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Standards Mapping

for ID 9-12

58

Standards in this Framework

19

Standards Mapped

32%

Mapped to Course

Standard Lessons
9-12.CS.1.1
Identify and describe hardware components.
9-12.CS.1.2
Identify and evaluate what computing system resources are required for a specific software program.
9-12.CS.1.3
Identify the use of embedded computers in various applications.
9-12.CS.1.4
Create or modify a program that uses different forms of input and output.
9-12.CS.1.5
Identify how a high level programming language abstracts machine language in a computer program.
9-12.CS.1.6
Create a model of how embedded systems sense, process, and interact in a given environment.
9-12.CS.2.1
Use applicable data collection techniques for various scenarios.
  1. 1.2 Gathering Data
  2. 1.10 Mini-Project: Findings
  3. 2.3 Importing and Filtering Data
9-12.CS.2.2
Apply basic techniques for locating, collecting, and understanding the quality of data sets.
  1. 2.5 Data Cleaning
  2. 4.2 Quality Datasets
9-12.CS.2.3
Analyze data and identify patterns through modeling and simulation.
  1. 1.5 Series and Central Tendency
  2. 1.6 Measures of Spread
  3. 3.3 Data Visualizations
  4. 3.7 Trends and Correlations
  5. 3.8 Linear Regression
  6. 3.9 Explore Bivariate Data
9-12.CS.2.4
Use data analysis to show the transformation from data to information to knowledge.
  1. 1.5 Series and Central Tendency
  2. 1.6 Measures of Spread
  3. 2.7 Interpret and Present
  4. 3.1 Data Storytelling
9-12.CS.2.5
Use models and simulations to help formulate, refine, and test scientific hypotheses.
9-12.CS.2.6
Compare and contrast the viewpoints on cybersecurity from the perspective of security experts, privacy advocates, and the government.
9-12.CS.2.7
Analyze the strengths and weaknesses of security policies based on their usage of encryption and authentication strategies.
9-12.CS.2.8
Convert between binary, decimal, octal, and hexadecimal representations of data.
9-12.CS.2.9
Describe how real-world phenomena such as numbers, Strings, or images are represented as binary in a computer.
9-12.CS.2.10
Analyze the trade-offs among various compression algorithms.
9-12.CS.3.1
Demonstrate responsible digital citizenship (legal and ethical behaviors) in the use of technology systems and software.
9-12.CS.3.2
Explain the social and economic implications associated with unethical computing practices.
9-12.CS.3.3
Discuss trade-offs such as privacy, safety, and convenience associated with the collection and large-scale analysis of personal information.
  1. 2.2 Big Data and Bias
  2. 4.6 Bias in Data Analytics
9-12.CS.3.4
Identify and evaluate the beneficial and harmful effects of computing innovations on behavior and culture.
  1. 2.2 Big Data and Bias
  2. 4.6 Bias in Data Analytics
9-12.CS.3.5
Debate how the issues of equity, data access, and distribution of computing resources create a digital divide in a global society.
  1. 2.2 Big Data and Bias
  2. 4.6 Bias in Data Analytics
9-12.CS.3.6
Debate laws and regulations that impact the development, security and use of software.
9-12.CS.3.7
Understand and define artificial intelligence.
  1. 3.8 Linear Regression
9-12.CS.3.8
Research and explain the social, moral, ethical, and legal impacts of artificial intelligence systems and respective usage.
  1. 2.2 Big Data and Bias
  2. 4.6 Bias in Data Analytics
9-12.CS.3.9
Explain how computer automation continues to transform society and the global economy (e.g. financial markets, transactions, predictions).
9-12.CS.3.10
Research, analyze, and present how computational thinking has enabled computing to revolutionize business, manufacturing, commerce and society.
9-12.CS.3.11
Evaluate the accessibility of a computational artifact.
9-12.CS.3.12
Describe how computer science shares features with creating and designing an artifact such as in music and art.
9-12.CS.3.13
Understand the ecosystem of open-source software development and its impact on global collaboration.
9-12.CS.3.14
Explain how computer science fosters innovation and enhances other career and disciplines.
9-12.CS.4.1
Illustrate the basic components of computer networks and protocols.
9-12.CS.4.2
Analyze the issues that impact network functionality.
9-12.CS.4.3
Describe the data flow that occurs when using Internet-based services.
9-12.CS.4.4
Examine how encryption is essential to ensuring privacy and security over the internet.
9-12.CS.5.1
Diagram the flow of execution and output of a given program.
9-12.CS.5.2
Design algorithms using sequence, selection, iteration and recursion.
  1. 1.9 Using Functions
  2. 2.4 Conditional Filtering
9-12.CS.5.3
Use variable scope and encapsulation to design programs with cohesive and modular components.
  1. 1.4 Modules, Packages & Libraries
  2. 1.9 Using Functions
9-12.CS.5.4
Decompose a complex problem using abstraction through methods and/or classes.
  1. 1.1 What is Data Science?
  2. 1.9 Using Functions
9-12.CS.5.5
Demonstrate the value of abstraction to manage problem complexity.
  1. 1.7 Pandas DataFrames
  2. 1.9 Using Functions
9-12.CS.5.6
Demonstrate code reuse by creating programming solutions using APIs and libraries.
  1. 1.4 Modules, Packages & Libraries
  2. 1.7 Pandas DataFrames
9-12.CS.5.7
Evaluate the qualities of a program such as correctness, usability, readability, efficiency, portability and scalability through processes such as debugging and code review.
  1. 1.10 Mini-Project: Findings
  2. 2.7 Interpret and Present
9-12.CS.5.8
Compare and contrast simple data structures and their uses.
  1. 1.5 Series and Central Tendency
  2. 1.7 Pandas DataFrames
9-12.CS.5.9
Compare software development processes.
9-12.CS.5.10
Demonstrate an understanding of the software life cycle process.
9-12.CS.5.11
Design and develop a software artifact by leading, initiating, and participating in a team.
9-12.CS.5.12
Create collaborative software projects using Integrated Development Environments, or other collaborative tools.
9-12.CS.5.13
Understand the positive and negative implications that arise when you add functionality to an existing program.
9-12.CS.5.14
Demonstrate how diverse team collaboration improves the design and development of software products.
9-12.CS.5.15
Compare a variety of programming languages available to solve problems and develop systems.
9-12.CS.5.16
Analyze security issues that might lead to compromised computer programs.
9-12.CS.5.17
Classify and define the different types of software licenses in order to understand how to apply each one to a specific software example.
9-12.CS.5.18
Analyze the notion of intelligent behavior through the programs that learn and adapt, play games, do image recognition, perform text analysis, and control the behavior of robots.
  1. 3.8 Linear Regression
9-12.CS.5.19
Illustrate how mathematical and statistical functions, sets, and logic are used in computation.
  1. 1.5 Series and Central Tendency
  2. 1.6 Measures of Spread
  3. 3.8 Linear Regression
  4. 7.4 Mathematical Operators
  5. 7.9 Logical Operators
9-12.CS.5.20
Describe the concept of parallel processing.
9-12.CS.5.21
Explore issues surrounding mobile computing.
9-12.CS.5.22
Explain the value of heuristic algorithms to approximate solutions for interactable problems.
  1. 3.8 Linear Regression
9-12.CS.5.23
Critically examine algorithms and design an original algorithm (e.g. adapt, remix, improve).
9-12.CS.5.24
Classify problems as tractable, interactable, or computationally unsolvable.