Computer Science Worksheets

Learning Objectives

• Define variables, values, data types, and assignment in programming.
• Distinguish integers, decimals, strings, and Boolean values.
• Explain how assignment initializes or updates a variable.+ Show more

Learning Objectives

• Identify common examples of input used by programs
• Explain how programs process input and produce output
• Distinguish between input, output, response, and interaction+ Show more

Learning Objectives

• Identify common types of programming errors
• Explain how tracing code helps locate a bug
• Describe how programmers troubleshoot and test corrections+ Show more

Learning Objectives

• Identify repeated actions and structures across different problems
• Explain how patterns can help predict what happens next
• Compare tasks to find similarities that can be reused+ Show more

Learning Objectives

• Define input, processing, and output in a computer system.
• Identify common input and output devices and explain their functions.
• Trace data through input, processing, and output stages.+ Show more

Learning Objectives

• Identify features that make passwords difficult to guess
• Explain why different passwords protect separate accounts
• Describe safe habits for protecting login details+ Show more

Learning Objectives

• Define digital footprints, online presence, and online reputation.
• Identify everyday activities that leave digital traces.
• Compare positive and negative online behaviors.+ Show more

Learning Objectives

• Identify behaviors that can be considered cyberbullying
• Explain safe and respectful bystander responses to online harm
• Choose appropriate ways to report online harassment+ Show more

Learning Objectives

• Define digital footprints, online presence, and online reputation.
• Identify online activities that create lasting digital traces.
• Compare positive and negative online behaviors and their consequences.+ Show more

Learning Objectives

• Define machine learning, training data, patterns, and models.
• Explain how algorithms identify patterns in training examples.
• Compare how data accuracy and variety affect model performance.+ Show more

Learning Objectives

• Define iteration as a repeated cycle of testing and improvement
• Identify usability problems revealed by testing and user feedback
• Compare original and revised project versions using test evidence+ Show more

Learning Objectives

• Identify similarities and differences between two sets of data
• Compare amounts using greater, less, and same
• Read simple tables and classroom survey results+ Show more

Learning Objectives

• Define malware and identify common ways harmful software reaches devices
• Recognize warning signs in unsafe downloads and suspicious attachments
• Explain how malware can affect files, devices, and personal information+ Show more

Learning Objectives

• Identify strategies for solving simple classroom problems
• Compare strategies using clarity, efficiency, and accuracy
• Explain why a strategy fits a specific problem+ Show more

Learning Objectives

• Identify common benefits and limits of artificial intelligence
• Explain how data quality affects AI-generated results
• Describe how bias can influence AI outputs and decisions+ Show more

Learning Objectives

• Identify common parts of flowcharts and simple diagrams
• Explain how shapes and arrows show process order
• Interpret decisions and repeated actions in visual algorithms+ Show more

Learning Objectives

• Identify conditions, choices, branches, and paths in decision trees
• Explain how yes-or-no answers guide different computer results
• Follow simple decision-tree paths to determine outcomes+ Show more

Learning Objectives

• Identify conditions that determine which program instructions execute.
• Explain how if-then-else statements create alternative program branches.
• Trace conditional statements using different inputs and Boolean results.+ Show more

Learning Objectives

• Identify machine learning as learning from examples
• Explain how training data helps systems find patterns
• Describe how models use patterns to make predictions+ Show more

Learning Objectives

• Define a digital footprint and identify online traces
• Identify online activities that can leave digital traces
• Distinguish responsible from careless online choices+ Show more

Learning Objectives

• Identify common phishing warning signs in digital messages.
• Explain how urgent language can pressure recipients into risky actions.
• Distinguish suspicious communications from messages requiring safe verification.+ Show more

Learning Objectives

• Identify common forms of cyberbullying in digital spaces
• Explain how bystanders can support people experiencing online harassment
• Describe safe ways to block and report harmful accounts+ Show more

Learning Objectives

• Identify information in tables and graphs that supports an answer
• Interpret simple data displays by comparing values and patterns
• Identify evidence that supports a data-based conclusion+ Show more

Learning Objectives

• Define a variable and identify its stored value
• Identify information that can be stored in variables
• Explain how stored values change while programs run+ Show more

Learning Objectives

• Explain how the DOM represents a web page as objects that JavaScript can read and change
• Identify how event handlers (like button clicks) trigger JavaScript to update content
• Use correct JavaScript reasoning to predict how changes affect elements on a page

Learning Objectives

• Define a program as a set of instructions that tells a computer what actions to perform.
• Identify examples of program output and actions, such as moving a character or displaying messages.
• Match key vocabulary terms (program, instruction, output, command) to their meanings.+ Show more

Learning Objectives

• Define and use the words evidence, conclusion, and interpret when working with data.
• Read simple graphs and tables to describe what the data shows.
• Choose a conclusion that matches the evidence instead of guessing.

Learning Objectives

• Define algorithm, code, sequence, and repeat using simple examples.
• Arrange steps in the correct sequence to solve a programming problem.
• Identify how repeating instructions can reduce work in a program.+ Show more

Learning Objectives

• Define and use the vocabulary compare, data set, relationship, and difference when discussing data.
• Identify similarities and differences between two or more data sets using greater, less, equal, and changing values.
• Describe how a relationship can be shown by how values change across data sets.+ Show more

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

• Define two-factor authentication and explain how it adds an extra security step.
• Identify common second factors such as a code, a message, or an app prompt.
• Compare single-step login versus two-step verification using a real-world lock example.

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 test, output, result, and correct as they relate to checking a program
• Compare an expected outcome with the actual output from a program test
• Choose the correct conclusion about whether a program’s output matches the intended result+ 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 key digital wellness terms and explain why they matter.
• Match strategies to examples that support healthier screen time.
• Use screen-time management habits to plan a balanced day.+ Show more

Learning Objectives

• Explain what a strategy is and how it helps with a solution to a problem
• Compare two solution strategies by considering clarity, speed, and accuracy
• Choose the most efficient strategy for a simple classroom problem

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

• Identify how algorithms use steps to solve problems
• Explain what variables store in an algorithm
• Use conditional logic to choose different outcomes

Learning Objectives

• Explain the difference between stack (LIFO) and queue (FIFO) behavior.
• Identify which ADT best fits a given scenario using push/pop or enqueue/dequeue operations.
• Analyze statements about stack and queue operations for correctness.+ Show more

Learning Objectives

• Define evidence, conclusion, and analysis using data displays.
• Use information from a table or graph to choose the best conclusion.
• Explain how analysis of data supports a claim.

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.

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

• 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

• 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

• Define key terms: recommendation, preference, prediction, and algorithm.
• Explain how a recommendation system uses information and patterns to make predictions.
• Identify examples of recommendation systems and describe how they suggest items.

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 how labels are used in diagrams and documentation to identify parts of a system or model
• Distinguish between labels and other features such as captions, annotations, and component names
• Apply correct terminology when describing features of labeled representations

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.