Computer Science Worksheets

Learning Objectives

• Explain how surveys gather information by asking questions
• Identify data collected through questions, observations, and counts
• Recognize responses recorded during a classroom survey+ Show more

Learning Objectives

• Identify key features of bar graphs and pictographs
• Interpret graph scales and pictograph keys accurately
• Compare quantities across categories using visual data+ Show more

Learning Objectives

• Explain how conditional statements use logical comparisons to choose which instructions run.
• Identify the correct logic and comparison operator for a given situation.
• Interpret if/else behavior in simple program scenarios.

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

• 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

• Explain what phishing is and how scam messages try to trick people.
• Identify warning signs in fake messages, such as urgent language and suspicious links.
• Use safe response strategies when you see suspicious or fraud attempts online.

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

• 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 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 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 the difference between bandwidth and latency in computer networks
• Predict how latency and bandwidth affect the time it takes for data to move
• Use network vocabulary such as delay, packet, and throughput accurately

Learning Objectives

• Explain how abstraction removes nonessential details to focus on essential features of a problem
• Use models and representations to describe systems, patterns, and relationships
• Identify examples of essential information in a simplified computer science scenario

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

• Differentiate syntax errors from logic errors and explain why each affects program behavior differently.
• Use debugging steps like tracing, testing hypotheses, and checking results to find and fix errors.
• Apply vocabulary such as debug, syntax, logic, and troubleshoot to describe debugging in a clear, accurate way.

Learning Objectives

• Explain how data ethics guides responsible collection, storage, and data use
• Describe how privacy and consent help protect personal information
• Apply privacy and ethics concepts to common digital situations

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

• Explain what survey data is and how it is collected by asking questions
• Use survey vocabulary (survey, data, collect, response) correctly in simple sentences
• Identify the best way to ask questions for a classroom survey and record answers

Learning Objectives

• Identify how events trigger program responses in event-driven systems
• Use key vocabulary (event, trigger, interaction, response) to explain what happens in a program
• Evaluate whether statements about event-driven programming are true or false+ Show more

Learning Objectives

• Choose an appropriate chart type to communicate patterns, comparisons, or trends in data.
• Use key visualization vocabulary (visualization, graph, chart, category) accurately in explanations.
• Evaluate whether a graph type matches the question being asked about the data.

Learning Objectives

• Explain what a variable stores and how assignment changes its value in a program.
• Identify common data types (numbers, text, booleans) and match them to appropriate operations.
• Use variables to compare values and understand how comparisons depend on data type.

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 networks connect devices to communicate and share resources
• Identify common network infrastructure components such as routers and transmission media
• Use key vocabulary (network, device, router, connection) correctly in context+ 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

• Identify common programming errors such as syntax mistakes and logic errors
• Use a systematic debugging process to test and troubleshoot code
• Explain how assumptions can cause incorrect program behavior

Learning Objectives

• Explain why testing checks whether digital features work as intended
• Identify useful observations and feedback from digital product testing
• Compare testing results with user feedback about a product+ Show more

Learning Objectives

• Explain the difference between mean and median for a numeric data set.
• Compute the mean and median from a list of values and interpret what they represent.
• Recognize when median is more reliable than mean in the presence of outliers.

Learning Objectives

• Use keyword selection to make search queries more precise and relevant.
• Apply common search operators and quotation marks to narrow results.
• Interpret search filters and relevance to improve research quality.

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 abstraction, model, and essential details accurately
• Explain how abstraction simplifies complex systems
• Identify essential details in a complex situation+ 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 functions and explain their role in modular programs
• Identify how parameters provide input to reusable functions
• Explain how return values send results to calling code+ Show more

Learning Objectives

• Explain how algorithm efficiency affects performance and resource use
• Use optimization strategies to improve an algorithm without changing its correct outcome
• Compare multiple algorithms for the same task and justify which is more efficient

Learning Objectives

• Describe how reliable data is collected using careful observation, accurate counting, and consistent methods.
• Use key vocabulary words (reliable, observe, count, data) correctly in science and computer science contexts.
• Decide whether statements about data collection are true or false and explain short answers clearly.

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

• 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

• Explain how shared documents, comments, version history, and permissions support teamwork.
• Use key vocabulary (collaboration, permission, comment, version) accurately in sentences.
• Identify correct practices for working together safely and effectively online.

Learning Objectives

• Explain how clarity and consistency improve a user interface.
• Use key interface vocabulary (user interface, layout, button, navigation) to describe design choices.
• Identify usability principles and apply them to common UI elements like menus and controls.+ Show more

Learning Objectives

• Explain how bias can appear in AI when training data is incomplete or unbalanced.
• Use key vocabulary (bias, fairness, representation, outcome) to describe AI results.
• Identify ways to improve fairness by changing data collection and evaluation.

Learning Objectives

• Define password, credential, authentication, and secure accurately
• Compare weak and strong password protection methods
• Explain why password reuse increases account security risks+ Show more

Learning Objectives

• Define mean, median, mode, and range accurately
• Choose an appropriate summary measure for a data question
• Compare groups using numerical summaries+ Show more

Learning Objectives

• Identify everyday browsing actions that reduce cybersecurity risks
• Explain why software updates improve device protection
• Explain how secure device settings support cybersecurity+ Show more

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 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 phishing and social engineering and explain how deception is used to obtain sensitive information.
• Identify red flags in realistic messages and online requests.
• Choose safer actions when encountering suspicious login, payment, or account-recovery requests.

Learning Objectives

• Define encryption, decryption, ciphertext, and key in secure communication
• Explain how encryption protects data during network transmission
• Explain how encryption protects data stored on devices+ Show more

Learning Objectives

• Define loops and iteration using correct programming vocabulary
• Identify how loops repeat instructions to change program behavior
• Choose loop conditions for counting, checking, and pattern tasks+ Show more

Learning Objectives

• Define bias and fairness in the context of AI systems.
• Explain how representation in training data can affect AI outcomes.
• Identify examples of biased data or design choices that lead to unfair results.+ 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.