Computer Science Standards
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Showing 11 - 20 of 23 Standards
Standard Identifier: 6-8.CS.2
Grade Range:
6–8
Concept:
Computing Systems
Subconcept:
Hardware & Software
Practice(s):
Creating Computational Artifacts (5.1)
Standard:
Design a project that combines hardware and software components to collect and exchange data.
Descriptive Statement:
Collecting and exchanging data involves input, output, storage, and processing. When possible, students select the components for their project designs by considering tradeoffs between factors such as functionality, cost, size, speed, accessibility, and aesthetics. Students do not need to implement their project design in order to meet this standard. For example, students could design a mobile tour app that displays information relevant to specific locations when the device is nearby or when the user selects a virtual stop on the tour. They select appropriate components, such as GPS or cellular-based geolocation tools, textual input, and speech recognition, to use in their project design. Alternatively, students could design a project that uses a sensor to collect the salinity, moisture, and temperature of soil. They may select a sensor that connects wirelessly through a Bluetooth connection because it supports greater mobility, or they could instead select a physical USB connection that does not require a separate power source. (CA NGSS: MS-ETS1-1, MS-ETS1-2)
Design a project that combines hardware and software components to collect and exchange data.
Descriptive Statement:
Collecting and exchanging data involves input, output, storage, and processing. When possible, students select the components for their project designs by considering tradeoffs between factors such as functionality, cost, size, speed, accessibility, and aesthetics. Students do not need to implement their project design in order to meet this standard. For example, students could design a mobile tour app that displays information relevant to specific locations when the device is nearby or when the user selects a virtual stop on the tour. They select appropriate components, such as GPS or cellular-based geolocation tools, textual input, and speech recognition, to use in their project design. Alternatively, students could design a project that uses a sensor to collect the salinity, moisture, and temperature of soil. They may select a sensor that connects wirelessly through a Bluetooth connection because it supports greater mobility, or they could instead select a physical USB connection that does not require a separate power source. (CA NGSS: MS-ETS1-1, MS-ETS1-2)
Standard Identifier: 6-8.DA.9
Grade Range:
6–8
Concept:
Data & Analysis
Subconcept:
Inference & Models
Practice(s):
Developing and Using Abstractions, Testing and Refining Computational Artifacts (4.4, 6.1)
Standard:
Test and analyze the effects of changing variables while using computational models.
Descriptive Statement:
Variables within a computational model may be changed, in order to alter a computer simulation or to more accurately represent how various data is related. Students interact with a given model, make changes to identified model variables, and observe and reflect upon the results. For example, students could test a program that makes a robot move on a track by making changes to variables (e.g., height and angle of track, size and mass of the robot) and discussing how these changes affect how far the robot travels. (CA NGSS: MS-PS2-2) Alternatively, students could test a game simulation and change variables (e.g., skill of simulated players, nature of opening moves) and analyze how these changes affect who wins the game. (CA NGSS: MS-ETS1-3) Additionally, students could modify a model for predicting the likely color of the next pick from a bag of colored candy and analyze the effects of changing variables representing the common color ratios in a typical bag of candy. (CA CCSS for Mathematics 7.SP.7, 8.SP.4)
Test and analyze the effects of changing variables while using computational models.
Descriptive Statement:
Variables within a computational model may be changed, in order to alter a computer simulation or to more accurately represent how various data is related. Students interact with a given model, make changes to identified model variables, and observe and reflect upon the results. For example, students could test a program that makes a robot move on a track by making changes to variables (e.g., height and angle of track, size and mass of the robot) and discussing how these changes affect how far the robot travels. (CA NGSS: MS-PS2-2) Alternatively, students could test a game simulation and change variables (e.g., skill of simulated players, nature of opening moves) and analyze how these changes affect who wins the game. (CA NGSS: MS-ETS1-3) Additionally, students could modify a model for predicting the likely color of the next pick from a bag of colored candy and analyze the effects of changing variables representing the common color ratios in a typical bag of candy. (CA CCSS for Mathematics 7.SP.7, 8.SP.4)
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.AP.13
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Variables
Practice(s):
Developing and Using Abstractions (4.1)
Standard:
Create more generalized computational solutions using collections instead of repeatedly using simple variables.
Descriptive Statement:
Computers can automate repetitive tasks with algorithms that use collections to simplify and generalize computational problems. Students identify common features in multiple segments of code and substitute a single segment that uses collections (i.e., arrays, sets, lists) to account for the differences. For example, students could take a program that inputs students' scores into multiple variables and modify it to read these scores into a single array of scores. Alternatively, instead of writing one procedure to find averages of student scores and another to find averages of student absences, students could write a single general average procedure to support both tasks.
Create more generalized computational solutions using collections instead of repeatedly using simple variables.
Descriptive Statement:
Computers can automate repetitive tasks with algorithms that use collections to simplify and generalize computational problems. Students identify common features in multiple segments of code and substitute a single segment that uses collections (i.e., arrays, sets, lists) to account for the differences. For example, students could take a program that inputs students' scores into multiple variables and modify it to read these scores into a single array of scores. Alternatively, instead of writing one procedure to find averages of student scores and another to find averages of student absences, students could write a single general average procedure to support both tasks.
Standard Identifier: 9-12.CS.2
Grade Range:
9–12
Concept:
Computing Systems
Subconcept:
Hardware & Software
Practice(s):
Developing and Using Abstractions (4.1)
Standard:
Compare levels of abstraction and interactions between application software, system software, and hardware.
Descriptive Statement:
At its most basic level, a computer is composed of physical hardware on which software runs. Multiple layers of software are built upon various layers of hardware. Layers manage interactions and complexity in the computing system. System software manages a computing device's resources so that software can interact with hardware. Application software communicates with the user and the system software to accomplish its purpose. Students compare and describe how application software, system software, and hardware interact. For example, students could compare how various levels of hardware and software interact when a picture is to be taken on a smartphone. Systems software provides low-level commands to operate the camera hardware, but the application software interacts with system software at a higher level by requesting a common image file format (e.g., .png) that the system software provides.
Compare levels of abstraction and interactions between application software, system software, and hardware.
Descriptive Statement:
At its most basic level, a computer is composed of physical hardware on which software runs. Multiple layers of software are built upon various layers of hardware. Layers manage interactions and complexity in the computing system. System software manages a computing device's resources so that software can interact with hardware. Application software communicates with the user and the system software to accomplish its purpose. Students compare and describe how application software, system software, and hardware interact. For example, students could compare how various levels of hardware and software interact when a picture is to be taken on a smartphone. Systems software provides low-level commands to operate the camera hardware, but the application software interacts with system software at a higher level by requesting a common image file format (e.g., .png) that the system software provides.
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: 9-12S.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.
Showing 11 - 20 of 23 Standards
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