Computer Science Standards
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Algorithms
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Showing 11 - 20 of 35 Standards
Standard Identifier: 3-5.DA.8
Grade Range:
3–5
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Communicating About Computing (7.1)
Standard:
Organize and present collected data visually to highlight relationships and support a claim.
Descriptive Statement:
Raw data has little meaning on its own. Data is often sorted or grouped to provide additional clarity. Organizing data can make interpreting and communicating it to others easier. Data points can be clustered by a number of commonalities. The same data could be manipulated in different ways to emphasize particular aspects or parts of the data set. For example, students could create and administer electronic surveys to their classmates. Possible topics could include favorite books, family heritage, and after school activities. Students could then create digital displays of the data they have collected such as column histogram charts showing the percent of respondents in each grade who selected a particular favorite book. Finally, students could make quantitative statements supported by the data such as which books are more appealing to specific ages of students. As an extension, students could write an opinion piece stating a claim and supporting it with evidence from the data they collected. (CA CCSS for Mathematics 3.MD.3, 4.MD.4, 5.MD.2) (CA CCSS for ELA/Literacy W.3.1, W.4.1, W.5.1) Alternatively, students could represent data in tables and graphical displays to describe weather experienced in the last several years. They could select the type of graphical display based on the specific data represented (e.g., daily high/low temperatures on a scatter plot, average temperatures for a month across years in a column chart). Students could then make a claim about expected weather in future months based on the data. (CA NGSS: 3-ESS2-1)
Organize and present collected data visually to highlight relationships and support a claim.
Descriptive Statement:
Raw data has little meaning on its own. Data is often sorted or grouped to provide additional clarity. Organizing data can make interpreting and communicating it to others easier. Data points can be clustered by a number of commonalities. The same data could be manipulated in different ways to emphasize particular aspects or parts of the data set. For example, students could create and administer electronic surveys to their classmates. Possible topics could include favorite books, family heritage, and after school activities. Students could then create digital displays of the data they have collected such as column histogram charts showing the percent of respondents in each grade who selected a particular favorite book. Finally, students could make quantitative statements supported by the data such as which books are more appealing to specific ages of students. As an extension, students could write an opinion piece stating a claim and supporting it with evidence from the data they collected. (CA CCSS for Mathematics 3.MD.3, 4.MD.4, 5.MD.2) (CA CCSS for ELA/Literacy W.3.1, W.4.1, W.5.1) Alternatively, students could represent data in tables and graphical displays to describe weather experienced in the last several years. They could select the type of graphical display based on the specific data represented (e.g., daily high/low temperatures on a scatter plot, average temperatures for a month across years in a column chart). Students could then make a claim about expected weather in future months based on the data. (CA NGSS: 3-ESS2-1)
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.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.AP.11
Grade Range:
6–8
Concept:
Algorithms & Programming
Subconcept:
Variables
Practice(s):
Creating Computational Artifacts (5.1, 5.2)
Standard:
Create clearly named variables that store data, and perform operations on their contents.
Descriptive Statement:
A variable is a container for data, and the name used for accessing the variable is called the identifier. Students declare, initialize, and update variables for storing different types of program data (e.g., text, integers) using names and naming conventions (e.g. camel case) that clearly convey the purpose of the variable, facilitate debugging, and improve readability. For example, students could program a quiz game with a score variable (e.g. quizScore) that is initially set to zero and increases by increments of one each time the user answers a quiz question correctly and decreases by increments of one each time a user answers a quiz question incorrectly, resulting in a score that is either a positive or negative integer. (CA CCSS for Mathematics 6.NS.5) Alternatively, students could write a program that prompts the user for their name, stores the user's response in a variable (e.g. userName), and uses this variable to greet the user by name.
Create clearly named variables that store data, and perform operations on their contents.
