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Kentucky Computational Thinking Standards Mapping

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AP Computer Science Principles in Python

12 Standards in this Framework 11 Standards Mapped 91% Mapped to Course


Standard Lessons
1 Demonstrate an understanding of elementary logic, truth tables, and Boolean algebra.
  1. 4.1 Booleans
  2. 4.2 Logical Operators
  3. 4.3 Comparison Operators
  4. 28.1 Short Circuit Evaluation
  5. 28.2 De Morgan's Laws
2 Demonstrate programming style best practices.
  1. 1.6 Top Down Design and Decomposition in Karel
  2. 1.7 Commenting Your Code
  3. 1.15 Debugging Strategies
  4. 18.1 Intro to Design Thinking
  5. 18.2 Prototype
  6. 18.3 Test
  7. 18.4 Project Prep and Development
3 Illustrate the flow of a program.
  1. 18.1 Intro to Design Thinking
  2. 18.2 Prototype
  3. 18.3 Test
  4. 18.4 Project Prep and Development
  5. 31.1 Practice PT: Testing 1, 2, 3 ...
  6. 32.1 Practice PT: The Shopping List
4 Illustrate concepts using one or more programming languages
  1. 3.1 What is Code
  2. 3.2 Uses of Programs
  3. 5.7 Python vs Karel
5 Explain the implications of file processing.
  1. 13.1 Getting Started with Data
  2. 13.2 Visualizing and Interpreting Data
  3. 13.3 Data Collection & Limitations
6 Describe the steps addressed in the design of a program to solve the state problem.
  1. 30.1 Let's Build Mastermind
  2. 31.1 Practice PT: Testing 1, 2, 3 ...
  3. 32.1 Practice PT: The Shopping List
7 Explain how algorithms are used to produce artificial intelligences(AI)
8 Describe the principles of object-oriented programming.
  1. 27.1 Classes and Objects
  2. 27.2 Methods
  3. 27.3 Built-In Methods
  4. 27.4 Operator Overloading
  5. 27.5 Class Variables vs. Instance Variables
  6. 27.6 Inheritance
  7. 27.7 Hidden Attributes
  8. 27.8 Namespaces
  9. 27.9 Modules
9 Develop algorithms with increasing degree of complexity using structured programming techniques such as: sequence, selection, and repetition.
  1. 1.10 For Loops
  2. 1.11 If Statements
  3. 1.12 If/Else Statements
  4. 1.13 While Loops in Karel
  5. 4.4 If Statements
  6. 4.5 Key Events
  7. 4.6 For Loops in Python
  8. 4.7 General For Loops
  9. 4.8 For Loop Practice
  10. 4.10 While Loops
  11. 4.11 Loop and a Half
  12. 28.1 Short Circuit Evaluation
  13. 28.2 De Morgan's Laws
10 Use fundamental data types and data structures such as: integers, reals, characters, strings, Booleans, one - and two - dimensional arrays.
  1. 3.4 Variables
  2. 7.1 Tuples
  3. 7.2 Lists
  4. 7.3 For Loops and Lists
  5. 7.4 List Methods
  6. 33.1 Indexing
  7. 33.2 Slicing
  8. 33.3 Immutability
  9. 33.4 Strings and For Loops
  10. 33.6 String Methods
11 Analyze the binary representation of data.
  1. 8.1 Intro to Digital Information
  2. 8.2 Number Systems
  3. 8.3 Encoding Text with Binary
12 Use modular programming.
  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. 5.6 Local Variables and Scope
  7. 27.1 Classes and Objects
  8. 27.2 Methods
  9. 27.3 Built-In Methods
  10. 27.4 Operator Overloading
  11. 27.5 Class Variables vs. Instance Variables
  12. 27.6 Inheritance
  13. 27.7 Hidden Attributes
  14. 27.9 Modules