Computer Science Worksheets

Learning Objectives

• Define bug, error, debug, and troubleshoot in the context of computer programs
• Identify whether an observed problem is caused by a logical error or a sequencing error
• Use a simple testing and observation process to debug a program+ Show more

Learning Objectives

• Identify what a graph shows about quantities and categories
• Read bar graphs, line graphs, and pictographs to find patterns and trends
• Interpret information by describing what changes in a graph over time or between categories

Learning Objectives

• Identify the parts of a decision tree: conditions, branches, and outcomes
• Follow a decision tree to predict an outcome from given conditions
• Construct simple decision pathways by choosing branches based on conditions+ Show more

Learning Objectives

• Define and use the words test, result, expected outcome, and evaluation in the context of program testing.
• Compare intended behavior and actual behavior to decide whether a program passes a test.
• Describe how observation during testing helps find strengths and areas for improvement.

Learning Objectives

• Identify warning signs of online scams such as suspicious messages and urgent requests
• Explain how phishing and fraud attempts try to trick people into sharing information
• Use critical thinking steps to decide whether an online offer or message is trustworthy+ Show more

Learning Objectives

• Define the terms input, output, response, and interaction.
• Identify inputs and outputs from short computer scenarios.
• Explain how an input leads to an output through a program’s response.+ Show more

Learning Objectives

• Explain how a condition guides a decision in an algorithm
• Identify the outcome that matches a true or false condition
• Trace a branching path in a simple decision scenario+ Show more

Learning Objectives

• Define digital footprint, online presence, and reputation and explain how they connect.
• Identify examples of responsible and irresponsible online behaviors.
• Explain how online actions can have long-term effects on how others view a person.

Learning Objectives

• Define key conditional vocabulary such as condition, decision, and branch.
• Identify which action a simple program would take based on an if/else condition.
• Use conditional logic to predict outputs for different inputs.

Learning Objectives

• Identify patterns in solutions and explain how they help solve new problems.
• Use pattern recognition to describe a strategy that can be repeated across tasks.
• Match vocabulary words such as pattern, strategy, repeat, and recognition to their meanings.+ Show more

Learning Objectives

• Explain how machine learning uses training data to find patterns
• Identify what a model is and how it makes predictions
• Describe how machine learning improves when it learns from new examples+ Show more

Learning Objectives

• Explain what an algorithm, sequence, instruction, and process mean
• Order steps in a correct sequence to complete a task
• Use clear, precise instructions to design an everyday or digital procedure+ Show more

Learning Objectives

• Define artificial intelligence and describe what it can do.
• Identify key AI vocabulary: prediction, pattern, and decision.
• Match AI terms to correct examples or definitions.+ Show more

Learning Objectives

• Define evidence, analysis, and conclusion and explain how they connect.
• Use information from graphs, tables, and surveys to choose conclusions supported by evidence.
• Identify whether a claim is supported by reliable data.

Learning Objectives

• Explain how balancing screen time with physical activity, rest, and social interaction supports well-being.
• Identify healthy digital habits and describe how different routines can affect daily life.
• Use vocabulary such as balance, well-being, screen time, and healthy habits in context.+ Show more

Learning Objectives

• Explain how privacy helps protect personal information when using AI tools.
• Identify ways to judge whether an AI answer is trustworthy and complete.
• Describe limits of technology and when human judgment is needed.+ Show more

Learning Objectives

• Use data sets to compare similarities and differences between groups of information.
• Identify a relationship between two variables described in a simple data set.
• Explain how careful data analysis supports an evidence-based conclusion.

Learning Objectives

• Identify what a table is used for when organizing information by categories.
• Choose the best chart type to help compare data shown in collected results.
• Explain how charts and tables make it easier to analyze and communicate information.+ Show more

Learning Objectives

• Define the terms flowchart, process, decision, and symbol.
• Identify what different flowchart symbols and arrows mean in a simple process.
• Create a simple flowchart from a short set of steps with one decision.+ Show more

Learning Objectives

• Define the terms bug, error, debug, and correction in the context of algorithms.
• Identify common causes of algorithm errors, such as missing steps, repeated steps, or steps in the wrong order.
• Use debugging steps to improve an algorithm by making corrections based on evidence.

Learning Objectives

• Explain how inheritance supports code reuse by defining parent and child classes.
• Use method overriding to change child class behavior while keeping the same method interface.
• Describe polymorphism and predict how different objects can respond to the same method call.+ Show more

Learning Objectives

• Explain how classes define attributes and behaviors, and how objects are created from those blueprints.
• Identify the roles of constructors, methods, and encapsulation in managing program state.
• Apply class and object concepts to model a real-world system in code.

