Computer Science Standards
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Showing 11 - 20 of 28 Standards
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.CS.1
Grade Range:
6–8
Concept:
Computing Systems
Subconcept:
Devices
Practice(s):
Fostering an Inclusive Computing Culture, Recognizing and Defining Computational Problems (1.2, 3.3)
Standard:
Design modifications to computing devices in order to improve the ways users interact with the devices.
Descriptive Statement:
Computing devices can extend the abilities of humans, but design considerations are critical to make these devices useful. Students suggest modifications to the design of computing devices and describe how these modifications would improve usabilty. For example, students could create a design for the screen layout of a smartphone that is more usable by people with vision impairments or hand tremors. They might also design how to use the device as a scanner to convert text to speech. Alternatively, students could design modifications for a student ID card reader to increase usability by planning for scanner height, need of scanner device to be connected physically to the computer, robustness of scanner housing, and choice of use of RFID or line of sight scanners. (CA NGSS: MS-ETS1-1)
Design modifications to computing devices in order to improve the ways users interact with the devices.
Descriptive Statement:
Computing devices can extend the abilities of humans, but design considerations are critical to make these devices useful. Students suggest modifications to the design of computing devices and describe how these modifications would improve usabilty. For example, students could create a design for the screen layout of a smartphone that is more usable by people with vision impairments or hand tremors. They might also design how to use the device as a scanner to convert text to speech. Alternatively, students could design modifications for a student ID card reader to increase usability by planning for scanner height, need of scanner device to be connected physically to the computer, robustness of scanner housing, and choice of use of RFID or line of sight scanners. (CA NGSS: MS-ETS1-1)
Standard Identifier: 6-8.DA.8
Grade Range:
6–8
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Communicating About Computing (7.1)
Standard:
Collect data using computational tools and transform the data to make it more useful.
Descriptive Statement:
Data collection has become easier and more ubiquitous. The cleaning of data is an important transformation for ensuring consistent format, reducing noise and errors (e.g., removing irrelevant responses in a survey), and/or making it easier for computers to process. Students build on their ability to organize and present data visually to support a claim, understanding when and how to transform data so information can be more easily extracted. Students also transform data to highlight or expose relationships. For example, students could use computational tools to collect data from their peers regarding the percentage of time technology is used for school work and entertainment, and then create digital displays of their data and findings. Students could then transform the data to highlight relationships representing males and females as percentages of a whole instead of as individual counts. (CA CCSS for Mathematics 6.SP.4, 7.SP.3, 8.SP.1, 8.SP.4) Alternatively, students could collect data from online forms and surveys, from a sensor, or by scraping a web page, and then transform the data to expose relationships. They could highlight the distribution of data (e.g., words on a web page, readings from a sensor) by giving quantitative measures of center and variability. (CA CCSS for Mathematics 6.SP.5.c, 7.SP.4)
Collect data using computational tools and transform the data to make it more useful.
Descriptive Statement:
Data collection has become easier and more ubiquitous. The cleaning of data is an important transformation for ensuring consistent format, reducing noise and errors (e.g., removing irrelevant responses in a survey), and/or making it easier for computers to process. Students build on their ability to organize and present data visually to support a claim, understanding when and how to transform data so information can be more easily extracted. Students also transform data to highlight or expose relationships. For example, students could use computational tools to collect data from their peers regarding the percentage of time technology is used for school work and entertainment, and then create digital displays of their data and findings. Students could then transform the data to highlight relationships representing males and females as percentages of a whole instead of as individual counts. (CA CCSS for Mathematics 6.SP.4, 7.SP.3, 8.SP.1, 8.SP.4) Alternatively, students could collect data from online forms and surveys, from a sensor, or by scraping a web page, and then transform the data to expose relationships. They could highlight the distribution of data (e.g., words on a web page, readings from a sensor) by giving quantitative measures of center and variability. (CA CCSS for Mathematics 6.SP.5.c, 7.SP.4)
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: 6-8.IC.22
Grade Range:
6–8
Concept:
Impacts of Computing
Subconcept:
Social Interactions
Practice(s):
Collaborating Around Computing, Creating Computational Artifacts (2.4, 5.2)
Standard:
Collaborate with many contributors when creating a computational artifact.
Descriptive Statement:
Users have diverse sets of experiences, needs, and wants. These need to be understood and integrated into the design of computational artifacts. Students use applications that enable crowdsourcing to gather services, ideas, or content from a large group of people. At this level, crowdsourcing can be done at the local level (e.g., classroom, school, or neighborhood) and/or global level (e.g., age-appropriate online communities). For example, a group of students could use electronic surveys to solicit input from their neighborhood regarding an important social or political issue. They could collaborate with a community artist to combine animations and create a digital community collage informing the public about various points of view regarding the topic. (VAPA Visual Art 8.5.2, 8.5.4)
Collaborate with many contributors when creating a computational artifact.
