Grade 5 Computer Science Worksheets

Learning Objectives

• Explain what makes a password strong by describing the mix of characters and its guessability.
• Identify safe account security habits, including using different passwords for different accounts.
• Use password and authentication vocabulary to describe how logins protect accounts.

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

• Explain how loops repeat code steps using the ideas of repeat, iteration, and a loop body.
• Identify when repetition makes a program shorter and more efficient by reducing duplicate code.
• Use loop logic to predict what a repeated action or pattern would produce.

Learning Objectives

• Define machine learning and explain how training data helps a model learn patterns.
• Identify common parts of a simple machine learning process: model, training data, and pattern.
• Use vocabulary (machine learning, training data, model, pattern) to answer questions about training and prediction.+ Show more

Learning Objectives

• Compare two algorithms by describing how many steps they use and how they affect time or effort.
• Define and use efficient, compare, and optimize to explain why one strategy works better than another.
• Use criteria to choose the most efficient strategy for a given problem.

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

• Explain how patterns can help predict outcomes in a problem-solving situation
• Identify repeated structures and rules in example tasks and algorithms
• Use pattern clues to choose an efficient next step in a solution+ Show more

Learning Objectives

• Explain how flowcharts use symbols and arrows to show a process.
• Identify how decision nodes create branches that change an outcome.
• Read and interpret simple decision paths in an algorithm.+ Show more

Learning Objectives

• Explain what decomposition means in problem-solving and in computer science.
• Identify subproblems and describe how a strategy helps plan steps.
• Describe how breaking a complex task into smaller steps supports logical thinking and better solutions.

Learning Objectives

• Define an algorithm as a clear sequence of instructions.
• Identify the purpose of each instruction step in an algorithm.
• Write and improve simple algorithms for everyday tasks.+ Show more

Learning Objectives

• Define the terms claim, evidence, conclusion, and support and explain how they connect.
• Interpret information from a graph or table to decide whether a claim is supported.
• Justify answers by citing specific evidence from data displays.+ 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 privacy, safety, data, and settings and explain how they relate to using AI tools
• Identify safe choices for interacting with AI-powered apps and devices
• Apply privacy and safety rules to a real-life AI scenario+ Show more

Learning Objectives

• Identify key information in bar graphs, line graphs, and pictographs.
• Use graph vocabulary to describe and compare data (graph, chart, category, compare).
• Interpret scales, axes, and labels to answer questions about data sets.+ 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

• Explain why reliable data collection uses careful observation, accurate counting, and consistent methods
• Identify suitable tools and steps for collecting survey and measurement data
• Distinguish between reliable data and unreliable data+ Show more

Learning Objectives

• Explain how tone, word choice, and audience affect understanding in online messages
• Identify respectful communication choices in common chat and comment situations
• Compare clear responses with replies that could be misread+ 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 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

• Identify reliable online information by checking evidence and clarity of authorship
• Compare sources by evaluating purpose, date, bias, and credibility
• Use source vocabulary (source, evidence, reliable, credibility) to explain why information should or should not be trusted+ Show more

Learning Objectives

• Define and explain the terms digital footprint and online presence.
• Describe how online choices can build a positive or negative reputation over time.
• Identify what information can leave a trace online and why it may be hard to remove.

Learning Objectives

• Define the terms input and output and explain how they work together in a program
• Identify examples of inputs, outputs, responses, and interactions in everyday software
• Use vocabulary to describe what happens when a program receives input and produces an output

Learning Objectives

• Explain how AI can help people save time and organize information
• Identify limits of AI such as mistakes and bias from data
• Use vocabulary words benefit, limit, bias, and accuracy in context+ Show more

Learning Objectives

• Define the terms recommendation, preference, suggestion, and algorithm in the context of recommendation systems.
• Explain how recommendation systems use past choices and patterns in data to suggest items.
• Identify examples of how suggestions can be helpful but not always perfect.

Learning Objectives

• Define artificial intelligence and describe what kinds of tasks it can do
• Identify how AI can recognize patterns, classify information, and make predictions
• Use vocabulary terms to explain common AI features in digital tools+ Show more

Learning Objectives

• Explain how a coding project plan helps guide building and reduce mistakes.
• Identify key parts of a plan, including a goal, features, inputs, outputs, and steps.
• Match project-planning vocabulary to its meaning.+ Show more

Learning Objectives

• Explain what a variable is and how it stores information in a program.
• Describe how updating a variable can change what a program does.
• Identify a variable’s value and predict how it changes after actions.

Learning Objectives

• Explain how code executes in the exact order commands are written
• Predict how changing the order of commands affects a program’s output
• Use sequencing vocabulary (sequence, order, command, output) to describe code behavior+ Show more

Learning Objectives

• Define debug, bug, error, and troubleshoot and use the words in explanations
• Identify common causes of program problems such as missing commands, wrong order, and logic that does not match the intended result
• Use tracing steps to find where code behavior first goes wrong and describe a fix+ Show more

Learning Objectives

• Define conditional, branch, rule, and decision in the context of simple programming.
• Identify how if, else, and otherwise choose different outcomes based on conditions.
• Complete a short branching program description using the correct vocabulary.+ Show more

Learning Objectives

• Define event, trigger, response, and interaction in the context of interactive programs.
• Identify events and their responses in examples that include clicks, taps, key presses, and timed actions.
• Explain how the same program can run different responses depending on the event that occurs.

Learning Objectives

• Define a variable and explain that it stores data values in a program
• Identify examples of data values (names, scores, points, and numbers) represented by variables
• Predict how changing a variable can change what a program displays or uses

Learning Objectives

• Define personal information and explain why it should stay private online.
• Choose which details are safe to share in messages, profiles, and forms.
• Explain how using strong, secure passwords helps protect accounts.+ Show more

Learning Objectives

• Explain how testing helps evaluate whether an algorithm works correctly.
• Identify weak points in an algorithm based on test results.
• Revise an algorithm so its steps are clearer and more accurate.+ Show more

Learning Objectives

• Define the terms conditional, condition, branch, and outcome.
• Use if-then logic to predict what happens next in a branching situation.
• Match common programming-like rules to the correct conditional meaning.+ Show more

Learning Objectives

• Define and use the terms compare, data set, difference, and relationship when working with numbers.
• Compare two data sets by describing similarities and differences in amounts, categories, and patterns.
• Identify simple relationships between two lists of information using evidence from the data.+ Show more

Learning Objectives

• Define and use the terms table, row, and column when describing data displays.
• Identify what information belongs in a specific row or column in a table.
• Use table structure to compare categories and find totals or relationships.+ Show more

Learning Objectives

• Explain how responsible AI use supports human judgment when making digital choices.
• Identify strategies for checking AI results for accuracy and fairness.
• Describe how respect for privacy applies to everyday AI features.