Computer Science Standards
Results
Showing 11 - 20 of 25 Standards
Standard Identifier: 3-5.DA.9
Grade Range:
3–5
Concept:
Data & Analysis
Subconcept:
Inference & Models
Practice(s):
Communicating About Computing (7.1)
Standard:
Use data to highlight and/or propose relationships, predict outcomes, or communicate ideas.
Descriptive Statement:
The accuracy of data analysis is related to how the data is represented. Inferences or predictions based on data are less likely to be accurate if the data is insufficient, incomplete, or inaccurate or if the data is incorrect in some way. Additionally, people select aspects and subsets of data to be transformed, organized, and categorized. Students should be able to refer to data when communicating an idea, in order to highlight and/or propose relationships, predict outcomes, highlight different views and/or communicate insights and ideas. For example, students can be provided a scenario in which they are city managers who have a specific amount of funds to improve a city in California. Students can collect data of a city concerning land use, vegetation, wildlife, climate, population density, services and transportation (HSS.4.1.5) to determine and present what area needs to be focused on to improve a problem. Students can compare their data and planned use of funds with peers, clearly communicating or predict outcomes based on data collected. (CA CCCS for ELA/Literacy SL.3.1, SL.4.1, SL.5.1) Alternatively, students could record the temperature at noon each day to show that temperatures are higher in certain months of the year. If temperatures are not recorded on non-school days or are recorded incorrectly, the data would be incomplete and ideas being communicated could be inaccurate. Students may also record the day of the week on which the data was collected, but this would have no relevance to whether temperatures are higher or lower. In order to have sufficient and accurate data on which to communicate the idea, students might use data provided by a governmental weather agency. (CA NGSS: 3-ESS2-1)
Use data to highlight and/or propose relationships, predict outcomes, or communicate ideas.
Descriptive Statement:
The accuracy of data analysis is related to how the data is represented. Inferences or predictions based on data are less likely to be accurate if the data is insufficient, incomplete, or inaccurate or if the data is incorrect in some way. Additionally, people select aspects and subsets of data to be transformed, organized, and categorized. Students should be able to refer to data when communicating an idea, in order to highlight and/or propose relationships, predict outcomes, highlight different views and/or communicate insights and ideas. For example, students can be provided a scenario in which they are city managers who have a specific amount of funds to improve a city in California. Students can collect data of a city concerning land use, vegetation, wildlife, climate, population density, services and transportation (HSS.4.1.5) to determine and present what area needs to be focused on to improve a problem. Students can compare their data and planned use of funds with peers, clearly communicating or predict outcomes based on data collected. (CA CCCS for ELA/Literacy SL.3.1, SL.4.1, SL.5.1) Alternatively, students could record the temperature at noon each day to show that temperatures are higher in certain months of the year. If temperatures are not recorded on non-school days or are recorded incorrectly, the data would be incomplete and ideas being communicated could be inaccurate. Students may also record the day of the week on which the data was collected, but this would have no relevance to whether temperatures are higher or lower. In order to have sufficient and accurate data on which to communicate the idea, students might use data provided by a governmental weather agency. (CA NGSS: 3-ESS2-1)
Standard Identifier: 6-8.AP.16
Grade Range:
6–8
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Developing and Using Abstractions, Creating Computational Artifacts, Communicating About Computing (4.2, 5.2, 7.3)
Standard:
Incorporate existing code, media, and libraries into original programs, and give attribution.
Descriptive Statement:
Building on the work of others enables students to produce more interesting and powerful creations. Students use portions of code, algorithms, digital media, and/or data created by others in their own programs and websites. They give attribution to the original creators to acknowledge their contributions. For example, when creating a side-scrolling game, students may incorporate portions of code that create a realistic jump movement from another person's game, and they may also import Creative Commons-licensed images to use in the background. Alternatively, when creating a website to demonstrate their knowledge of historical figures from the Civil War, students may use a professionally-designed template and public domain images of historical figures. (HSS.8.10.5) Additionally, students could import libraries and connect to web application program interfaces (APIs) to make their own programming processes more efficient and reduce the number of bugs (e.g., to check whether the user input is a valid date, to input the current temperature from another city).
Incorporate existing code, media, and libraries into original programs, and give attribution.
