Computer Science Worksheets

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

• Identify what makes a sequence program fail when a step is missing or out of order
• Use the terms debug, error, missing, and fix correctly in explanations
• Explain how checking each step helps find and correct mistakes+ Show more

Learning Objectives

• Define private information and personal information using Grade 3 vocabulary
• Identify which details should stay protected online versus what can be shared publicly
• Explain how to choose secure online information choices

Learning Objectives

• Identify common flowchart shapes and explain how arrows show a process
• Use decision steps to describe choices in a simple algorithm
• Interpret simple diagrams that show directions or repeated actions using basic vocabulary

Learning Objectives

• Explain how flowcharts use shapes and arrows to show the steps of a process
• Identify the meanings of flowchart parts such as arrows and decision steps
• Read simple visual algorithms and predict what happens next+ Show more

Learning Objectives

• Explain how encryption and decryption protect digital information.
• Identify key roles in secure communication, including keys and secure channels.
• Evaluate scenarios to decide whether a message is protected in transit or at rest.

Learning Objectives

• Define key search terms such as keyword, query, and result.
• Use more focused keywords to improve search results.
• Explain how a search engine uses a query to return results.+ Show more

Learning Objectives

• Identify key parts of graphs and charts, including categories and axes
• Compare data shown in bar graphs, line graphs, and pictographs
• Interpret information to answer questions using evidence from visual displays+ Show more

Learning Objectives

• Explain how bias can enter AI systems through unbalanced or incomplete training data
• Evaluate common fairness concerns and describe practical ways to reduce unequal outcomes
• Use fairness vocabulary (e.g., bias, data, testing, evaluation) to justify design choices

Learning Objectives

• Explain how variables store information that a program can use and update while it runs.
• Match common data types (integers, strings, booleans, lists) to suitable kinds of values.
• Predict whether a statement is correct based on data type rules.

Learning Objectives

• Explain what Big-O notation describes about how runtime or space grows as input size increases.
• Compare algorithms by identifying which has the better (slower-growing) time complexity.
• Justify answers using growth-rate reasoning instead of focusing on constant factors.

Learning Objectives

• Explain key cyber law and ethical responsibilities related to privacy and data handling.
• Identify appropriate and responsible actions when facing unauthorized access or misuse.
• Describe how intellectual property rules apply to copying and sharing digital content.

Learning Objectives

• Use precise step words to write code directions in a correct sequence.
• Identify how unclear instructions can cause mistakes in a computer program.
• Match coding terms to their meanings and use them in explanations.

Learning Objectives

• Explain how trees represent hierarchical relationships and how graphs represent network connections
• Use traversal ideas to describe how nodes can be visited in a tree or graph
• Determine path relationships and interpret common graph terms such as vertices, edges, and degree+ Show more

Learning Objectives

• Explain how labels communicate meaning in user interfaces and data representations.
• Identify common features of labeled interfaces, including readability, consistency, and clarity.
• Evaluate statements about labels and their role in usability and data understanding.

Learning Objectives

• Explain key AI ethics concepts: fairness, transparency, privacy, and accountability.
• Apply model evaluation ideas to decide whether an AI system is trustworthy across different groups and situations.
• Identify common sources of bias and unintended harmful outputs, and propose responsible evaluation steps.

Learning Objectives

• Explain how normalization reduces redundancy and improves update behavior in relational tables.
• Identify integrity problems caused by poor table design (insertion, update, and deletion anomalies).
• Apply rules of data integrity to keep records accurate, complete, and consistent over time.

Learning Objectives

• Explain how relational databases use tables, keys, and relationships to model real-world information.
• Identify good database design practices that reduce redundancy and improve data integrity.
• Evaluate statements about normalization, primary keys, and foreign keys in relational schemas.+ Show more

Learning Objectives

• Compare linear search and binary search in terms of required data conditions and time efficiency
• Trace the steps of a search algorithm and interpret the number of comparisons
• Select the best search method for a given data scenario and justify the choice

Learning Objectives

• Explain how generative AI and large language models learn patterns from data to produce new content
• Identify common limitations of generative AI, including errors, bias, and unclear reliability
• Apply strategies for deciding when to use generative tools and when to require human review

Learning Objectives

• Differentiate trees and graphs using key properties such as hierarchy, cycles, and connectivity
• Describe how traversal methods (like BFS/DFS) explore structures and find paths
• Apply graph and tree ideas to real-world relationship systems, such as maps and file structures

Learning Objectives

• Explain encryption, decryption, and the role of cryptographic keys in protecting data.
• Identify how cryptography helps secure communication and data online.
• Evaluate statements about ciphertext, plaintext, and security properties.

Learning Objectives

• Explain how relational databases use tables with records and fields to store structured data.
• Identify how relationships between tables support real-world queries and data integrity.
• Distinguish between effective table purposes and design choices in relational models.

