Computer Science Standards
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Collection, Visualization, & Transformation
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Network Communication & Organization
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Showing 11 - 20 of 24 Standards
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.NI.4
Grade Range:
6–8
Concept:
Networks & the Internet
Subconcept:
Network Communication & Organization
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Model the role of protocols in transmitting data across networks and the Internet.
Descriptive Statement:
Protocols are rules that define how messages between computers are sent. They determine how quickly and securely information is transmitted across networks, as well as how to handle errors in transmission. Students model how data is sent using protocols to choose the fastest path and to deal with missing information. Knowledge of the details of how specific protocols work is not expected. The priority at this grade level is understanding the purpose of protocols and how they enable efficient and errorless communication. For example, students could devise a plan for sending data representing a textual message and devise a plan for resending lost information. Alternatively, students could devise a plan for sending data to represent a picture, and devise a plan for interpreting the image when pieces of the data are missing. Additionally, students could model the speed of sending messages by Bluetooth, Wi-Fi, or cellular networks and describe ways errors in data transmission can be detected and dealt with.
Model the role of protocols in transmitting data across networks and the Internet.
Descriptive Statement:
Protocols are rules that define how messages between computers are sent. They determine how quickly and securely information is transmitted across networks, as well as how to handle errors in transmission. Students model how data is sent using protocols to choose the fastest path and to deal with missing information. Knowledge of the details of how specific protocols work is not expected. The priority at this grade level is understanding the purpose of protocols and how they enable efficient and errorless communication. For example, students could devise a plan for sending data representing a textual message and devise a plan for resending lost information. Alternatively, students could devise a plan for sending data to represent a picture, and devise a plan for interpreting the image when pieces of the data are missing. Additionally, students could model the speed of sending messages by Bluetooth, Wi-Fi, or cellular networks and describe ways errors in data transmission can be detected and dealt with.
Standard Identifier: 9-12.AP.14
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Control
Practice(s):
Creating Computational Artifacts (5.2)
Standard:
Justify the selection of specific control structures by identifying tradeoffs associated with implementation, readability, and performance.
Descriptive Statement:
The selection of control structures in a given programming language impacts readability and performance. Readability refers to how clear the program is to other programmers and can be improved through documentation. Control structures at this level may include, for example, conditional statements, loops, event handlers, and recursion. Students justify control structure selection and tradeoffs in the process of creating their own computational artifacts. The discussion of performance is limited to a theoretical understanding of execution time and storage requirements; a quantitative analysis is not expected. For example, students could compare the readability and program performance of iterative and recursive implementations of procedures that calculate the Fibonacci sequence. Alternatively, students could compare the readability and performance tradeoffs of multiple if statements versus a nested if statement.
Justify the selection of specific control structures by identifying tradeoffs associated with implementation, readability, and performance.
Descriptive Statement:
The selection of control structures in a given programming language impacts readability and performance. Readability refers to how clear the program is to other programmers and can be improved through documentation. Control structures at this level may include, for example, conditional statements, loops, event handlers, and recursion. Students justify control structure selection and tradeoffs in the process of creating their own computational artifacts. The discussion of performance is limited to a theoretical understanding of execution time and storage requirements; a quantitative analysis is not expected. For example, students could compare the readability and program performance of iterative and recursive implementations of procedures that calculate the Fibonacci sequence. Alternatively, students could compare the readability and performance tradeoffs of multiple if statements versus a nested if statement.
Standard Identifier: 9-12.AP.15
Grade Range:
9–12
Concept:
Algorithms & Programming
Subconcept:
Control
Practice(s):
Creating Computational Artifacts (5.1, 5.2, 5.3)
Standard:
Iteratively design and develop computational artifacts for practical intent, personal expression, or to address a societal issue by using events to initiate instructions.
Descriptive Statement:
In this context, relevant computational artifacts can include programs, mobile apps, or web apps. Events can be user-initiated, such as a button press, or system-initiated, such as a timer firing. For example, students might create a tool for drawing on a canvas by first implementing a button to set the color of the pen. Alternatively, students might create a game where many events control instructions executed (e.g., when a score climbs above a threshold, a congratulatory sound is played; when a user clicks on an object, the object is loaded into a basket; when a user clicks on an arrow key, the player object is moved around the screen).
Iteratively design and develop computational artifacts for practical intent, personal expression, or to address a societal issue by using events to initiate instructions.
Descriptive Statement:
In this context, relevant computational artifacts can include programs, mobile apps, or web apps. Events can be user-initiated, such as a button press, or system-initiated, such as a timer firing. For example, students might create a tool for drawing on a canvas by first implementing a button to set the color of the pen. Alternatively, students might create a game where many events control instructions executed (e.g., when a score climbs above a threshold, a congratulatory sound is played; when a user clicks on an object, the object is loaded into a basket; when a user clicks on an arrow key, the player object is moved around the screen).
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.NI.4
Grade Range:
9–12
Concept:
Networks & the Internet
Subconcept:
Network Communication & Organization
Practice(s):
Developing and Using Abstractions (4.1)
Standard:
Describe issues that impact network functionality.
Descriptive Statement:
Many different organizations, including educational, governmental, private businesses, and private households rely on networks to function adequately in order to engage in online commerce and activity. Quality of Service (QoS) refers to the capability of a network to provide better service to selected network traffic over various technologies from the perspective of the consumer. Students define and discuss performance measures that impact network functionality, such as latency, bandwidth, throughput, jitter, and error rate. For example, students could use online network simulators to explore how performance measures impact network functionality and describe impacts when various changes in the network occur. Alternatively, students could describe how pauses in television interviews conducted over satellite telephones are impacted by networking factors such as latency and jitter.
