Computer Science Standards
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Showing 1 - 10 of 11 Standards
Standard Identifier: K-2.AP.10
Grade Range:
K–2
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Recognizing and Defining Computational Problems, Developing and Using Abstractions (3.2, 4.4)
Standard:
Model daily processes by creating and following algorithms to complete tasks.
Descriptive Statement:
Algorithms are sequences of instructions that describe how to complete a specific task. Students create algorithms that reflect simple life tasks inside and outside of the classroom. For example, students could create algorithms to represent daily routines for getting ready for school, transitioning through center rotations, eating lunch, and putting away art materials. Students could then write a narrative sequence of events. (CA CCSS for ELA/Literacy W.K.3, W.1.3, W.2.3) Alternatively, students could create a game or a dance with a specific set of movements to reach an intentional goal or objective. (P.E K.2, 1.2, 2.2) Additionally, students could create a map of their neighborhood and give step-by-step directions of how they get to school. (HSS.K.4, 1.2, 2.2)
Model daily processes by creating and following algorithms to complete tasks.
Descriptive Statement:
Algorithms are sequences of instructions that describe how to complete a specific task. Students create algorithms that reflect simple life tasks inside and outside of the classroom. For example, students could create algorithms to represent daily routines for getting ready for school, transitioning through center rotations, eating lunch, and putting away art materials. Students could then write a narrative sequence of events. (CA CCSS for ELA/Literacy W.K.3, W.1.3, W.2.3) Alternatively, students could create a game or a dance with a specific set of movements to reach an intentional goal or objective. (P.E K.2, 1.2, 2.2) Additionally, students could create a map of their neighborhood and give step-by-step directions of how they get to school. (HSS.K.4, 1.2, 2.2)
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: 6-8.AP.10
Grade Range:
6–8
Concept:
Algorithms & Programming
Subconcept:
Algorithms
Practice(s):
Developing and Using Abstractions (4.1, 4.4)
Standard:
Use flowcharts and/or pseudocode to design and illustrate algorithms that solve complex problems.
Descriptive Statement:
Complex problems are problems that would be difficult for students to solve without breaking them down into multiple steps. Flowcharts and pseudocode are used to design and illustrate the breakdown of steps in an algorithm. Students design and illustrate algorithms using pseudocode and/or flowcharts that organize and sequence the breakdown of steps for solving complex problems. For example, students might use a flowchart to illustrate an algorithm that produces a recommendation for purchasing sneakers based on inputs such as size, colors, brand, comfort, and cost. Alternatively, students could write pseudocode to express an algorithm for suggesting their outfit for the day, based on inputs such as the weather, color preferences, and day of the week.
Use flowcharts and/or pseudocode to design and illustrate algorithms that solve complex problems.
Descriptive Statement:
Complex problems are problems that would be difficult for students to solve without breaking them down into multiple steps. Flowcharts and pseudocode are used to design and illustrate the breakdown of steps in an algorithm. Students design and illustrate algorithms using pseudocode and/or flowcharts that organize and sequence the breakdown of steps for solving complex problems. For example, students might use a flowchart to illustrate an algorithm that produces a recommendation for purchasing sneakers based on inputs such as size, colors, brand, comfort, and cost. Alternatively, students could write pseudocode to express an algorithm for suggesting their outfit for the day, based on inputs such as the weather, color preferences, and day of the week.
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.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.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.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.
Showing 1 - 10 of 11 Standards
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