Computer Science Standards
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Algorithms
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Collection, Visualization, & Transformation
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Control
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Network Communication & Organization
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Variables
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Showing 31 - 37 of 37 Standards
Standard Identifier: 9-12S.AP.14
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Variables
Practice(s):
Developing and Using Abstractions (4.2)
Standard:
Compare and contrast fundamental data structures and their uses.
Descriptive Statement:
Data structures are designed to provide different ways of storing and manipulating data sets to optimize various aspects of storage or runtime performance. Choice of data structures is made based on expected data characteristics and expected program functions. Students = compare and contrast how basic functions (e.g.., insertion, deletion, and modification) would differ for common data structures including lists, arrays, stacks, and queues. For example, students could draw a diagram of how different data structures change when items are added, deleted, or modified. They could explain tradeoffs in storage and efficiency issues. Alternatively, when presented with a description of a program and the functions it would be most likely to be running, students could list pros and cons for a specific data structure use in that scenario.
Compare and contrast fundamental data structures and their uses.
Descriptive Statement:
Data structures are designed to provide different ways of storing and manipulating data sets to optimize various aspects of storage or runtime performance. Choice of data structures is made based on expected data characteristics and expected program functions. Students = compare and contrast how basic functions (e.g.., insertion, deletion, and modification) would differ for common data structures including lists, arrays, stacks, and queues. For example, students could draw a diagram of how different data structures change when items are added, deleted, or modified. They could explain tradeoffs in storage and efficiency issues. Alternatively, when presented with a description of a program and the functions it would be most likely to be running, students could list pros and cons for a specific data structure use in that scenario.
Standard Identifier: 9-12S.AP.15
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Control
Practice(s):
Recognizing and Defining Computational Problems, Communicating About Computing (3.2, 7.2)
Standard:
Demonstrate the flow of execution of a recursive algorithm.
Descriptive Statement:
Recursion is a powerful problem-solving approach where the problem solution is built on solutions of smaller instances of the same problem. A base case, which returns a result without referencing itself, must be defined, otherwise infinite recursion will occur. Students represent a sequence of calls to a recursive algorithm and show how the process resolves to a solution. For example, students could draw a diagram to illustrate flow of execution by keeping track of parameter and returned values for each recursive call. Alternatively, students could create a video showing the passing of arguments as the recursive algorithm runs.
Demonstrate the flow of execution of a recursive algorithm.
Descriptive Statement:
Recursion is a powerful problem-solving approach where the problem solution is built on solutions of smaller instances of the same problem. A base case, which returns a result without referencing itself, must be defined, otherwise infinite recursion will occur. Students represent a sequence of calls to a recursive algorithm and show how the process resolves to a solution. For example, students could draw a diagram to illustrate flow of execution by keeping track of parameter and returned values for each recursive call. Alternatively, students could create a video showing the passing of arguments as the recursive algorithm runs.
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.
Standard Identifier: 9-12S.DA.9
Grade Range:
9–12 Specialty
Concept:
Data & Analysis
Subconcept:
Inference & Models
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
Descriptive Statement:
A model could be implemented as a diagram or a program that represents key properties of a physical or other system. A simulation is based on a model, and enables observation of the system as key properties change. Students explore, explain, and evaluate existing models and simulations, in order to support the refinement of hypotheses about how the systems work. At this level, the ability to accurately and completely model and simulate complex systems is not expected. For example, a computer model of ants following a path created by other ants who found food explains the trail-like travel patterns of the insect. Students could evaluate if the output of the model fits well with their hypothesis that ants navigate the world through the use of pheromones. They could explain how the computer model supports this hypothesis and how it might leave out certain aspects of ant behavior and whether these are important to understanding ant travel behavior. Alternatively, students could hypothesize how different ground characteristics (e.g., soil type, thickness of sediment above bedrock) relate to the severity of shaking at the surface during an earthquake. They could add or modify input about ground characteristics into an earthquake simulator, observe the changed simulation output, and then evaluate their hypotheses.