Describe issues that impact network functionality.
Descriptive Statement:
Many different organizations, including educational, governmental, private businesses, and private households rely on networks to function adequately in order to engage in online commerce and activity. Quality of Service (QoS) refers to the capability of a network to provide better service to selected network traffic over various technologies from the perspective of the consumer. Students define and discuss performance measures that impact network functionality, such as latency, bandwidth, throughput, jitter, and error rate. For example, students could use online network simulators to explore how performance measures impact network functionality and describe impacts when various changes in the network occur. Alternatively, students could describe how pauses in television interviews conducted over satellite telephones are impacted by networking factors such as latency and jitter.
Standard Identifier: 9-12.NI.5
Grade Range:
9–12
Concept:
Networks & the Internet
Subconcept:
Network Communication & Organization
Practice(s):
Communicating About Computing (7.2)
Standard:
Describe the design characteristics of the Internet.
Descriptive Statement:
The Internet connects devices and networks all over the world. Large-scale coordination occurs among many different machines across multiple paths every time a web page is opened or an image is viewed online. Through the domain name system (DNS), devices on the Internet can look up Internet Protocol (IP) addresses, allowing end-to-end communication between devices. The design decisions that direct the coordination among systems composing the Internet also allow for scalability and reliability. Students factor historical, cultural, and economic decisions in their explanations of the Internet. For example, students could explain how hierarchy in the DNS supports scalability and reliability. Alternatively, students could describe how the redundancy of routing between two nodes on the Internet increases reliability and scales as the Internet grows.
Describe the design characteristics of the Internet.
Descriptive Statement:
The Internet connects devices and networks all over the world. Large-scale coordination occurs among many different machines across multiple paths every time a web page is opened or an image is viewed online. Through the domain name system (DNS), devices on the Internet can look up Internet Protocol (IP) addresses, allowing end-to-end communication between devices. The design decisions that direct the coordination among systems composing the Internet also allow for scalability and reliability. Students factor historical, cultural, and economic decisions in their explanations of the Internet. For example, students could explain how hierarchy in the DNS supports scalability and reliability. Alternatively, students could describe how the redundancy of routing between two nodes on the Internet increases reliability and scales as the Internet grows.
Standard Identifier: 9-12S.AP.15
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Control
Practice(s):
Recognizing and Defining Computational Problems, Communicating About Computing (3.2, 7.2)
Standard:
Demonstrate the flow of execution of a recursive algorithm.
Descriptive Statement:
Recursion is a powerful problem-solving approach where the problem solution is built on solutions of smaller instances of the same problem. A base case, which returns a result without referencing itself, must be defined, otherwise infinite recursion will occur. Students represent a sequence of calls to a recursive algorithm and show how the process resolves to a solution. For example, students could draw a diagram to illustrate flow of execution by keeping track of parameter and returned values for each recursive call. Alternatively, students could create a video showing the passing of arguments as the recursive algorithm runs.
Demonstrate the flow of execution of a recursive algorithm.
Descriptive Statement:
Recursion is a powerful problem-solving approach where the problem solution is built on solutions of smaller instances of the same problem. A base case, which returns a result without referencing itself, must be defined, otherwise infinite recursion will occur. Students represent a sequence of calls to a recursive algorithm and show how the process resolves to a solution. For example, students could draw a diagram to illustrate flow of execution by keeping track of parameter and returned values for each recursive call. Alternatively, students could create a video showing the passing of arguments as the recursive algorithm runs.
Standard Identifier: 9-12S.DA.7
Grade Range:
9–12 Specialty
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Communicating About Computing (7.1)
Standard:
Select and use data collection tools and techniques to generate data sets.
Descriptive Statement:
Data collection and organization is essential for obtaining new information insights and revealing new knowledge in our modern world. As computers are able to process larger sets of data, gathering data in an efficient and reliable matter remains important. The choice of data collection tools and quality of the data collected influences how new information, insights, and knowledge will support claims and be communicated. Students devise a reliable method to gather information, use software to extract digital data from data sets, and clean and organize the data in ways that support summaries of information obtained from the data. At this level, students may, but are not required to, create their own data collection tools. For example, students could create a computational artifact that records information from a sonic distance sensor to monitor the motion of a prototype vehicle. Alternatively, students could develop a reliable and practical way to automatically digitally record the number of animals entering a portion of a field to graze. Additionally, students could also find a web site containing data (e.g., race results for a major marathon), scrape the data from the web site using data collection tools, and format the data so it can be analyzed.
Select and use data collection tools and techniques to generate data sets.
Descriptive Statement:
Data collection and organization is essential for obtaining new information insights and revealing new knowledge in our modern world. As computers are able to process larger sets of data, gathering data in an efficient and reliable matter remains important. The choice of data collection tools and quality of the data collected influences how new information, insights, and knowledge will support claims and be communicated. Students devise a reliable method to gather information, use software to extract digital data from data sets, and clean and organize the data in ways that support summaries of information obtained from the data. At this level, students may, but are not required to, create their own data collection tools. For example, students could create a computational artifact that records information from a sonic distance sensor to monitor the motion of a prototype vehicle. Alternatively, students could develop a reliable and practical way to automatically digitally record the number of animals entering a portion of a field to graze. Additionally, students could also find a web site containing data (e.g., race results for a major marathon), scrape the data from the web site using data collection tools, and format the data so it can be analyzed.
Showing 11 - 20 of 24 Standards
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