Computer Science Standards
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Showing 11 - 12 of 12 Standards
Standard Identifier: 9-12S.AP.12
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.2)
Standard:
Implement searching and sorting algorithms to solve computational problems.
Descriptive Statement:
One of the core uses of computers is to store, organize, and retrieve information when working with large amounts of data. Students create computational artifacts that use searching and/or sorting algorithms to retrieve, organize, or store information. Students do not need to select their algorithm based on efficiency. For example, students could write a script to sequence their classmates in order from youngest to oldest. Alternatively, students could write a program to find certain words within a text and report their location.
Implement searching and sorting algorithms to solve computational problems.
Descriptive Statement:
One of the core uses of computers is to store, organize, and retrieve information when working with large amounts of data. Students create computational artifacts that use searching and/or sorting algorithms to retrieve, organize, or store information. Students do not need to select their algorithm based on efficiency. For example, students could write a script to sequence their classmates in order from youngest to oldest. Alternatively, students could write a program to find certain words within a text and report their location.
Standard Identifier: 9-12S.DA.8
Grade Range:
9–12 Specialty
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Developing and Using Abstractions, Communicating About Computing (4.1, 7.1)
Standard:
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.
Showing 11 - 12 of 12 Standards
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