Worksheet Worksheets

Learning Objectives

• Identify features that make a password difficult to guess
• Explain how strong passwords help protect accounts and devices
• Recognize safe habits for keeping passwords private+ Show more

Learning Objectives

• Identify conditions that determine an algorithm's execution path
• Interpret Boolean values and distinguish conditional branches
• Trace conditional algorithms using different inputs and rules+ Show more

Learning Objectives

• Explain how decomposition makes large tasks easier to solve.
• Identify subproblems within familiar projects and everyday routines.
• Organize smaller steps into a logical sequence.+ Show more

Learning Objectives

• Define two-factor authentication and explain its purpose.
• Identify common second-step verification methods.
• Explain how a second authentication step reduces unauthorized access risk.+ Show more

Learning Objectives

• Define artificial intelligence and identify tasks associated with human thinking.
• Explain how AI systems recognize patterns in information.
• Describe how AI uses patterns to make predictions.+ Show more

Learning Objectives

• Identify events that cause computer programs to respond.
• Explain how inputs connect to program responses.
• Describe user actions that trigger program responses.+ Show more

Learning Objectives

• Identify repeated structures in routines, data, and algorithms
• Predict likely outcomes by recognizing reliable patterns
• Explain how patterns can make problem solving more efficient+ Show more

Learning Objectives

• Define variables, values, data, and storage in programming.
• Identify how variables store information in simple programs.
• Distinguish between assigning values and updating stored information.+ Show more

Learning Objectives

• Define efficiency, optimization, resource, and performance in algorithms.
• Compare algorithms using operation counts and resource requirements.
• Explain how linear search differs from binary search.+ Show more

Learning Objectives

• Calculate the mean, median, mode, and range of numerical data.
• Explain what each summary measure reveals about a data set.
• Compare groups using multiple numerical summary measures.+ Show more

Learning Objectives

• Identify standard flowchart symbols and explain their purposes.
• Explain how conditions determine the branches followed in a flowchart.
• Trace flowcharts to predict outputs for different inputs.+ Show more

Learning Objectives

• Explain how an algorithm becomes a sequence of code instructions
• Arrange code instructions in a logical sequence
• Identify when repetition can shorten repeated code instructions+ Show more

Learning Objectives

• Define abstraction and explain how it simplifies complex systems.
• Identify essential information for a specific problem-solving task.
• Compare representations and explain how each supports a different purpose.+ Show more

Learning Objectives

• Define data ethics, privacy, consent, and responsible data use.
• Identify responsible and irresponsible practices for handling personal information.
• Explain why informed consent and data minimization matter.+ Show more

Learning Objectives

• Identify how privacy settings control access to online content.
• Explain how application permissions affect access to personal information.
• Evaluate privacy options before sharing information online.+ Show more

Learning Objectives

• Explain how test cases compare expected and actual algorithm outputs
• Identify edge cases and boundary values that may reveal errors
• Trace algorithm steps to locate logical and calculation errors+ Show more

Learning Objectives

• Define machine learning, training data, models, and patterns.
• Explain how learning algorithms use examples to make predictions.
• Analyze how data quality and variety affect model accuracy.+ Show more

Learning Objectives

• Define conditional logic and explain its role in algorithms.
• Identify conditions, branches, and outcomes in if-then structures.
• Trace how different input values change program behavior.+ Show more

Learning Objectives

• Identify common flowchart symbols and explain their functions.
• Trace instruction sequences and decision branches in algorithms.
• Construct logical flowcharts using processes, decisions, and loops.+ Show more

Learning Objectives

• Define artificial intelligence and describe tasks associated with human thinking.
• Identify patterns in data that can support AI predictions.
• Explain how machine-learning systems use examples to learn relationships.+ Show more

Learning Objectives

• Define recommendation systems and describe their purpose on digital platforms
• Identify data types used to generate personalized content suggestions
• Explain how algorithms use observed behavior to estimate user interests+ Show more

Learning Objectives

• Define abstraction and explain how it reduces problem complexity.
• Identify essential and unnecessary details in simplified models.
• Compare representations designed for different purposes and users.+ Show more

Learning Objectives

• Explain how incomplete or unbalanced training data can introduce AI bias
• Distinguish bias, representation, fairness, and outcome using practical examples
• Identify strategies for improving AI training data quality and representation+ Show more

Learning Objectives

• Explain how privacy influences ethical decisions about artificial intelligence.
• Describe how transparency makes AI decisions easier to evaluate.
• Identify unfair outcomes linked to incomplete or unrepresentative training data.+ Show more

