Grade 7 Computer Science Worksheets

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 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

• 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 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

• 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 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

• 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

Learning Objectives

• Explain how testing checks whether an algorithm works as intended under different conditions
• Use validation results to revise an algorithm for better reliability and clarity
• Identify vocabulary terms: testing, validation, refinement, and revision+ Show more

Learning Objectives

• Define pseudocode and explain its role in algorithm design
• Identify sequence, selection, and iteration in pseudocode
• Translate problem descriptions into step-by-step logic plans+ Show more

Learning Objectives

• Define and use key terms related to program planning, including pseudocode, algorithm, structure, and plan
• Translate a problem description into clear steps using pseudocode
• Choose appropriate logic and check statements for correctness before writing code

Learning Objectives

• Identify common data types, including integer, string, and boolean
• Distinguish data types from data values and explain why type choice matters
• Use data types to decide which operations or comparisons are appropriate

Learning Objectives

• Explain how variables, events, conditionals, and loops work together in an interactive application.
• Describe how program structure supports user interaction and intended functionality.
• Use key vocabulary (application, interface, interaction, functionality) accurately in explanations.

Learning Objectives

• Explain how functions help organize code into reusable modules for specific tasks.
• Identify the role of parameters and return values in function design.
• Describe how modular programming improves readability, testing, and maintenance.

Learning Objectives

• Identify common programming errors such as syntax errors and logic errors
• Describe how systematic testing helps troubleshoot a program
• Match debugging vocabulary to correct definitions+ Show more

Learning Objectives

• Identify patterns and relationships in examples to predict outcomes
• Use generalization to reuse a solution strategy for new problems
• Explain why a rule or prediction works using evidence from patterns

Learning Objectives

• Define key machine learning terms: machine learning, training data, model, and prediction.
• Explain how training data helps a model learn patterns for future predictions.
• Evaluate statements about machine learning using basic vocabulary and reasoning.

Learning Objectives

• Explain how artificial intelligence (AI) is used in everyday tools such as virtual assistants and recommendation systems.
• Use key vocabulary (artificial intelligence, automation, algorithm, prediction) to describe how AI makes decisions.
• Evaluate statements about AI accuracy, data, and predictions as True or False.+ Show more

Learning Objectives

• Define digital footprint and explain how it forms from online activity.
• Describe how online presence can affect reputation and future opportunities.
• Identify how permanence and context influence what stays searchable over time.

Learning Objectives

• Use credibility, evidence, and bias to evaluate online claims
• Identify misinformation by checking authorship, sources, and supporting evidence
• Practice choosing the most reliable online information for school and personal decisions

Learning Objectives

• Explain how different online actions create a digital footprint.
• Describe how online presence can affect reputation and opportunities.
• Apply strategies to protect privacy and manage permanence.

Learning Objectives

• Define key statistics vocabulary: mean, median, range, and distribution
• Use averages and range to summarize data and compare groups
• Evaluate statements about statistics using true/false reasoning+ Show more

Learning Objectives

• Use keyword choices and search operators to make online queries more targeted.
• Evaluate search results for relevance and credibility before using information.
• Compare broad and focused searches to improve the quality of findings.

Learning Objectives

• Explain how encryption and decryption protect information during secure communication.
• Identify the role of a key in encryption and understand why it matters for security.
• Evaluate whether statements about encryption and secure communication are correct.

Learning Objectives

• Identify common uses of different data visualization types such as charts and graphs.
• Explain how visualizations reveal patterns and trends that may be hard to see in raw data.
• Use key visualization vocabulary correctly, including visualization, chart, graph, and trend.

Learning Objectives

• Explain how testing helps validate an algorithm under different conditions.
• Identify ways to revise an algorithm based on observed test results.
• Use vocabulary such as testing, validation, refinement, and revision to describe improvement steps.

Learning Objectives

• Explain how ethics, accountability, transparency, and responsibility relate to AI decisions.
• Identify ethical risks in everyday AI examples, including privacy and biased outcomes.
• Describe practical steps to improve trust in AI systems.

Learning Objectives

• Interpret flowcharts by following arrows and decisions to predict an outcome.
• Use correct flowchart vocabulary to describe a process and its branches.
• Create a simple process model using decision points and branches.