Learning Objectives

• Define key algorithm vocabulary such as algorithm, sequence, process, and instruction.
• Identify the correct order of steps in a simple algorithm.
• Use logical reasoning to choose the best algorithm for a given situation.+ Show more

Learning Objectives

• Define malware, virus, download, and protection in simple computer-safety terms
• Identify risky signs in file names, links, and message attachments
• Explain how to protect devices and accounts when downloading files+ Show more

Learning Objectives

• Define malware and identify common types such as viruses and ransomware
• Explain how device protection strategies reduce cybersecurity risks
• Apply knowledge to choose safer actions when malware threats are possible+ Show more

Learning Objectives

• Define pseudocode and explain how it helps plan a program before writing code.
• Use sequence and logic to outline steps for a simple everyday task.
• Match planning terms (plan, sequence, logic) to their meanings.+ 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

• Explain how inheritance supports code reuse by defining parent and child classes.
• Use method overriding to change child class behavior while keeping the same method interface.
• Describe polymorphism and predict how different objects can respond to the same method call.+ Show more

Learning Objectives

• Define and use the terms decision, choice, condition, and branch when discussing decision trees.
• Read a simple decision tree and follow the correct path to reach an outcome.
• Explain how different yes/no conditions lead to different results in a decision tree.

Learning Objectives

• Identify the rule in numeric, visual, and action patterns
• Use a pattern rule to predict what comes next in a sequence
• Explain how repeating steps help make accurate predictions+ Show more

Learning Objectives

• Identify repeated structures in a problem or algorithm
• Explain how pattern recognition helps predict outcomes
• Use the ideas of pattern and structure to improve a solution approach+ Show more

Learning Objectives

• Explain what an algorithm, sequence, instruction, and process mean
• Order steps in a correct sequence to complete a task
• Use clear, precise instructions to design an everyday or digital procedure+ Show more

Learning Objectives

• Explain how pseudocode uses plain language to describe program logic and sequence.
• Write and revise simple plans for tasks using ordered steps.
• Identify correct logic and order when statements or steps are given.

Learning Objectives

• Explain the difference between arrays and lists and when each is useful.
• Use indexing, iteration, and search strategies to find elements and compute totals or averages.
• Analyze how ordered collections affect retrieval and update operations.

Learning Objectives

• Put a set of actions in the correct order to complete a multi-step process.
• Identify what happens first, next, and last in a given set of steps.
• Choose the correct sequence when solving a simple problem.

Learning Objectives

• Describe the typical incident response process and the priorities during containment and recovery.
• Explain why documentation and evidence handling matter during investigation and restoration.
• Use decision-making skills to select appropriate next steps during an incident.

Learning Objectives

• Explain how algorithms use input, processing, and output to make decisions.
• Describe how relationships in data help an AI system generate results.
• Evaluate how algorithm design choices can affect accuracy and reliability.

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

• Define and use the terms benefit, risk, privacy, and fairness when talking about AI.
• Identify common everyday examples of how AI is used and explain one benefit and one risk.
• Explain how privacy, fairness, and accuracy can affect people when AI is used.+ Show more

Learning Objectives

• Explain how taking breaks supports focus and learning.
• Identify healthy technology routines and describe what a balanced screen time habit looks like.
• Compare healthy and unhealthy technology choices in everyday situations.

Learning Objectives

• Define cyberbullying and harassment and distinguish them from normal online disagreement
• Identify effective response steps, including reporting and preserving evidence
• Use bystander and support strategies to help someone affected by cyberbullying+ Show more

Learning Objectives

• Explain how decomposition breaks a large problem into smaller subproblems.
• Use a simple strategy to plan steps before coding.
• Identify whether a statement correctly describes decomposition and solutions.

Learning Objectives

• Distinguish regression models from classification models based on the type of prediction target.
• Identify factors that affect prediction accuracy, including model fit and variable relationships.
• Use basic reasoning to select appropriate modeling choices for numerical prediction problems.

Learning Objectives

• Identify common HTML elements and describe what they do in a web page.
• Use semantic HTML elements to organize content logically.
• Recognize correct element hierarchy for typical page sections.

Learning Objectives

• Explain how version control helps teams track changes, compare versions, and restore earlier work
• Describe how collaboration tools support shared editing, feedback, and organized teamwork
• Identify common rules for coordinating edits to avoid overwriting and reduce merge conflicts

Learning Objectives

• Explain what a primary key is and why it must uniquely identify records.
• Describe how foreign keys create relationships between tables.
• Use primary and foreign keys to interpret table relationships and prevent confusion between records.

Learning Objectives

• Define artificial intelligence, automation, algorithm, and prediction in everyday terms.
• Identify how recommendation systems and virtual assistants use data to make predictions.
• Explain how AI affects daily communication, entertainment, transportation, and education.+ Show more