Computer Science Standards
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Showing 41 - 44 of 44 Standards
Standard Identifier: 9-12S.AP.26
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Communicating About Computing (7.2)
Standard:
Compare multiple programming languages, and discuss how their features make them suitable for solving different types of problems.
Descriptive Statement:
Particular problems may be more effectively solved using some programming languages than other programming languages. Students provide a rationale for why a specific programming language is better suited for a solving a particular class of problem. For example, students could explain how a language with a large library base can make developing a web application easier. Alternatively, students could explain how languages that support particular programming paradigms (e.g., object-oriented or functional) can make implementation more aligned with design choices. Additionally, students could discuss how languages that implement garbage collection are good for simplicity of memory management, but may result in poor performance characteristics.
Compare multiple programming languages, and discuss how their features make them suitable for solving different types of problems.
Descriptive Statement:
Particular problems may be more effectively solved using some programming languages than other programming languages. Students provide a rationale for why a specific programming language is better suited for a solving a particular class of problem. For example, students could explain how a language with a large library base can make developing a web application easier. Alternatively, students could explain how languages that support particular programming paradigms (e.g., object-oriented or functional) can make implementation more aligned with design choices. Additionally, students could discuss how languages that implement garbage collection are good for simplicity of memory management, but may result in poor performance characteristics.
Standard Identifier: 9-12S.CS.2
Grade Range:
9–12 Specialty
Concept:
Computing Systems
Subconcept:
Hardware & Software
Practice(s):
Communicating About Computing (7.2)
Standard:
Categorize and describe the different functions of operating system software.
Descriptive Statement:
Operating systems (OS) software is the code that manages the computer’s basic functions. Students describe at a high level the different functions of different components of operating system software. Examples of functions could include memory management, data storage/retrieval, processes management, and access control. For example, students could use monitoring tools including within an OS to inspect the services and functions running on a system and create an artifact to describe the activity that they observed (e.g., when a browser is running with many tabs open, memory usage is increased). They could also inspect and describe changes in the activity monitor that occur as different applications are executing (e.g., processor utilization increases when a new application is launched).
Categorize and describe the different functions of operating system software.
Descriptive Statement:
Operating systems (OS) software is the code that manages the computer’s basic functions. Students describe at a high level the different functions of different components of operating system software. Examples of functions could include memory management, data storage/retrieval, processes management, and access control. For example, students could use monitoring tools including within an OS to inspect the services and functions running on a system and create an artifact to describe the activity that they observed (e.g., when a browser is running with many tabs open, memory usage is increased). They could also inspect and describe changes in the activity monitor that occur as different applications are executing (e.g., processor utilization increases when a new application is launched).
Standard Identifier: 9-12S.DA.7
Grade Range:
9–12 Specialty
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Communicating About Computing (7.1)
Standard:
Select and use data collection tools and techniques to generate data sets.
Descriptive Statement:
Data collection and organization is essential for obtaining new information insights and revealing new knowledge in our modern world. As computers are able to process larger sets of data, gathering data in an efficient and reliable matter remains important. The choice of data collection tools and quality of the data collected influences how new information, insights, and knowledge will support claims and be communicated. Students devise a reliable method to gather information, use software to extract digital data from data sets, and clean and organize the data in ways that support summaries of information obtained from the data. At this level, students may, but are not required to, create their own data collection tools. For example, students could create a computational artifact that records information from a sonic distance sensor to monitor the motion of a prototype vehicle. Alternatively, students could develop a reliable and practical way to automatically digitally record the number of animals entering a portion of a field to graze. Additionally, students could also find a web site containing data (e.g., race results for a major marathon), scrape the data from the web site using data collection tools, and format the data so it can be analyzed.
Select and use data collection tools and techniques to generate data sets.
Descriptive Statement:
Data collection and organization is essential for obtaining new information insights and revealing new knowledge in our modern world. As computers are able to process larger sets of data, gathering data in an efficient and reliable matter remains important. The choice of data collection tools and quality of the data collected influences how new information, insights, and knowledge will support claims and be communicated. Students devise a reliable method to gather information, use software to extract digital data from data sets, and clean and organize the data in ways that support summaries of information obtained from the data. At this level, students may, but are not required to, create their own data collection tools. For example, students could create a computational artifact that records information from a sonic distance sensor to monitor the motion of a prototype vehicle. Alternatively, students could develop a reliable and practical way to automatically digitally record the number of animals entering a portion of a field to graze. Additionally, students could also find a web site containing data (e.g., race results for a major marathon), scrape the data from the web site using data collection tools, and format the data so it can be analyzed.
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 41 - 44 of 44 Standards
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