Data Integrity & Algorithmic Bias: 9th Grade Cybersecurity Literacy Quiz (Medium) 워크시트 • 무료 PDF 다운로드 정답 키 포함
High schoolers identify structural bias in machine learning and apply data cleaning techniques to maintain digital integrity and ethical accuracy.
교육적 개요
This assessment evaluates student understanding of data ethics, algorithmic bias, and digital integrity within a modern cybersecurity context. The quiz utilizes a formative assessment approach, transitioning from basic data cleaning definitions to complex scenarios involving proxy variables and sampling bias. It is ideally suited for a high school computer science or media literacy unit, aligning with CSTA standards for data and analysis.
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- Identify common types of algorithmic bias, including sampling bias and the use of inappropriate proxy variables.
- Evaluate the integrity of data sets by recognizing the risks of low-quality data and the importance of data provenance.
- Analyze data visualizations for potential bias or misleading representations such as truncated axes.
All 10 Questions
- An urban planning group uses transit app data to determine where to build new bike lanes. What is the most significant 'sampling bias' risk in this dataset?A) The data only represents residents who own smartphones and use that specific app.B) The data is stored in a cloud-based server rather than a local hard drive.C) The app uses GPS coordinates instead of manual address entries.D) The dataset includes information from both weekends and weekdays.
- Data 'scrubbing' or cleaning is the process of removing outliers or errors from a dataset to improve the accuracy of the final analysis.A) TrueB) False
- When a researcher uses data collected by a government agency (like the World Health Organization) rather than gathering it themselves, they are using _______ data.A) PrimaryB) SecondaryC) QualitativeD) Anecdotal
Show all 10 questions
- Which of these is a 'proxy variable' for measuring a person's socioeconomic status if direct income data is unavailable?A) Their favorite colorB) The number of hours they sleepC) Their highest level of education completedD) The operating system of their computer
- Correlation between two data points (such as ice cream sales and sunburns) always proves that one variable caused the other to happen.A) TrueB) False
- The ethical practice of making data 'anonymous' by removing names, Social Security numbers, and birthdates is known as _______.A) De-identificationB) CategorizationC) Data MiningD) Encryption
- A data visualization uses a truncated y-axis (starting at 50 instead of 0) to show a small increase in stock prices. Why might this be considered misleading?A) It hides the fact that the data is qualitative.B) It makes a small change look much more dramatic than it actually is.C) It prevents the reader from seeing the historical data.D) It identifies the source of the data too clearly.
- What is the primary risk of using 'Low-Quality' data (data that is outdated or inaccurate) in an Artificial Intelligence model?A) The model will take up too much storage space.B) The model will automatically delete the data.C) The model will produce 'Garbage In, Garbage Out' (GIGO) results.D) The model will require more electricity to run.
- When evaluating a source, a data scientist looks at the _______, which describes the history, origins, and movements of a dataset.A) Data ProvenanceB) Data VolumeC) File ExtensionD) Metadata Tagging
- Open Data initiatives are projects that make government and scientific datasets freely available for anyone to use, redistribute, and reuse.A) TrueB) False
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자주 묻는 질문
Yes, this Cybersecurity Literacy Quiz is an excellent choice for a substitute plan because it features clear explanations for every answer, allowing students to self-correct and learn independently even without a subject-matter expert present.
Most ninth-grade students can complete this Cybersecurity Literacy Quiz in approximately 20 to 30 minutes, making it a perfect tool for a mid-period check for understanding or a focused exit ticket.
This Cybersecurity Literacy Quiz supports differentiation by providing a mix of multiple-choice and true-false questions that scaffold from basic terminology to higher-order ethical analysis of real-world data scenarios.
While specifically designed as a 9th Grade Cybersecurity Literacy Quiz, the content is highly relevant for any high school introductory computer science or social studies course focusing on data ethics and digital footprints.
You can use this Cybersecurity Literacy Quiz as a pre-assessment to gauge prior knowledge of data bias or as a post-lesson check to ensure students understand key concepts like data provenance and de-identification before moving on to hands-on data projects.
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