Learning Objectives

• Differentiate trees and graphs using key properties such as hierarchy, cycles, and connectivity
• Describe how traversal methods (like BFS/DFS) explore structures and find paths
• Apply graph and tree ideas to real-world relationship systems, such as maps and file structures

Learning Objectives

• Explain how testing helps validate an algorithm and find errors in edge cases and unexpected inputs.
• Use test results to refine steps and improve correctness, clarity, and reliability.
• Validate that changes do not break earlier behavior by retesting with multiple scenarios.

Learning Objectives

• Identify common warning signs of scams and phishing messages.
• Explain safe choices when you see suspicious emails, texts, or pop-ups.
• Use key vocabulary (scam, phishing, suspicious, fraud) accurately in explanations.

Learning Objectives

• Explain how decomposition breaks a complex problem into smaller subproblems with clear goals.
• Apply a decomposition strategy to plan steps for a solution.
• Evaluate whether proposed steps match the subproblems needed for a solution.

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 encryption helps protect digital information from unauthorized reading.
• Use key vocabulary (encryption, decryption, key, secure communication) accurately in context.
• Identify correct statements about secure communication and the role of keys.

Learning Objectives

• Explain the difference between a trend and a correlation when analyzing data.
• Interpret a graph by describing patterns over time and relationships between variables.
• Avoid overgeneralizing by stating what a correlation does and does not prove.

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 events trigger actions in an event-driven program.
• Use key vocabulary (event, trigger, response, interaction) to describe program behavior.
• Identify event types such as clicks, key presses, touches, and timed actions.

Learning Objectives

• Explain how generative AI and large language models learn patterns from data to produce new content
• Identify common limitations of generative AI, including errors, bias, and unclear reliability
• Apply strategies for deciding when to use generative tools and when to require human review

Learning Objectives

• Define key statistics vocabulary: mean, median, range, and distribution
• Use averages and range to summarize data and compare groups
• Evaluate statements about statistics using true/false reasoning+ Show more

Learning Objectives

• Explain how the internet connects devices using networks and data transfer.
• Describe the roles of networks and servers in sending and receiving information.
• Use key vocabulary words correctly: internet, network, server, connect.

Learning Objectives

• Explain how labels communicate meaning in user interfaces and data representations.
• Identify common features of labeled interfaces, including readability, consistency, and clarity.
• Evaluate statements about labels and their role in usability and data understanding.

Learning Objectives

• Explain how decomposition breaks a complex problem into smaller subproblems with clear goals.
• Identify strategies for planning, organizing, and troubleshooting using decomposition.
• Use key vocabulary (decomposition, subproblem, strategy, solution) accurately in context.

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

• Define a function, call, and reusable code in simple computer science language
• Explain why reusable code blocks make programs easier to read and maintain
• Choose the best option that describes how functions work in a program

Learning Objectives

• Identify harmful online behaviors that qualify as cyberbullying or harassment.
• Choose safe, responsible responses as a bystander or target.
• Use key vocabulary (cyberbullying, harassment, report, bystander) to explain next steps.

Learning Objectives

• Explain why privacy matters when using AI-powered apps and websites.
• Identify common types of data collection and describe how data can be used.
• Use the terms privacy, data, collection, and consent in accurate, responsible technology choices.

Learning Objectives

• Use keywords and quotation marks to form more precise search queries.
• Apply common search operators and filters to narrow results and improve relevance.
• Explain how query structure affects search results.

Learning Objectives

• Explain why responsible AI use requires evaluation of outputs and human judgment.
• Identify common limitations of AI tools and apply safe checking habits.
• Use lesson vocabulary (responsibility, evaluation, judgment, limitation) in context.

Learning Objectives

• Explain how algorithms use input, processing, and output to make decisions.
• Describe how relationships in data help an AI system generate results.
• Evaluate how algorithm design choices can affect accuracy and reliability.

Learning Objectives

• Explain how privacy settings control who can view personal information and activity.
• Describe data protection practices that reduce the risk of unwanted sharing.
• Use permissions and account settings to manage visibility and data access.

Learning Objectives

• Explain how accessible web design supports users with different abilities and devices.
• Identify common accessibility features and describe why they matter for usability.
• Apply web publishing checks such as link verification and layout testing before release.

Learning Objectives

• Explain what malware is and identify common types such as viruses, spyware, and ransomware.
• Describe warning signs in files, links, and attachments that may indicate malware.
• Use safe download habits to reduce the risk of infection and data loss.+ Show more

Learning Objectives

• Explain how machine learning uses training data to learn patterns.
• Use key vocabulary words including machine learning, training data, model, and pattern.
• Describe how examples can change a model’s predictions.

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.