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South Dakota CS Principles Standards Mapping

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AP Computer Science Principles in Python

22 Standards in this Framework 19 Standards Mapped 86% Mapped to Course


Standard Lessons
SD.CSP.1.1 Compare and contrast how abstractions hide the underlying implementation details of computing systems embedded in everyday objects.
  1. 1.8 Abstraction
SD.CSP.1.2 Use concepts to compare levels of abstraction and interactions between application software, system software, and hardware layers.
  1. 1.8 Abstraction
SD.CSP.1.3 Develop and implement guidelines that convey systematic troubleshooting strategies that others can use to identify and fix errors.
  1. 1.7 Commenting Your Code
  2. 1.15 Debugging Strategies
SD.CSP.2.1 Describe the issues that impact network functionality (e.g., bandwidth, load, delay, topology).
  1. 11.1 Welcome to the Internet
  2. 11.2 Internet Hardware
  3. 11.3 Internet Addresses
  4. 11.4 Viewing Websites
  5. 11.5 DNS
  6. 11.6 Routing
  7. 11.7 Packets and Protocols
  8. 11.8 Sequential, Parallel & Distributed Computing
SD.CSP.2.2 Give examples to illustrate how sensitive data can be affected by malware and other attacks.
  1. 11.9 Cybersecurity
SD.CSP.2.3 Recommend security measures to address various scenarios based on the CIA Triad (confidentiality, integrity, and availability).
  1. 8.10 Cryptography
  2. 11.9 Cybersecurity
SD.CSP.2.4 Recommend various security measures, considering tradeoffs between the usability and security of a computing system.
  1. 8.10 Cryptography
  2. 11.9 Cybersecurity
SD.CSP.3.1 Translate between different bit representations of real-world phenomena, such as characters, numbers, and images.
  1. 8.1 Intro to Digital Information
  2. 8.2 Number Systems
  3. 8.3 Encoding Text with Binary
  4. 8.4 Pixel Images
  5. 8.5 Hexadecimal
  6. 8.6 Pixel Colors!
  7. 8.7 Image Manipulation
SD.CSP.3.2 Evaluate the tradeoffs in how data elements are organized and where data is stored.
  1. 7.1 Tuples
  2. 7.2 Lists
  3. 7.3 For Loops and Lists
  4. 7.4 List Methods
  5. 27.1 Classes and Objects
  6. 27.2 Methods
  7. 27.3 Built-In Methods
  8. 27.4 Operator Overloading
  9. 27.5 Class Variables vs. Instance Variables
  10. 27.6 Inheritance
  11. 27.7 Hidden Attributes
  12. 27.8 Namespaces
  13. 27.9 Modules
SD.CSP.3.3 Select and use data collection tools and techniques to generate data sets that support a claim or communicate information.
  1. 13.1 Getting Started with Data
  2. 13.2 Visualizing and Interpreting Data
  3. 13.3 Data Collection & Limitations
SD.CSP.4.1 Use and evaluate algorithms in terms of their efficiency, correctness, and clarity.
SD.CSP.4.2 Compare and contrast fundamental data structures and their uses.
  1. 7.1 Tuples
  2. 7.2 Lists
  3. 7.3 For Loops and Lists
  4. 7.4 List Methods
  5. 27.1 Classes and Objects
  6. 27.9 Modules
SD.CSP.4.3 Recommend specific control structures and identify tradeoffs involving implementation, readability, and program performance.
  1. 4.1 Booleans
  2. 4.2 Logical Operators
  3. 4.3 Comparison Operators
  4. 4.4 If Statements
  5. 4.5 Key Events
  6. 4.6 For Loops in Python
  7. 4.7 General For Loops
  8. 4.10 While Loops
  9. 4.11 Loop and a Half
  10. 28.1 Short Circuit Evaluation
SD.CSP.4.4 Decompose problems into smaller components through systematic analysis, using constructs such as procedures, modules, and/or objects.
  1. 5.1 Functions and Parameters 1
  2. 5.2 Functions and Parameters 2
  3. 5.3 Functions and Parameters 3
  4. 5.4 Functions and Return Values 1
  5. 5.5 Functions and Return Values 2
  6. 27.1 Classes and Objects
  7. 27.9 Modules
SD.CSP.4.5 Construct solutions to problems based on user feedback.
  1. 18.1 Intro to Design Thinking
  2. 18.2 Prototype
  3. 18.3 Test
  4. 18.4 Project Prep and Development
SD.CSP.4.6 Plan and develop programs for broad audiences using a software life cycle process.
  1. 18.1 Intro to Design Thinking
  2. 18.2 Prototype
  3. 18.3 Test
  4. 18.4 Project Prep and Development
SD.CSP.4.7 Investigate and compare multiple programming languages and discuss how their features make them suitable for solving different types of problems.
  1. 3.1 What is Code
  2. 3.2 Uses of Programs
  3. 5.8 Python vs Karel
SD.CSP.5.1 Evaluate the ways computing impacts personal, ethical, social, economic, and cultural practices.
  1. 11.10 The Impact of the Internet
  2. 12.1 The Effects of the Internet
  3. 15.1 The Impacts of Computing
SD.CSP.5.2 Identify and critique bias, equity, access, and influence in existing computer programs.
  1. 11.10 The Impact of the Internet
  2. 12.1 The Effects of the Internet
  3. 15.1 The Impacts of Computing
SD.CSP.5.3 Identify and use tools and methods for collaboration on a project to increase connectivity of people in different cultures and career fields.
SD.CSP.5.4 Debate laws and regulations that impact the development and use of software.
  1. 11.9 Cybersecurity
  2. 11.11 Creative Credit & Copyright
SD.CSP.5.5 Explore careers in computer science.