Computer Science Standards
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Showing 11 - 20 of 21 Standards
Standard Identifier: 6-8.NI.6
Grade Range:
6–8
Concept:
Networks & the Internet
Subconcept:
Cybersecurity
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Apply multiple methods of information protection to model the secure transmission of information.
Descriptive Statement:
Digital information is protected using a variety of cryptographic techniques. Cryptography is essential to many models of cybersecurity. At its core, cryptography has a mathematical foundation. Cryptographic encryption can be as simple as letter substitution or as complicated as modern methods used to secure networks and the Internet. Students encode and decode messages using encryption methods, and explore different levels of complexity used to hide or secure information. For example, students could identify methods of secret communication used during the Revolutionary War (e.g., ciphers, secret codes, invisible ink, hidden letters) and then secure their own methods such as substitution ciphers or steganography (i.e., hiding messages inside a picture or other data) to compose a message from either the Continental Army or British Army. (HSS.8.1) Alternatively, students could explore functions and inverse functions for encryption and decryption and consider functions that are complex enough to keep data secure from their peers. (CA CCSS for Mathematics 8.F.1)
Apply multiple methods of information protection to model the secure transmission of information.
Descriptive Statement:
Digital information is protected using a variety of cryptographic techniques. Cryptography is essential to many models of cybersecurity. At its core, cryptography has a mathematical foundation. Cryptographic encryption can be as simple as letter substitution or as complicated as modern methods used to secure networks and the Internet. Students encode and decode messages using encryption methods, and explore different levels of complexity used to hide or secure information. For example, students could identify methods of secret communication used during the Revolutionary War (e.g., ciphers, secret codes, invisible ink, hidden letters) and then secure their own methods such as substitution ciphers or steganography (i.e., hiding messages inside a picture or other data) to compose a message from either the Continental Army or British Army. (HSS.8.1) Alternatively, students could explore functions and inverse functions for encryption and decryption and consider functions that are complex enough to keep data secure from their peers. (CA CCSS for Mathematics 8.F.1)
Standard Identifier: 9-12.AP.12
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.1)
Standard:
Design algorithms to solve computational problems using a combination of original and existing algorithms.
Descriptive Statement:
Knowledge of common algorithms improves how people develop software, secure data, and store information. Some algorithms may be easier to implement in a particular programming language, work faster, require less memory to store data, and be applicable in a wider variety of situations than other algorithms. Algorithms used to search and sort data are common in a variety of software applications. For example, students could design an algorithm to calculate and display various sports statistics and use common sorting or mathematical algorithms (e.g., average) in the design of the overall algorithm. Alternatively, students could design an algorithm to implement a game and use existing randomization algorithms to place pieces randomly in starting positions or to control the "roll" of a dice or selection of a "card" from a deck.
Design algorithms to solve computational problems using a combination of original and existing algorithms.
Descriptive Statement:
Knowledge of common algorithms improves how people develop software, secure data, and store information. Some algorithms may be easier to implement in a particular programming language, work faster, require less memory to store data, and be applicable in a wider variety of situations than other algorithms. Algorithms used to search and sort data are common in a variety of software applications. For example, students could design an algorithm to calculate and display various sports statistics and use common sorting or mathematical algorithms (e.g., average) in the design of the overall algorithm. Alternatively, students could design an algorithm to implement a game and use existing randomization algorithms to place pieces randomly in starting positions or to control the "roll" of a dice or selection of a "card" from a deck.
Standard Identifier: 9-12.DA.11
Grade Range:
9–12
Concept:
Data & Analysis
Subconcept:
Inference & Models
Practice(s):
Developing and Using Abstractions, Testing and Refining Computational Artifacts (4.4, 6.3)
Standard:
Refine computational models to better represent the relationships among different elements of data collected from a phenomenon or process.
Descriptive Statement:
Computational models are used to make predictions about processes or phenomena based on selected data and features. They allow people to investigate the relationships among different variables to understand a system. Predictions are tested to validate models. Students evaluate these models against real-world observations. For example, students could use a population model that allows them to speculate about interactions among different species, evaluate the model based on data gathered from nature, and then refine the model to reflect more complex and realistic interactions.
Refine computational models to better represent the relationships among different elements of data collected from a phenomenon or process.
Descriptive Statement:
Computational models are used to make predictions about processes or phenomena based on selected data and features. They allow people to investigate the relationships among different variables to understand a system. Predictions are tested to validate models. Students evaluate these models against real-world observations. For example, students could use a population model that allows them to speculate about interactions among different species, evaluate the model based on data gathered from nature, and then refine the model to reflect more complex and realistic interactions.
Standard Identifier: 9-12.NI.7
Grade Range:
9–12
Concept:
Networks & the Internet
Subconcept:
Cybersecurity
Practice(s):
Recognizing and Defining Computational Problems, Developing and Using Abstractions (3.3, 4.4)
Standard:
Compare and contrast cryptographic techniques to model the secure transmission of information.