Descriptive Statement:
A variable is a container for data, and the name used for accessing the variable is called the identifier. Students declare, initialize, and update variables for storing different types of program data (e.g., text, integers) using names and naming conventions (e.g. camel case) that clearly convey the purpose of the variable, facilitate debugging, and improve readability. For example, students could program a quiz game with a score variable (e.g. quizScore) that is initially set to zero and increases by increments of one each time the user answers a quiz question correctly and decreases by increments of one each time a user answers a quiz question incorrectly, resulting in a score that is either a positive or negative integer. (CA CCSS for Mathematics 6.NS.5) Alternatively, students could write a program that prompts the user for their name, stores the user's response in a variable (e.g. userName), and uses this variable to greet the user by name.
Standard Identifier: 6-8.AP.12
Grade Range:
6–8
Concept:
Algorithms & Programming
Subconcept:
Control
Practice(s):
Creating Computational Artifacts (5.1, 5.2)
Standard:
Design and iteratively develop programs that combine control structures and use compound conditions.
Descriptive Statement:
Control structures can be combined in many ways. Nested loops are loops placed within loops, and nested conditionals allow the result of one conditional to lead to another. Compound conditions combine two or more conditions in a logical relationship (e.g., using AND, OR, and NOT). Students appropriately use control structures to perform repetitive and selection tasks. For example, when programming an interactive story, students could use a compound conditional within a loop to unlock a door only if a character has a key AND is touching the door. (CA CCSS for ELA/Literacy W.6.3, W.7.3, W.8.3) Alternatively, students could use compound conditionals when writing a program to test whether two points lie along the line defined by a particular linear function. (CA CCSS for Mathematics 8.EE.7) Additionally, students could use nested loops to program a character to do the "chicken dance" by opening and closing the beak, flapping the wings, shaking the hips, and clapping four times each; this dance "chorus" is then repeated several times in its entirety.
Design and iteratively develop programs that combine control structures and use compound conditions.
Descriptive Statement:
Control structures can be combined in many ways. Nested loops are loops placed within loops, and nested conditionals allow the result of one conditional to lead to another. Compound conditions combine two or more conditions in a logical relationship (e.g., using AND, OR, and NOT). Students appropriately use control structures to perform repetitive and selection tasks. For example, when programming an interactive story, students could use a compound conditional within a loop to unlock a door only if a character has a key AND is touching the door. (CA CCSS for ELA/Literacy W.6.3, W.7.3, W.8.3) Alternatively, students could use compound conditionals when writing a program to test whether two points lie along the line defined by a particular linear function. (CA CCSS for Mathematics 8.EE.7) Additionally, students could use nested loops to program a character to do the "chicken dance" by opening and closing the beak, flapping the wings, shaking the hips, and clapping four times each; this dance "chorus" is then repeated several times in its entirety.
Standard Identifier: 6-8.DA.7
Grade Range:
6–8
Concept:
Data & Analysis
Subconcept:
Storage
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Represent data in multiple ways.
Descriptive Statement:
Computers store data as sequences of 0s and 1s (bits). Software translates to and from this low-level representation to higher levels that are understandable by people. Furthermore, higher level data can be represented in multiple ways, such as the digital display of a color and its corresponding numeric RGB value, or a bar graph, a pie chart, and table representation of the same data in a spreadsheet. For example, students could use a color picker to explore the correspondence between the digital display or name of a color (high-level representations) and its RGB value or hex code (low-level representation). Alternatively, students could translate a word (high-level representation) into Morse code or its corresponding sequence of ASCII codes (low-level representation).
Represent data in multiple ways.
Descriptive Statement:
Computers store data as sequences of 0s and 1s (bits). Software translates to and from this low-level representation to higher levels that are understandable by people. Furthermore, higher level data can be represented in multiple ways, such as the digital display of a color and its corresponding numeric RGB value, or a bar graph, a pie chart, and table representation of the same data in a spreadsheet. For example, students could use a color picker to explore the correspondence between the digital display or name of a color (high-level representations) and its RGB value or hex code (low-level representation). Alternatively, students could translate a word (high-level representation) into Morse code or its corresponding sequence of ASCII codes (low-level representation).
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.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.
Showing 11 - 20 of 35 Standards
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