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Standards Mapping

for Certiport Computational Thinking

61

Standards in this Framework

30

Standards Mapped

49%

Mapped to Course

Standard Lessons
1.1.1
Understand and recognize structured and unstructured data
1.1.2
Understand and recognize different types of data such as text, numeric, date/time, image, and audio
  1. 3.2 Variables and Types
  2. 28.3 Variables and Types
1.1.3
Understand and recognize data encoding (ascii, binary, character mapping)
1.2.1
Recognize and apply Boolean and logical operators
  1. 5.1 Booleans
  2. 5.4 Logical Operators
1.2.2
Recognize and apply inductive reasoning
  1. 2.5 Top Down Design and Decomposition in Karel
  2. 2.14 Debugging Strategies
  3. 2.15 Algorithms
  4. 3.2 Variables and Types
  5. 5.4 Logical Operators
  6. 28.3 Variables and Types
1.2.3
Recognize ambiguity in a logical reasoning problem
  1. 2.7 Abstraction
1.2.4
Recognize and apply deductive reasoning
  1. 5.1 Booleans
  2. 5.2 If Statements
  3. 5.3 Comparison Operators
  4. 5.4 Logical Operators
  5. 5.5 Floating Point Numbers and Rounding
1.3.1
Explain the purpose of algorithmic thinking
1.3.2
Understand the purpose of abstraction and model building
  1. 2.7 Abstraction
1.3.3
Understand the purpose and capabilities of automation
2.1.1
Identify the data needed to solve a problem
  1. 13.4 Dictionaries
  2. 28.21 Dictionaries
2.1.2
Assess relevance of existing data sets
2.1.3
Determine the gap between existing data and data needs
2.2.1
Understand validity
2.2.2
Understand reliability
2.2.3
Explain data cleaning in data sets
2.3.1
Collect relevant data using existing data sources
2.3.2
Select appropriate tools to gather, analyze, and process data
2.3.3
Retrieve information from a data source, such as a list, a table, an infographic, etc.
  1. 12.1 Tuples
  2. 12.2 Lists
  3. 12.3 For Loops and Lists
  4. 12.4 List Methods
  5. 13.1 2d Lists
  6. 13.4 Dictionaries
  7. 28.17 For Loops and Lists
  8. 28.19 2d Lists
  9. 28.21 Dictionaries
2.3.4
Choose a method for creating original data sets such as an observation or a survey
2.3.5
Use input-validation methods
2.3.6
Explain the legal and ethical dimensions of data collection
3.1.1
Identify patterns in data
3.1.2
Organize data using models such as tables, charts, and graphs
3.1.3
Sort and filter data by relevant criteria
3.1.4
Identify similarities, differences, and subsets in a data set
3.1.5
Make predictions by examining patterns
3.2.1
Recognize an abstract representation, such as a model, variable, function, or procedure
3.2.2
Create an abstract model to understand complex systems or facilitate problem solving
3.2.3
Interpret a process flow diagram
4.1.1
Identify an appropriate problem statement based on information provided
4.1.2
Define the scope and limitations of a problem
  1. 4.1 Project: Mad Libs
  2. 6.1 Project: Quiz Game
  3. 8.1 Project: Password Authenticator
  4. 11.1 Project: The Game of Pig
  5. 14.1 Project: Guess the Word
4.1.3
Identify decision makers, collaborators, and target audience
4.1.4
Break down a problem into component parts by using decomposition
  1. 2.5 Top Down Design and Decomposition in Karel
4.2.1
Select a design process, such as iterative or incremental
  1. 7.1 While Loops
  2. 7.2 For Loops
  3. 7.3 Break and Continue
  4. 7.4 Nested Control Structures
  5. 28.10 For Loops
4.2.2
Identify prerequisites for a solution
  1. 4.1 Project: Mad Libs
  2. 6.1 Project: Quiz Game
  3. 8.1 Project: Password Authenticator
  4. 11.1 Project: The Game of Pig
  5. 14.1 Project: Guess the Word
4.2.3
Identify the possible outcomes of a solution
  1. 4.1 Project: Mad Libs
  2. 6.1 Project: Quiz Game
  3. 8.1 Project: Password Authenticator
  4. 11.1 Project: The Game of Pig
  5. 14.1 Project: Guess the Word
4.2.4
Choose appropriate tools to develop a solution, such as flow charts, spreadsheets, pseudocode, surveys
5.1.1
Create a sequence of steps
  1. 2.2 More Basic Karel
  2. 2.3 Karel Can't Turn Right
  3. 2.4 Functions in Karel
5.1.2
Evaluate the outcome of a sequence of steps
  1. 2.2 More Basic Karel
  2. 2.3 Karel Can't Turn Right
  3. 2.4 Functions in Karel
  4. 3.3 User Input
5.1.3
Recognize when to combine steps into reusable procedures and functions
  1. 2.4 Functions in Karel
  2. 2.5 Top Down Design and Decomposition in Karel
  3. 9.1 Functions
5.2.1
Recognize when to use iteration
  1. 7.1 While Loops
  2. 7.2 For Loops
  3. 7.3 Break and Continue
  4. 7.4 Nested Control Structures
  5. 28.10 For Loops
5.2.2
Recognize when to use nested loops
  1. 7.4 Nested Control Structures
5.2.3
Determine the outcome of an algorithm that uses iteration
  1. 7.1 While Loops
  2. 7.2 For Loops
  3. 7.3 Break and Continue
  4. 7.4 Nested Control Structures
  5. 28.10 For Loops
5.2.4
Create an algorithm that uses iteration
  1. 7.1 While Loops
  2. 7.2 For Loops
  3. 7.3 Break and Continue
  4. 7.4 Nested Control Structures
  5. 28.10 For Loops
5.3.1
Recognize when to use selection statements
  1. 5.2 If Statements
  2. 5.3 Comparison Operators
  3. 5.4 Logical Operators
5.3.2
Recognize when to use nesting in selection statements
  1. 7.4 Nested Control Structures
5.3.3
Determine the outcome of an algorithm that uses selection statements
  1. 5.2 If Statements
  2. 5.3 Comparison Operators
  3. 5.4 Logical Operators
5.3.4
Create an algorithm that uses selection statements
  1. 5.2 If Statements
  2. 5.3 Comparison Operators
  3. 5.4 Logical Operators
5.4.1
Recognize when to use variables
  1. 3.2 Variables and Types
  2. 28.3 Variables and Types
5.4.2
Determine the outcome of an algorithm that uses variables
  1. 3.2 Variables and Types
  2. 28.3 Variables and Types
5.4.3
Create an algorithm that uses variables
  1. 3.2 Variables and Types
  2. 28.3 Variables and Types
6.1.1
Choose an effective medium for communicating a solution to a target audience
  1. 16.1 Software Engineer
  2. 16.2 QA Engineer
  3. 16.3 Designer
  4. 16.4 Project Manager
6.1.2
Create an original computational artifact to communicate a solution to a target audience
  1. 8.1 Project: Password Authenticator
6.2.1
Interpret a design for a computational artifact
  1. 16.3 Designer
6.2.2
Critique and provide feedback on a design for a computational artifact
6.2.3
Incorporate collaborative feedback into a computational artifact
6.3.1
Create a prototype to evaluate the effectiveness of an automated solution
6.3.2
Compare the efficiency of multiple possible solutions
6.3.3
Troubleshoot an automated solution
6.3.4
Use iterative testing to improve an automated solution