Descriptive Statement:
Cryptography is a technique for transforming information on a computer in such a way that it becomes unreadable by anyone except authorized parties. Cryptography is useful for supporting secure communication of data across networks. Examples of cryptographic methods include hashing, symmetric encryption/decryption (private key), and assymmetric encryption/decryption (public key/private key). Students use software to encode and decode messages using cryptographic methods. Students compare the costs and benefits of using various cryptographic methods. At this level, students are not expected to perform the mathematical calculations associated with encryption and decryption. For example, students could compare and contrast multiple examples of symmetric cryptographic techiques. Alternatively, students could compare and contrast symmetric and asymmetric cryptographic techniques in which they apply for a given scenario.
Compare and contrast cryptographic techniques to model the secure transmission of information.
Descriptive Statement:
Cryptography is a technique for transforming information on a computer in such a way that it becomes unreadable by anyone except authorized parties. Cryptography is useful for supporting secure communication of data across networks. Examples of cryptographic methods include hashing, symmetric encryption/decryption (private key), and assymmetric encryption/decryption (public key/private key). Students use software to encode and decode messages using cryptographic methods. Students compare the costs and benefits of using various cryptographic methods. At this level, students are not expected to perform the mathematical calculations associated with encryption and decryption. For example, students could compare and contrast multiple examples of symmetric cryptographic techiques. Alternatively, students could compare and contrast symmetric and asymmetric cryptographic techniques in which they apply for a given scenario.
Standard Identifier: 9-12S.AP.10
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Recognizing and Defining Computational Problems, Communicating About Computing (3.1, 7.2)
Standard:
Describe how artificial intelligence drives many software and physical systems.
Descriptive Statement:
Artificial intelligence is a sub-discipline of computer science that enables computers to solve problems previously handled by biological systems. There are many applications of artificial intelligence, including computer vision and speech recognition. Students research and explain how artificial intelligence has been employed in a given system. Students are not expected to implement an artificially intelligent system in order to meet this standard. For example, students could observe an artificially intelligent system and notice where its behavior is not human-like, such as when a character in a videogame makes a mistake that a human is unlikely to make, or when a computer easily beats even the best human players at a given game. Alternatively, students could interact with a search engine asking various questions, and after reading articles on the topic, they could explain how the computer is able to respond to queries.
Describe how artificial intelligence drives many software and physical systems.
Descriptive Statement:
Artificial intelligence is a sub-discipline of computer science that enables computers to solve problems previously handled by biological systems. There are many applications of artificial intelligence, including computer vision and speech recognition. Students research and explain how artificial intelligence has been employed in a given system. Students are not expected to implement an artificially intelligent system in order to meet this standard. For example, students could observe an artificially intelligent system and notice where its behavior is not human-like, such as when a character in a videogame makes a mistake that a human is unlikely to make, or when a computer easily beats even the best human players at a given game. Alternatively, students could interact with a search engine asking various questions, and after reading articles on the topic, they could explain how the computer is able to respond to queries.
Standard Identifier: 9-12S.AP.11
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Recognizing and Defining Computational Problems, Creating Computational Artifacts (3.1, 5.3)
Standard:
Implement an algorithm that uses artificial intelligence to overcome a simple challenge.
Descriptive Statement:
Artificial intelligence algorithms allow a computer to perceive and move in the world, use knowledge, and engage in problem solving. Students create a computational artifact that is able to carry out a simple task commonly performed by living organisms. Students do not need to realistically simulate human behavior or solve a complex problem in order to meet this standard. For example, students could implement an algorithm for playing tic-tac-toe that would select an appropriate location for the next move. Alternatively, students could implement an algorithm that allows a solar-powered robot to move to a sunny location when its batteries are low.
Implement an algorithm that uses artificial intelligence to overcome a simple challenge.
Descriptive Statement:
Artificial intelligence algorithms allow a computer to perceive and move in the world, use knowledge, and engage in problem solving. Students create a computational artifact that is able to carry out a simple task commonly performed by living organisms. Students do not need to realistically simulate human behavior or solve a complex problem in order to meet this standard. For example, students could implement an algorithm for playing tic-tac-toe that would select an appropriate location for the next move. Alternatively, students could implement an algorithm that allows a solar-powered robot to move to a sunny location when its batteries are low.
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.AP.13
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Recognizing and Defining Computational Problems (3.3)
Standard:
Evaluate algorithms in terms of their efficiency.
Descriptive Statement:
Algorithms that perform the same task can be implemented in different ways, which take different amounts of time to run on a given input set. Algorithms are commonly evaluated using asymptotic analysis (i.e., “Big O”) which involves exploration of behavior when the input set grows very large. Students classify algorithms by the most common time classes (e.g., log n, linear, n log n, and quadratic or higher). For example, students could read a given algorithm, identify the control constructs, and in conjunction with input size, identify the efficiency class of the algorithm.
Evaluate algorithms in terms of their efficiency.
Descriptive Statement:
Algorithms that perform the same task can be implemented in different ways, which take different amounts of time to run on a given input set. Algorithms are commonly evaluated using asymptotic analysis (i.e., “Big O”) which involves exploration of behavior when the input set grows very large. Students classify algorithms by the most common time classes (e.g., log n, linear, n log n, and quadratic or higher). For example, students could read a given algorithm, identify the control constructs, and in conjunction with input size, identify the efficiency class of the algorithm.
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.
Showing 11 - 20 of 21 Standards
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