Descriptive Statement:
Users have diverse sets of experiences, needs, and wants. These need to be understood and integrated into the design of computational artifacts. Students use applications that enable crowdsourcing to gather services, ideas, or content from a large group of people. At this level, crowdsourcing can be done at the local level (e.g., classroom, school, or neighborhood) and/or global level (e.g., age-appropriate online communities). For example, a group of students could use electronic surveys to solicit input from their neighborhood regarding an important social or political issue. They could collaborate with a community artist to combine animations and create a digital community collage informing the public about various points of view regarding the topic. (VAPA Visual Art 8.5.2, 8.5.4)
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.CS.1
Grade Range:
9–12
Concept:
Computing Systems
Subconcept:
Devices
Practice(s):
Developing and Using Abstractions (4.1)
Standard:
Describe ways in which abstractions hide the underlying implementation details of computing systems to simplify user experiences.
Descriptive Statement:
An abstraction is a representation of an idea or phenomenon that hides details irrelevant to the question at hand. Computing systems, both stand alone and embedded in products, are often integrated with other systems to simplify user experiences. For example, students could identify geolocation hardware embedded in a smartphone and describe how this simplifies the users experience since the user does not have to enter her own location on the phone. Alternatively, students might select an embedded device such as a car stereo, identify the types of data (e.g., radio station presets, volume level) and procedures (e.g., increase volume, store/recall saved station, mute) it includes, and explain how the implementation details are hidden from the user.
Describe ways in which abstractions hide the underlying implementation details of computing systems to simplify user experiences.
Descriptive Statement:
An abstraction is a representation of an idea or phenomenon that hides details irrelevant to the question at hand. Computing systems, both stand alone and embedded in products, are often integrated with other systems to simplify user experiences. For example, students could identify geolocation hardware embedded in a smartphone and describe how this simplifies the users experience since the user does not have to enter her own location on the phone. Alternatively, students might select an embedded device such as a car stereo, identify the types of data (e.g., radio station presets, volume level) and procedures (e.g., increase volume, store/recall saved station, mute) it includes, and explain how the implementation details are hidden from the user.
Standard Identifier: 9-12.DA.10
Grade Range:
9–12
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Creating Computational Artifacts (5.2)
Standard:
Create data visualizations to help others better understand real-world phenomena.
Descriptive Statement:
People transform, generalize, simplify, and present large data sets in different ways to influence how other people interpret and understand the underlying information. Students select relevant data from large or complex data sets in support of a claim or to communicate the information in a more sophisticated manner. Students use software tools or programming to perform a range of mathematical operations to transform and analyze data and create powerful data visualizations (that reveal patterns in the data). For example, students could create data visualizations to reveal patterns in voting data by state, gender, political affiliation, or socioeconomic status. Alternatively, students could use U.S. government data on criticially endangered animals to visualize population change over time.
Create data visualizations to help others better understand real-world phenomena.
Descriptive Statement:
People transform, generalize, simplify, and present large data sets in different ways to influence how other people interpret and understand the underlying information. Students select relevant data from large or complex data sets in support of a claim or to communicate the information in a more sophisticated manner. Students use software tools or programming to perform a range of mathematical operations to transform and analyze data and create powerful data visualizations (that reveal patterns in the data). For example, students could create data visualizations to reveal patterns in voting data by state, gender, political affiliation, or socioeconomic status. Alternatively, students could use U.S. government data on criticially endangered animals to visualize population change over time.
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.IC.27
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Social Interactions
Practice(s):
Collaborating Around Computing (2.4)
Standard:
Use collaboration tools and methods to increase connectivity with people of different cultures and careers.
Descriptive Statement:
Increased digital connectivity and communication between people across a variety of cultures and in differing professions has changed the collaborative nature of personal and professional interaction. Students identify, explain, and use appropriate collaborative tools. For example, students could compare ways that various technological collaboration tools could help a team become more cohesive and then choose one of these tools to manage their teamwork. Alternatively, students could use different collaborative tools and methods to solicit input from not only team members and classmates but also others, such as participants in online forums or local communities.
Use collaboration tools and methods to increase connectivity with people of different cultures and careers.
Descriptive Statement:
Increased digital connectivity and communication between people across a variety of cultures and in differing professions has changed the collaborative nature of personal and professional interaction. Students identify, explain, and use appropriate collaborative tools. For example, students could compare ways that various technological collaboration tools could help a team become more cohesive and then choose one of these tools to manage their teamwork. Alternatively, students could use different collaborative tools and methods to solicit input from not only team members and classmates but also others, such as participants in online forums or local communities.
Showing 11 - 20 of 28 Standards
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