Computer Science Worksheets

Learning Objectives

• Define event, trigger, response, and interaction in the context of event-driven programs.
• Identify which user action or timer event should trigger a specific program response.
• Match event-driven terms to their correct definitions.+ Show more

Learning Objectives

• Explain how variables, events, and logic interact in programs
• Identify how user interfaces support application functionality
• Predict program outcomes using conditionals and loops

Learning Objectives

• Define key cybersecurity terms and explain how they relate to online safety.
• Identify common threats and vulnerabilities in everyday digital habits.
• Apply prevention strategies to protect devices and online accounts.

Learning Objectives

• Identify a pattern in a sequence or set of examples and describe the relationship it shows
• Use pattern recognition to make a reasonable prediction for a new case
• Explain how generalizations can help solve similar problems more efficiently+ Show more

Learning Objectives

• Define mean, median, range, and distribution using data from examples
• Calculate the mean, median, and range for small data sets
• Use numerical summaries to compare two groups described by statistics+ Show more

Learning Objectives

• Define ethics, accountability, transparency, and responsibility in the context of artificial intelligence.
• Identify ethical risks in AI scenarios, such as privacy problems and unfair or unclear decisions.
• Explain how designers can reduce harm by improving transparency and accountability.+ Show more

Learning Objectives

• Define evidence, analysis, conclusion, and decision in the context of using data.
• Identify which data supports a conclusion and explain why it does.
• Use logical reasoning to choose the best recommendation based on given data.+ Show more

Learning Objectives

• Define digital footprint, trace, reputation, and online presence using correct vocabulary.
• Explain how repeated online actions can affect online reputation over time.
• Identify examples of online behaviors that create positive or negative traces.+ Show more

Learning Objectives

• Define event, trigger, interaction, and response in programs
• Identify how events cause code to run in software
• Match user actions to event types and program responses+ Show more

Learning Objectives

• Explain how privacy settings control who can view personal information and activity.
• Identify key data protection ideas, including data collection and sharing.
• Use permissions settings to decide what information an app can access.+ Show more

Learning Objectives

• Define visualization terms and identify the role of charts and graphs in communicating data
• Compare common graph types and match each type to an appropriate data situation
• Interpret a data display by recognizing trends and patterns+ Show more

Learning Objectives

• Define cyberbullying and harassment and identify common examples of each online.
• Explain the role of a bystander in responding safely to harmful online behavior.
• Select respectful actions that protect someone who is being targeted, including blocking, reporting, and saving evidence.

Learning Objectives

• Define key terms in machine learning, including training data, model, and prediction.
• Explain how a model learns patterns from training data to make predictions.
• Identify which statement best describes the relationship between training and prediction quality.+ Show more

Learning Objectives

• Define pseudocode and explain its role in algorithm design
• Identify sequence, selection, and iteration in pseudocode
• Translate problem descriptions into step-by-step logic plans+ Show more

Learning Objectives

• Define decomposition and explain how it helps solve complex problems
• Identify parts of a problem as subproblems and choose strategies for solving each
• Use decomposition steps to plan a sequence of actions toward a solution+ Show more

Learning Objectives

• Define abstraction and explain how it helps simplify a computing problem.
• Identify essential features versus unnecessary details in a system or process.
• Use models and representations to describe how an algorithm works.+ Show more

Learning Objectives

• Define input, output, response, and interaction in the context of computer programs.
• Identify examples of input and output from everyday interactive situations.
• Explain how changing an input affects a program’s output.+ Show more

Learning Objectives

• Define key vocabulary for interactive games, including interactive, game, score, and program
• Explain how variables and loops can update a game over repeated turns
• Use conditionals to decide what happens in a game when an event occurs+ Show more

Learning Objectives

• Define the terms event, trigger, interaction, and response in an event-driven program.
• Identify how user actions can trigger events that change what a program does.
• Match event-related vocabulary to correct definitions.+ Show more

Learning Objectives

• Identify key source-check details (author, purpose, date, and evidence) that affect credibility.
• Use evidence-based criteria to choose reliable information online.
• Compare reliable and misleading information using clear reasoning.+ Show more

Learning Objectives

• Define human intelligence and machine intelligence using age-appropriate vocabulary.
• Compare how people and machines solve problems using judgment versus programmed rules.
• Identify examples of tasks that are better suited to humans or to computers.+ Show more

Learning Objectives

• Identify common data types (integer, string, boolean) from examples
• Match data values to the correct data type
• Explain how choosing the right operation depends on the data type+ Show more

Learning Objectives

• Explain how testing checks whether an algorithm works as intended under different conditions
• Use validation results to revise an algorithm for better reliability and clarity
• Identify vocabulary terms: testing, validation, refinement, and revision+ Show more

Learning Objectives

• Define the terms scam, phishing, suspicious, and fraud and use them correctly.
• Identify common warning signs in messages, pop-ups, and emails.
• Explain safe actions to take when you are unsure a message is real.+ Show more

Learning Objectives

• Define debug, logic, error, and trace and use them correctly in context
• Identify logical errors by comparing expected results to actual results
• Use a tracing approach to find where reasoning goes wrong in a sequence+ Show more

Learning Objectives

• Define debugging and identify common causes of program errors.
• Use a step-by-step tracing strategy to find where a program goes wrong.
• Troubleshoot a short code problem by correcting order, logic, missing parts, or incorrect values.

