Computer Science Standards
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Showing 11 - 17 of 17 Standards
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.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: 9-12S.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.CS.1
Grade Range:
9–12 Specialty
Concept:
Computing Systems
Subconcept:
Devices
Practice(s):
Developing and Using Abstractions, Communicating About Computing (4.4, 7.2)
Standard:
Illustrate ways computing systems implement logic through hardware components.
Descriptive Statement:
Computing systems use processors (e.g., a central processing unit or CPU) to execute program instructions. Processors are composed of components that implement the logical or computational operations required by the instructions. AND, OR, and NOT are examples of logic gates. Adders are examples of higher-leveled circuits built using low-level logic gates. Students illustrate how modern computing devices are made up of smaller and simpler components which implement the logic underlying the functionality of a computer processor. At this level, knowledge of how logic gates are constructed is not expected. For example, students could construct truth tables, draw logic circuit diagrams, or use an online logic circuit simulator. Students could explore the interaction of the CPU, RAM, and I/O by labeling a diagram of the von Neumann architecture. Alternatively, students could design higher-level circuits using low-level logic gates (e.g., adders).
Illustrate ways computing systems implement logic through hardware components.
Descriptive Statement:
Computing systems use processors (e.g., a central processing unit or CPU) to execute program instructions. Processors are composed of components that implement the logical or computational operations required by the instructions. AND, OR, and NOT are examples of logic gates. Adders are examples of higher-leveled circuits built using low-level logic gates. Students illustrate how modern computing devices are made up of smaller and simpler components which implement the logic underlying the functionality of a computer processor. At this level, knowledge of how logic gates are constructed is not expected. For example, students could construct truth tables, draw logic circuit diagrams, or use an online logic circuit simulator. Students could explore the interaction of the CPU, RAM, and I/O by labeling a diagram of the von Neumann architecture. Alternatively, students could design higher-level circuits using low-level logic gates (e.g., adders).
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.
Standard Identifier: 9-12S.DA.8
Grade Range:
9–12 Specialty
Concept:
Data & Analysis
Subconcept:
Collection, Visualization, & Transformation
Practice(s):
Developing and Using Abstractions, Communicating About Computing (4.1, 7.1)
Standard:
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.
Showing 11 - 17 of 17 Standards
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