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Standards Framework

for Certiport Computational Thinking

61

Standards in this Framework

Standard Description
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
1.1.3 Understand and recognize data encoding (ascii, binary, character mapping)
1.2.1 Recognize and apply Boolean and logical operators
1.2.2 Recognize and apply inductive reasoning
1.2.3 Recognize ambiguity in a logical reasoning problem
1.2.4 Recognize and apply deductive reasoning
1.3.1 Explain the purpose of algorithmic thinking
1.3.2 Understand the purpose of abstraction and model building
1.3.3 Understand the purpose and capabilities of automation
2.1.1 Identify the data needed to solve a problem
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.
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
4.1.3 Identify decision makers, collaborators, and target audience
4.1.4 Break down a problem into component parts by using decomposition
4.2.1 Select a design process, such as iterative or incremental
4.2.2 Identify prerequisites for a solution
4.2.3 Identify the possible outcomes of a solution
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
5.1.2 Evaluate the outcome of a sequence of steps
5.1.3 Recognize when to combine steps into reusable procedures and functions
5.2.1 Recognize when to use iteration
5.2.2 Recognize when to use nested loops
5.2.3 Determine the outcome of an algorithm that uses iteration
5.2.4 Create an algorithm that uses iteration
5.3.1 Recognize when to use selection statements
5.3.2 Recognize when to use nesting in selection statements
5.3.3 Determine the outcome of an algorithm that uses selection statements
5.3.4 Create an algorithm that uses selection statements
5.4.1 Recognize when to use variables
5.4.2 Determine the outcome of an algorithm that uses variables
5.4.3 Create an algorithm that uses variables
6.1.1 Choose an effective medium for communicating a solution to a target audience
6.1.2 Create an original computational artifact to communicate a solution to a target audience
6.2.1 Interpret a design for a computational artifact
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