Learning Objectives

• Define and use spreadsheet vocabulary including worksheet, cell, row, and column.
• Identify rows, columns, and cells in a simple spreadsheet layout.
• Use sorting to reorganize information while keeping related data together.+ Show more

Learning Objectives

• Describe the difference between a pattern and a trend in data.
• Explain how correlation relates to pattern changes over time or across categories.
• Use careful analysis to make a reasonable prediction from data.

Learning Objectives

• Explain what bias is in AI and how it can affect outcomes.
• Describe fairness by using the ideas of representation and evaluation.
• Identify ways to reduce bias by checking data and test results.

Learning Objectives

• Define phishing and social engineering and explain how deception is used in these attacks.
• Identify common warning signs in realistic messages and describe safer next steps.
• Match social engineering terms to their correct meanings.+ Show more

Learning Objectives

• Identify the roles of servers, routers, and packets in data transfer
• Explain how transmissions move from a sender to a destination using interconnected networks
• Describe how websites and messages are delivered using routing and packet switching+ Show more

Learning Objectives

• Explain how servers, routers, and networks work together to transfer data.
• Describe how packets are transmitted and why transmission happens in many steps.
• Use correct vocabulary to compare wired and wireless data transfer methods.

Learning Objectives

• Explain key cybersecurity vocabulary: cybersecurity, vulnerability, prevention, and threat.
• Identify safe online habits that reduce risks for devices and accounts.
• Recognize common warning signs of cyber threats and choose appropriate prevention steps.

Learning Objectives

• Define cloud computing, server, storage, and synchronization in everyday terms.
• Explain how cloud services enable access to files and applications from different devices.
• Identify benefits of cloud systems for collaboration and flexibility.+ Show more

Learning Objectives

• Define cloud computing and explain how it uses remote servers instead of local devices.
• Describe the roles of storage and synchronization in keeping files up to date.
• Identify examples of cloud services and explain how they support collaboration and flexibility.

Learning Objectives

• Explain how abstraction helps focus on important information while ignoring unnecessary details.
• Identify and describe a model or representation of a system using simplified features.
• Use abstraction to simplify a problem and support an algorithm design.

Learning Objectives

• Identify key features of credible online sources, including evidence, authorship, and bias.
• Use vocabulary terms such as misinformation, credibility, evidence, and bias to explain source quality.
• Apply a source-evaluation process to decide whether a claim should be accepted or questioned.

Learning Objectives

• Explain how privacy settings control who can view personal information and activity.
• Describe data protection practices that reduce the risk of unwanted sharing.
• Use permissions and account settings to manage visibility and data access.

Learning Objectives

• Explain how consistent methods and reliable measurements improve data quality.
• Use validation steps to check that collected data is complete and trustworthy.
• Compare different data collection methods and identify common sources of error.

Learning Objectives

• Define phishing and social engineering and describe how they try to manipulate people.
• Identify common warning signs in realistic messages and explain safer next steps.
• Use key vocabulary (deception, scam) to describe how attackers pressure victims.

Learning Objectives

• Explain how privacy, intellectual property, and respect guide ethical technology choices.
• Identify responsible actions when facing common digital dilemmas.
• Apply digital citizenship principles to online behavior and information sharing.

Learning Objectives

• Explain how computer networks connect devices and move information between locations.
• Use key vocabulary (network, node, connection, infrastructure) to describe network parts and functions.
• Identify the difference between local communication and global communication in networks.

Learning Objectives

• Explain how loops use repetition to automate repeated steps in a program.
• Use loop ideas to predict what a program will do over multiple iterations.
• Compare efficiency and code clarity when using loops instead of duplicate instructions.

Learning Objectives

• Identify and use key spreadsheet vocabulary: spreadsheet, worksheet, cell, row, and column.
• Explain how data is organized in rows and columns to form cells in a spreadsheet.
• Describe and apply simple spreadsheet skills such as sorting information.

Learning Objectives

• Use evidence and data analysis to support a conclusion or recommendation.
• Explain how a decision can be justified by comparing alternatives using logical reasoning.
• Use key vocabulary words: evidence, analysis, conclusion, and decision.

Learning Objectives

• Identify trends and patterns in data presented over time or across categories.
• Explain how correlation can suggest relationships but does not prove causation.
• Use analysis to make reasonable predictions based on observed data.+ Show more