset quality and variety affect model predictions
• Describe how training feedback helps reduce prediction error+ Show more

Learning Objectives

• Explain how neural networks use layers to transform inputs into outputs.
• Describe the role of weights in neural network predictions.
• Recognize how training adjusts weights to reduce errors.+ Show more

Learning Objectives

• Define artificial intelligence and describe what kinds of tasks AI systems can perform.
• Use key vocabulary (pattern, prediction, automation) to explain how AI makes decisions.
• Identify real-world examples of AI and distinguish AI from simple automated rules.

Learning Objectives

• Define artificial intelligence using accurate Computer Science vocabulary
• Identify pattern recognition and prediction as common AI tasks
• Explain how automation supports repeated AI-powered tasks+ Show more

Learning Objectives

• Explain how clear variables and consistent measurement improve data reliability.
• Identify sources of bias and faulty sampling that can weaken conclusions.
• Use evidence to judge whether a data set is complete enough for analysis.

Learning Objectives

• Translate an everyday process into structured pseudocode using sequence, selection, and iteration.
• Use flowchart symbols and arrows to represent the same logic as pseudocode.
• Compare statements and logic to decide whether a pseudocode or flowchart step is correct.

Learning Objectives

• Identify warning signs of phishing and common malware threats
• Match cyber threats with their likely effects on systems
• Apply safer behaviors when handling links, downloads, and attachments+ Show more

Learning Objectives

• Explain how bubble sort, selection sort, and insertion sort work at the level of passes and swaps
• Trace sorting steps to predict the final ordered list
• Compare algorithm behavior by describing how many times elements may move or swap+ Show more

Learning Objectives

• Identify common cyber threats such as phishing, spyware, viruses, and ransomware by their warning signs and effects.
• Match malware and threat types to likely impacts on computers, accounts, or data.
• Apply safe response strategies when encountering suspicious links, downloads, or messages.

Learning Objectives

• Describe how to test a web project for working links, correct text display, and loaded images across devices and browsers
• Explain the steps for preparing and publishing a finished web project for an audience
• Identify common reasons a site is not launch-ready and propose practical fixes

Learning Objectives

• Explain how IP addresses identify devices on a network.
• Describe how DNS translates domain names into IP addresses.
• Trace how a browser uses DNS and IP addressing to reach a website.

Learning Objectives

• Explain how functions group reusable instructions into named blocks.
• Describe how parameters allow functions to work with different inputs.
• Identify when functions return values to provide information to the rest of a program.

Learning Objectives

• Explain how encryption protects information by making it unreadable without the correct key
• Describe how authentication verifies that a user or device is allowed to access data or services
• Distinguish between encryption and authentication in common security scenarios

Learning Objectives

• Identify the base case and the recursive step in a recursive algorithm
• Trace repeated steps in recursion to predict outputs and termination
• Recognize patterns where recursion is appropriate compared to iteration

Learning Objectives

• Explain how generative AI produces outputs by learning patterns from data.
• Apply responsible use practices, including accuracy checks, privacy protection, and proper source citation.
• Evaluate when human judgment is necessary to reduce harm from errors or bias.

Learning Objectives

• Match different data visualization types to specific questions and data types.
• Interpret trends and relationships shown in common graphs and charts.
• Identify ways visuals can mislead viewers through scales, missing context, or inappropriate chart choice.

Learning Objectives

• Explain why loops reduce duplicate code by repeating a block of instructions.
• Distinguish count-controlled loops from condition-based loops and choose when each is appropriate.
• Predict or correct loop behavior, including off-by-one errors, in simple programs.

Learning Objectives

• Explain how user experience (UX) affects how easily people use a digital product
• Identify interface design choices that reduce confusion and improve usability
• Evaluate design decisions using principles like clarity, consistency, and feedback

Learning Objectives

• Explain how privacy, consent, and data security connect to responsible data practices.
• Identify ethical and unethical uses of personal data in real-world scenarios.
• Describe how anonymization and access controls can reduce harm from data misuse.

Learning Objectives

• Explain how if, else, and nested if statements select different actions based on conditions.
• Use comparison operators (>, <, ==, !=) to form correct logical tests.
• Trace and predict program behavior for branching logic.

Learning Objectives

• Explain how loops reduce repeated program instructions
• Differentiate count-controlled and condition-based loops
• Predict loop output from counters and stopping rules+ Show more

Learning Objectives

• Explain how data moves across the internet using networks, servers, and routers.
• Identify key roles of clients and servers in requesting and receiving information.
• Describe the path of a web request from device to remote server and back.

Learning Objectives

• Explain how biased training data can create unequal outcomes
• Identify fairness problems caused by incomplete or unrepresentative data
• Compare model performance across different groups+ Show more

Learning Objectives

• Explain how protocols standardize communication between networked devices
• Describe the structure and purpose of data packets
• Trace packets as they travel through network routes+ Show more

Learning Objectives

• Identify fields, records, and keys in a database table
• Explain how unique keys identify individual database records
• Compare filtering and sorting operations in database queries+ Show more

Learning Objectives

• Explain how spreadsheets organize data in rows, columns, and cells
• Construct formulas using cell references and arithmetic operators
• Calculate totals and averages using spreadsheet formulas and functions+ Show more

Learning Objectives

• Identify the best visualization type for a given data question
• Interpret trends, patterns, and relationships shown in graphs and charts
• Explain how misleading scales can distort visual comparisons+ Show more

Learning Objectives

• Identify independent, dependent, and controlled variables in data plans
• Evaluate sample quality and measurement consistency in collected data
• Apply strategies that reduce bias in surveys and experiments+ Show more

Learning Objectives

• Explain how variables store and update program data
• Identify integers, strings, booleans, and lists
• Match data types to appropriate programming tasks+ Show more

Learning Objectives

• Identify safe browsing behaviors for websites, links, and downloads
• Explain how strong passwords reduce online account security risks
• Describe how multi-factor authentication improves account protection+ Show more

Learning Objectives

• Explain algorithm efficiency in terms of time and space
• Interpret Big-O notation using dominant growth terms
• Compare O(n) and O(n²) algorithm growth+ Show more

Learning Objectives

• Explain how clarity and ease of use affect user experience
• Identify interface elements that improve digital usability
• Evaluate design choices for a specific target audience+ Show more