Computer Science Standards
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Showing 1 - 10 of 13 Standards
Standard Identifier: K-2.AP.11
Grade Range:
K–2
Concept:
Algorithms & Programming
Subconcept:
Variables
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Model the way programs store data.
Descriptive Statement:
Information in the real world can be represented in computer programs. Students model the digital storage of data by transforming real-world information into symbolic representations that include text, numbers, and images. For example, after identifying symbols on a map and explaining what they represent in the real world, students could create their own symbols and corresponding legend to represent items on a map of their classroom (HSS.K.4.3, 1.2.3, 2.2.2) Alternatively, students could invent symbols to represent beat and/or pitch. Students could then modify symbols within the notation and explain how the musical phrase changes. (VAPA Music K.1.1, 1.1.1, 2.1.1, 2.2.2)
Model the way programs store data.
Descriptive Statement:
Information in the real world can be represented in computer programs. Students model the digital storage of data by transforming real-world information into symbolic representations that include text, numbers, and images. For example, after identifying symbols on a map and explaining what they represent in the real world, students could create their own symbols and corresponding legend to represent items on a map of their classroom (HSS.K.4.3, 1.2.3, 2.2.2) Alternatively, students could invent symbols to represent beat and/or pitch. Students could then modify symbols within the notation and explain how the musical phrase changes. (VAPA Music K.1.1, 1.1.1, 2.1.1, 2.2.2)
Standard Identifier: K-2.DA.9
Grade Range:
K–2
Concept:
Data & Analysis
Subconcept:
Inference & Models
Practice(s):
Developing and Using Abstractions (4.1)
Standard:
Identify and describe patterns in data visualizations, such as charts or graphs, to make predictions.
Descriptive Statement:
Data can be used to make inferences or predictions about the world. For example, students could record the number of each color of candy in a small packet. Then, they compare their individual data with classmates. Students could use the collected data to predict how many of each colored candy will be in a full size bag of like candy. (CA CCSS for Mathematics K.MD.3, 1.MD.4, 2.MD.10) Alternatively, students could sort and classify objects according to their properties and note observations. Students could then create a graph or chart of their observations and look for connections/relationships (e.g., items that are hard are usually also smooth, or items that are fluffy are usually also light in weight.) Students then look at pictures of additional objects and make predictions regarding the properties of the objects pictured. (CA NGSS: 2-PS1-1, 2-PS1-2)
Identify and describe patterns in data visualizations, such as charts or graphs, to make predictions.
Descriptive Statement:
Data can be used to make inferences or predictions about the world. For example, students could record the number of each color of candy in a small packet. Then, they compare their individual data with classmates. Students could use the collected data to predict how many of each colored candy will be in a full size bag of like candy. (CA CCSS for Mathematics K.MD.3, 1.MD.4, 2.MD.10) Alternatively, students could sort and classify objects according to their properties and note observations. Students could then create a graph or chart of their observations and look for connections/relationships (e.g., items that are hard are usually also smooth, or items that are fluffy are usually also light in weight.) Students then look at pictures of additional objects and make predictions regarding the properties of the objects pictured. (CA NGSS: 2-PS1-1, 2-PS1-2)
Standard Identifier: 3-5.AP.14
Grade Range:
3–5
Concept:
Algorithms & Programming
Subconcept:
Modularity
Practice(s):
Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.3)
Standard:
Create programs by incorporating smaller portions of existing programs, to develop something new or add more advanced features.
Descriptive Statement:
Programs can be broken down into smaller parts, which can be incorporated into new or existing programs. Students incorporate predefined functions into their original designs. At this level, students do not need to understand all of the underlying implementation details of the abstractions that they use. For example, students could use code from a ping pong animation to make a ball bounce in a new basketball game. They could also incorporate code from a single-player basketball game to create a two-player game with slightly different rules. Alternatively, students could remix an animated story and add their own conclusion and/or additional dialogue. (CA CCSS for ELA/Literacy W.3.3.B, W.3.3.D, W.4.3.B, W.4.3.E, W.5.3.B, W.5.3.E) Additionally, when creating a game that occurs on the moon or planets, students could incorporate and modify code that simulates gravity on Earth. They could modify the strength of the gravitational force based on the mass of the planet or moon. (CA NGSS: 5-PS2-1)
Create programs by incorporating smaller portions of existing programs, to develop something new or add more advanced features.
Descriptive Statement:
Programs can be broken down into smaller parts, which can be incorporated into new or existing programs. Students incorporate predefined functions into their original designs. At this level, students do not need to understand all of the underlying implementation details of the abstractions that they use. For example, students could use code from a ping pong animation to make a ball bounce in a new basketball game. They could also incorporate code from a single-player basketball game to create a two-player game with slightly different rules. Alternatively, students could remix an animated story and add their own conclusion and/or additional dialogue. (CA CCSS for ELA/Literacy W.3.3.B, W.3.3.D, W.4.3.B, W.4.3.E, W.5.3.B, W.5.3.E) Additionally, when creating a game that occurs on the moon or planets, students could incorporate and modify code that simulates gravity on Earth. They could modify the strength of the gravitational force based on the mass of the planet or moon. (CA NGSS: 5-PS2-1)
Standard Identifier: 6-8.AP.14
Grade Range:
6–8
Concept:
Algorithms & Programming
Subconcept:
Modularity
Practice(s):
Developing and Using Abstractions (4.1, 4.3)
Standard:
Create procedures with parameters to organize code and make it easier to reuse.