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
Descriptive Statement:
A model could be implemented as a diagram or a program that represents key properties of a physical or other system. A simulation is based on a model, and enables observation of the system as key properties change. Students explore, explain, and evaluate existing models and simulations, in order to support the refinement of hypotheses about how the systems work. At this level, the ability to accurately and completely model and simulate complex systems is not expected. For example, a computer model of ants following a path created by other ants who found food explains the trail-like travel patterns of the insect. Students could evaluate if the output of the model fits well with their hypothesis that ants navigate the world through the use of pheromones. They could explain how the computer model supports this hypothesis and how it might leave out certain aspects of ant behavior and whether these are important to understanding ant travel behavior. Alternatively, students could hypothesize how different ground characteristics (e.g., soil type, thickness of sediment above bedrock) relate to the severity of shaking at the surface during an earthquake. They could add or modify input about ground characteristics into an earthquake simulator, observe the changed simulation output, and then evaluate their hypotheses.
Standard Identifier: 9-12S.NI.3
Grade Range:
9–12 Specialty
Concept:
Networks & the Internet
Subconcept:
Network Communication & Organization
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Examine the scalability and reliability of networks, by describing the relationship between routers, switches, servers, topology, and addressing.
Descriptive Statement:
Choice of network topology is determined, in part, by how many devices can be supported and the character of communication needs between devices. Each device is assigned an address that uniquely identifies it on the network. Routers function by comparing addresses to determine how information on the network should reach its desgination. Switches compare addresses to determine which computers will receive information. Students explore and explain how network performance degrades when various factors affect the network. For example, students could use online network simulators to describe how network performance changes when the number of devices increases. Alternatively, students could visualize and describe changes to the distribution of network traffic when a router on the network fails.
Examine the scalability and reliability of networks, by describing the relationship between routers, switches, servers, topology, and addressing.
Descriptive Statement:
Choice of network topology is determined, in part, by how many devices can be supported and the character of communication needs between devices. Each device is assigned an address that uniquely identifies it on the network. Routers function by comparing addresses to determine how information on the network should reach its desgination. Switches compare addresses to determine which computers will receive information. Students explore and explain how network performance degrades when various factors affect the network. For example, students could use online network simulators to describe how network performance changes when the number of devices increases. Alternatively, students could visualize and describe changes to the distribution of network traffic when a router on the network fails.
Standard Identifier: 9-12S.NI.4
Grade Range:
9–12 Specialty
Concept:
Networks & the Internet
Subconcept:
Network Communication & Organization
Practice(s):
Communicating About Computing (7.2)
Standard:
Explain how the characteristics of the Internet influence the systems developed on it.
Descriptive Statement:
The design of the Internet includes hierarchy and redundancy to help it scale reliably. An end-to-end architecture means that key functions are placed at endpoints in the network (i.e., an Internet user's computer and the server hosting a website) rather than in the middle of the network. Open standards for transmitting information across the Internet help fuel its growth. This design philosophy impacts systems and technologies that integrate with the Internet. Students explain how Internet-based systems depend on these characteristics. For example, students could explain how having common, standard protocols enable products and services from different developers to communicate. Alternatively, students could describe how the end-to-end architecture and redundancy in routing enables Internet users to access information and services even if part of the network is down; the information can still be routed from one end to another through a different path.
Explain how the characteristics of the Internet influence the systems developed on it.
Descriptive Statement:
The design of the Internet includes hierarchy and redundancy to help it scale reliably. An end-to-end architecture means that key functions are placed at endpoints in the network (i.e., an Internet user's computer and the server hosting a website) rather than in the middle of the network. Open standards for transmitting information across the Internet help fuel its growth. This design philosophy impacts systems and technologies that integrate with the Internet. Students explain how Internet-based systems depend on these characteristics. For example, students could explain how having common, standard protocols enable products and services from different developers to communicate. Alternatively, students could describe how the end-to-end architecture and redundancy in routing enables Internet users to access information and services even if part of the network is down; the information can still be routed from one end to another through a different path.
Showing 31 - 37 of 37 Standards
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