Learning Objectives

• Explain why programmers test programs before considering results reliable
• Compare an expected result with a program's actual output
• Identify instructions that may need correction after testing+ Show more

Learning Objectives

• Define pseudocode and explain its role in program planning
• Sequence instructions to solve an everyday problem logically
• Represent decisions and repeated actions in a program plan+ Show more

Learning Objectives

• Identify safe and responsible ways to use artificial intelligence tools.
• Explain why personal information should remain private online.
• Identify reliable ways to verify information generated by AI.+ Show more

Learning Objectives

• Define ethics, transparency, accountability, and responsibility in AI.
• Identify privacy and fairness concerns in AI-assisted decisions.
• Explain how transparency helps people question AI recommendations.+ Show more

Learning Objectives

• Identify bugs involving instruction order, missing steps, and incorrect values
• Trace program instructions and track changes in values
• Distinguish logic errors from other common programming mistakes+ Show more

Learning Objectives

• Identify evidence in tables and graphs that supports a claim
• Analyze patterns and comparisons in data displays
• Form conclusions supported by reliable data+ Show more

Learning Objectives

• Define an algorithm and explain the purpose of pseudocode
• Identify logical sequences in everyday procedures and computational problems
• Construct pseudocode using ordered steps, input, and output+ Show more

Learning Objectives

• Define a computer network and identify its connected nodes.
• Compare wired and wireless connections used by networked devices.
• Explain how switches and routers support network communication.+ Show more

Learning Objectives

• Identify inputs, outputs, events, and feedback in simple interactive programs.
• Explain how a user action starts a program's instructions.
• Describe how clear feedback helps users decide what happens next.+ Show more

Learning Objectives

• Define bias, fairness, representation, and outcome in artificial intelligence.
• Explain how unbalanced training data can produce unfair AI decisions.
• Identify ways to improve representation in AI training data.+ Show more

Learning Objectives

• Identify habits that support healthy and balanced technology use
• Explain how screen time fits alongside other daily activities
• Compare daily routines for healthy technology balance+ Show more

Learning Objectives

• Explain bug, debug, error, and troubleshoot using simple program examples.
• Identify sequencing errors caused by commands in the wrong order.
• Distinguish logical errors from sequencing errors in simple programs.+ Show more

Learning Objectives

• Identify the goal and intended audience of a digital project
• Explain how audience needs influence digital product features
• Organize project tasks in a sensible sequence+ Show more

Learning Objectives

• Identify conditions and outcomes in if-then rules
• Explain how branches create different program pathways
• Describe how inputs affect conditional decisions+ Show more

Learning Objectives

• Explain how testing reveals whether an algorithm works as intended
• Evaluate test results to identify weak points and errors
• Describe how revision improves accuracy, clarity, and reliability+ Show more

Learning Objectives

• Identify events that trigger responses in interactive games
• Explain how player actions can change game outcomes
• Describe how variables store changing game values+ Show more

Learning Objectives

• Define efficiency, algorithm, strategy, compare, and optimize
• Compare algorithms by examining steps and required effort
• Identify efficient approaches under the same conditions+ Show more

Learning Objectives

• Identify everyday benefits of AI tools using familiar classroom examples.
• Explain accuracy risks using examples of incorrect AI results.
• Describe how to protect personal information when using AI tools.+ Show more

Learning Objectives

• Define network protocols and explain why devices need shared rules.
• Describe how HTTP requests and responses support web communication.
• Identify client and server roles in accessing web resources.+ Show more

Learning Objectives

• Explain how algorithm efficiency relates to time, operations, and memory.
• Compare algorithms that produce the same result using operation counts.
• Identify optimization opportunities that preserve an algorithm's intended outcome.+ Show more

Learning Objectives

• Define a digital footprint and explain how online actions leave traces
• Describe how repeated digital choices can shape online reputation
• Identify respectful communication choices in digital spaces+ Show more

Learning Objectives

• Define reliable data, observation, and measurement.
• Identify appropriate methods for collecting accurate data.
• Explain how consistent procedures improve data reliability.+ Show more

Learning Objectives

• Identify clues that indicate whether an online news source is credible
• Distinguish misinformation from accurate reporting using supporting evidence
• Explain how publication dates and missing context affect news reliability+ Show more

Learning Objectives

• Explain how privacy settings control account visibility and contact.
• Evaluate app permissions according to an application's purpose.
• Describe how informed consent affects personal data sharing.+ Show more