Descriptive Statement:
Procedures support modularity in developing programs. Parameters can provide greater flexibility, reusability, and efficient use of resources. Students create procedures and/or functions that are used multiple times within a program to repeat groups of instructions. They generalize the procedures and/or functions by defining parameters that generate different outputs for a wide range of inputs. For example, students could create a procedure to draw a circle which involves many instructions, but all of them can be invoked with one instruction, such as “drawCircle.” By adding a radius parameter, students can easily draw circles of different sizes. (CA CCSS for Mathematics 7.G.4) Alternatively, calculating the area of a regular polygon requires multiple steps. Students could write a function that accepts the number and length of the sides as parameters and then calculates the area of the polygon. This function can then be re-used inside any program to calculate the area of a regular polygon. (CA CCSS for Mathematics 6.G.1)
Create procedures with parameters to organize code and make it easier to reuse.
Descriptive Statement:
Procedures support modularity in developing programs. Parameters can provide greater flexibility, reusability, and efficient use of resources. Students create procedures and/or functions that are used multiple times within a program to repeat groups of instructions. They generalize the procedures and/or functions by defining parameters that generate different outputs for a wide range of inputs. For example, students could create a procedure to draw a circle which involves many instructions, but all of them can be invoked with one instruction, such as “drawCircle.” By adding a radius parameter, students can easily draw circles of different sizes. (CA CCSS for Mathematics 7.G.4) Alternatively, calculating the area of a regular polygon requires multiple steps. Students could write a function that accepts the number and length of the sides as parameters and then calculates the area of the polygon. This function can then be re-used inside any program to calculate the area of a regular polygon. (CA CCSS for Mathematics 6.G.1)
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.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.AP.17
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Modularity
Practice(s):
Developing and Using Abstractions, Creating Computational Artifacts (4.3, 5.2)
Standard:
Create computational artifacts using modular design.
Descriptive Statement:
Computational artifacts are created by combining and modifying existing computational artifacts and/or by developing new artifacts. To reduce complexity, large programs can be designed as systems of interacting modules, each with a specific role, coordinating for a common overall purpose. Students should create computational artifacts with interacting procedures, modules, and/or libraries. For example, students could incorporate a physics library into an animation of bouncing balls. Alternatively, students could integrate open-source JavaScript libraries to expand the functionality of a web application. Additionally, students could create their own game to teach Spanish vocabulary words using their own modular design (e.g., including methods to: control scoring, manage wordlists, manage access to different game levels, take input from the user, etc.).
Create computational artifacts using modular design.
Descriptive Statement:
Computational artifacts are created by combining and modifying existing computational artifacts and/or by developing new artifacts. To reduce complexity, large programs can be designed as systems of interacting modules, each with a specific role, coordinating for a common overall purpose. Students should create computational artifacts with interacting procedures, modules, and/or libraries. For example, students could incorporate a physics library into an animation of bouncing balls. Alternatively, students could integrate open-source JavaScript libraries to expand the functionality of a web application. Additionally, students could create their own game to teach Spanish vocabulary words using their own modular design (e.g., including methods to: control scoring, manage wordlists, manage access to different game levels, take input from the user, etc.).
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.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.16
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Modularity
Practice(s):
Recognizing and Defining Computational Problems, Developing and Using Abstractions (3.2, 4.2)
Standard:
Analyze a large-scale computational problem and identify generalizable patterns or problem components that can be applied to a solution.
Descriptive Statement:
As students encounter complex, real-world problems that span multiple disciplines or social systems, they need to be able to decompose problems and apply already developed code as part of their solutions. Students decompose complex problems into manageable subproblems that could potentially be solved with programs or procedures that can be reused or already exist. For example, in analyzing an Internet radio app, students could identify that users need to create an account and enter a password. They could identify a common application programming interface (API) for checking and displaying password strength. Additionally, students could recognize that the songs would need to be sorted by the time last played in order to display the most recently played songs and identify a common API for sorting dates from most to least recent. Alternatively, in analyzing the problem of tracking medical treatment in a hospital, students could recognize that patient records need to be stored in a database and identify a database solution to support quick access and modification of patient records. Additionally, they could recognize that records in the database need to be stored securely and could identify an encryption API to support the desired level of privacy.
Analyze a large-scale computational problem and identify generalizable patterns or problem components that can be applied to a solution.
Descriptive Statement:
As students encounter complex, real-world problems that span multiple disciplines or social systems, they need to be able to decompose problems and apply already developed code as part of their solutions. Students decompose complex problems into manageable subproblems that could potentially be solved with programs or procedures that can be reused or already exist. For example, in analyzing an Internet radio app, students could identify that users need to create an account and enter a password. They could identify a common application programming interface (API) for checking and displaying password strength. Additionally, students could recognize that the songs would need to be sorted by the time last played in order to display the most recently played songs and identify a common API for sorting dates from most to least recent. Alternatively, in analyzing the problem of tracking medical treatment in a hospital, students could recognize that patient records need to be stored in a database and identify a database solution to support quick access and modification of patient records. Additionally, they could recognize that records in the database need to be stored securely and could identify an encryption API to support the desired level of privacy.
Showing 1 - 10 of 13 Standards
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