Learning Objectives

• Describe how data collection methods can affect accuracy and reliability.
• Explain how validation checks help make data complete and trustworthy.
• Identify when a set of results may be unreliable due to measurement or procedure issues.+ Show more

Learning Objectives

• Define the terms condition, branch, logic, and outcome in the context of algorithms.
• Identify how an algorithm chooses different paths based on conditions.
• Use if/else reasoning to predict the outcome for a given scenario.+ Show more

Learning Objectives

• Define the terms trend, pattern, increase, decrease, and prediction.
• Identify whether data shows a trend or a pattern in a table or graph.
• Use data evidence to make a prediction about what may happen next.

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

• 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 helpful everyday uses of AI in learning, transportation, communication, and entertainment.
• Use key vocabulary (helpful, support, assist, AI) to describe how AI helps people.
• Recognize that AI can suggest options, not decide by itself, and evaluate uses responsibly.

Learning Objectives

• Define bias and fairness in the context of AI systems
• Explain how training data can lead to biased AI results
• Identify signs of unfair or inconsistent AI behavior in example situations+ Show more

Learning Objectives

• Explain how programs follow commands in the exact sequence they are written
• Identify how changing the order of code commands can change or break program output
• Use sequencing vocabulary (sequence, order, command, output) to describe code behavior+ Show more

Learning Objectives

• Explain how instruction order can change an outcome in a procedure.
• Identify accurate vs. inaccurate instruction sequences for a simple task.
• Use clear step order to improve the accuracy of instructions.

Learning Objectives

• Define key terms used in digital communication systems, including communication, platform, collaboration, and transmission.
• Describe how digital communication moves information through networks for different purposes.
• Compare common digital tools (email, messaging, video conferencing, and collaborative platforms) based on what they are best used for.+ Show more

Learning Objectives

• Explain the meaning of efficiency, performance, and resource use in algorithms.
• Compare two algorithms for the same task using ideas like time and memory.
• Identify ways to optimize an algorithm without changing its correct output.+ Show more

Learning Objectives

• Define a variable as stored data that can change while a program runs
• Identify the difference between a variable and its value in a programming scenario
• Explain how stored data helps a program track information like scores and names+ Show more

Learning Objectives

• Define responsibility, evaluation, judgment, and limitation in the context of AI tools
• Identify appropriate and inappropriate uses of AI-assisted tools in school tasks
• Evaluate AI output by checking accuracy, bias, and missing limitations+ Show more

Learning Objectives

• Define a function, parameter, module, and reusable in the context of programming
• Explain how modular code can improve readability and maintenance
• Identify how parameters pass information into a function and how results are used+ Show more

Learning Objectives

• Define key network vocabulary such as network, node, connection, and infrastructure.
• Describe the roles of devices and network infrastructure in sending information.
• Explain how local and global communication can use networks.+ 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

• Define key vocabulary related to healthy digital habits: balance, habit, screen time, and wellness.
• Compare technology routines that support focus and well-being with routines that may harm them.
• Use evidence from a short passage to choose healthy screen-time choices.+ Show more

Learning Objectives

• Define cyberbullying, bystander, report, and harassment
• Identify examples of harmful online behavior and safe bystander responses
• Explain how reporting can help stop repeated harassment

Learning Objectives

• Define and use key terms interactive, project, feature, and program in context
• Identify how inputs, outputs, events, loops, and conditionals work together in an interactive program
• Choose the best plan for testing an interactive feature before coding+ Show more

Learning Objectives

• Identify the purpose of flowcharts and decision points in algorithms
• Match flowchart vocabulary (flowchart, decision, branch, symbol) to correct meanings
• Complete and interpret a flowchart-style decision path using correct logic+ Show more

Learning Objectives

• Define algorithm, input, output, and processing and explain how they relate in an AI system
• Identify which step in an AI workflow connects input data to a generated output
• Use examples to describe how algorithm design affects reliability in AI decisions+ Show more

Learning Objectives

• Define input, output, and processing in an interactive computer program.
• Identify how input and output work together to create interaction.
• Use vocabulary to describe an input-output relationship in everyday examples.+ Show more