Descriptive Statement:
Building on the work of others enables students to produce more interesting and powerful creations. Students use portions of code, algorithms, digital media, and/or data created by others in their own programs and websites. They give attribution to the original creators to acknowledge their contributions. For example, when creating a side-scrolling game, students may incorporate portions of code that create a realistic jump movement from another person's game, and they may also import Creative Commons-licensed images to use in the background. Alternatively, when creating a website to demonstrate their knowledge of historical figures from the Civil War, students may use a professionally-designed template and public domain images of historical figures. (HSS.8.10.5) Additionally, students could import libraries and connect to web application program interfaces (APIs) to make their own programming processes more efficient and reduce the number of bugs (e.g., to check whether the user input is a valid date, to input the current temperature from another city).
Standard Identifier: 6-8.AP.19
Grade Range:
6–8
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Communicating About Computing (7.2)
Standard:
Document programs in order to make them easier to use, read, test, and debug.
Descriptive Statement:
Documentation allows creators, end users, and other developers to more easily use and understand a program. Students provide documentation for end users that explains their artifacts and how they function (e.g., project overview, user instructions). They also include comments within code to describe portions of their programs and make it easier for themselves and other developers to use, read, test, and debug. For example, students could add comments to describe functionality of different segments of code (e.g., input scores between 0 and 100, check for invalid input, calculate and display the average of the scores). They could also communicate the process used by writing design documents, creating flowcharts, or making presentations. (CA CCSS for ELA/Literacy SL.6.5, SL.7.5, SL.8.5)
Document programs in order to make them easier to use, read, test, and debug.
Descriptive Statement:
Documentation allows creators, end users, and other developers to more easily use and understand a program. Students provide documentation for end users that explains their artifacts and how they function (e.g., project overview, user instructions). They also include comments within code to describe portions of their programs and make it easier for themselves and other developers to use, read, test, and debug. For example, students could add comments to describe functionality of different segments of code (e.g., input scores between 0 and 100, check for invalid input, calculate and display the average of the scores). They could also communicate the process used by writing design documents, creating flowcharts, or making presentations. (CA CCSS for ELA/Literacy SL.6.5, SL.7.5, SL.8.5)
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: 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.19
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Communicating About Computing (7.3)
Standard:
Explain the limitations of licenses that restrict use of computational artifacts when using resources such as libraries.
Descriptive Statement:
Software licenses include copyright, freeware, and open-source licensing schemes. Licenses are used to protect the intellectual property of the author while also defining accessibility of the code. Students consider licensing implications for their own work, especially when incorporating libraries and other resources. For example, students might consider two software libraries that address a similar need, justifying their choice of one over the other. The choice could be based upon least restrictive licensing or further protections for their own intellectual property.
Explain the limitations of licenses that restrict use of computational artifacts when using resources such as libraries.
Descriptive Statement:
Software licenses include copyright, freeware, and open-source licensing schemes. Licenses are used to protect the intellectual property of the author while also defining accessibility of the code. Students consider licensing implications for their own work, especially when incorporating libraries and other resources. For example, students might consider two software libraries that address a similar need, justifying their choice of one over the other. The choice could be based upon least restrictive licensing or further protections for their own intellectual property.
Standard Identifier: 9-12.AP.22
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Communicating About Computing (7.2)
Standard:
Document decisions made during the design process using text, graphics, presentations, and/or demonstrations in the development of complex programs.
Descriptive Statement:
Complex programs are often iteratively designed as systems of interacting modules, each with a specific role, coordinating for a common overall purpose. Comments are included in code both to document the purpose of modules as well as the implementation details within a module. Together these support documentation of the design process. Students use resources such as libraries and tools to edit and manage parts of the program and corresponding documentation. For example, during development of a computational artifact students could comment their code (with date, modification, and rationale), sketch a flowchart to summarize control flow in a code journal, and share ideas and updates on a white board. Students may document their logic by explaining the development process and presenting to the class. The presentation could include photos of their white board, a video or screencast explaining the development process, or recorded audio description.
Document decisions made during the design process using text, graphics, presentations, and/or demonstrations in the development of complex programs.
Descriptive Statement:
Complex programs are often iteratively designed as systems of interacting modules, each with a specific role, coordinating for a common overall purpose. Comments are included in code both to document the purpose of modules as well as the implementation details within a module. Together these support documentation of the design process. Students use resources such as libraries and tools to edit and manage parts of the program and corresponding documentation. For example, during development of a computational artifact students could comment their code (with date, modification, and rationale), sketch a flowchart to summarize control flow in a code journal, and share ideas and updates on a white board. Students may document their logic by explaining the development process and presenting to the class. The presentation could include photos of their white board, a video or screencast explaining the development process, or recorded audio description.
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.
Showing 11 - 20 of 25 Standards
Questions: Curriculum Frameworks and Instructional Resources Division |
CFIRD@cde.ca.gov | 916-319-0881