Computer Science Standards
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Collection, Visualization, & Transformation
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Cybersecurity
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Hardware & Software
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Inference & Models
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Safety, Law, & Ethics
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Showing 21 - 30 of 34 Standards
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.28
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Safety, Law, & Ethics
Practice(s):
Communicating About Computing (7.3)
Standard:
Explain the beneficial and harmful effects that intellectual property laws can have on innovation.
Descriptive Statement:
Laws and ethics govern aspects of computing such as privacy, data, property, information, and identity. Students explain the beneficial and harmful effects of intellectual property laws as they relate to potential innovations and governance. For example, students could explain how patents protect inventions but may limit innovation. Alternatively, students could explain how intellectual property laws requiring that artists be paid for use of their media might limit the choice of songs developers can use in their computational artifacts.
Explain the beneficial and harmful effects that intellectual property laws can have on innovation.
Descriptive Statement:
Laws and ethics govern aspects of computing such as privacy, data, property, information, and identity. Students explain the beneficial and harmful effects of intellectual property laws as they relate to potential innovations and governance. For example, students could explain how patents protect inventions but may limit innovation. Alternatively, students could explain how intellectual property laws requiring that artists be paid for use of their media might limit the choice of songs developers can use in their computational artifacts.
Standard Identifier: 9-12.IC.29
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Safety, Law, & Ethics
Practice(s):
Communicating About Computing (7.2)
Standard:
Explain the privacy concerns related to the collection and generation of data through automated processes.
Descriptive Statement:
Data can be collected and aggregated across millions of people, even when they are not actively engaging with or physically near the data collection devices. Students recognize automated and non-evident collection of information and the privacy concerns they raise for individuals. For example, students could explain the impact on an individual when a social media site's security settings allows for mining of account information even when the user is not online. Alternatively, students could discuss the impact on individuals of using surveillance video in a store to track customers. Additionally, students could discuss how road traffic can be monitored to change signals in real time to improve road efficiency without drivers being aware and discuss policies for retaining data that identifies drivers' cars and their behaviors.
Explain the privacy concerns related to the collection and generation of data through automated processes.
Descriptive Statement:
Data can be collected and aggregated across millions of people, even when they are not actively engaging with or physically near the data collection devices. Students recognize automated and non-evident collection of information and the privacy concerns they raise for individuals. For example, students could explain the impact on an individual when a social media site's security settings allows for mining of account information even when the user is not online. Alternatively, students could discuss the impact on individuals of using surveillance video in a store to track customers. Additionally, students could discuss how road traffic can be monitored to change signals in real time to improve road efficiency without drivers being aware and discuss policies for retaining data that identifies drivers' cars and their behaviors.
Standard Identifier: 9-12.IC.30
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Safety, Law, & Ethics
Practice(s):
Communicating About Computing (7.2)
Standard:
Evaluate the social and economic implications of privacy in the context of safety, law, or ethics.
Descriptive Statement:
Laws govern many aspects of computing, such as privacy, data, property, information, and identity. International differences in laws and ethics have implications for computing. Students make and justify claims about potential and/or actual privacy implications of policies, laws, or ethics and consider the associated tradeoffs, focusing on society and the economy. For example, students could explore the case of companies tracking online shopping behaviors in order to decide which products to target to consumers. Students could evaluate the ethical and legal dilemmas of collecting such data without consumer knowledge in order to profit companies. Alternatively, students could evaluate the implications of net neutrality laws on society's access to information and on the impacts to businesses of varying sizes.
Evaluate the social and economic implications of privacy in the context of safety, law, or ethics.
Descriptive Statement:
Laws govern many aspects of computing, such as privacy, data, property, information, and identity. International differences in laws and ethics have implications for computing. Students make and justify claims about potential and/or actual privacy implications of policies, laws, or ethics and consider the associated tradeoffs, focusing on society and the economy. For example, students could explore the case of companies tracking online shopping behaviors in order to decide which products to target to consumers. Students could evaluate the ethical and legal dilemmas of collecting such data without consumer knowledge in order to profit companies. Alternatively, students could evaluate the implications of net neutrality laws on society's access to information and on the impacts to businesses of varying sizes.
Standard Identifier: 9-12.NI.6
Grade Range:
9–12
Concept:
Networks & the Internet
Subconcept:
Cybersecurity
Practice(s):
Communicating About Computing (7.2)
Standard:
Compare and contrast security measures to address various security threats.
Descriptive Statement:
Network security depends on a combination of hardware, software, and practices that control access to data and systems. The needs of users and the sensitivity of data determine the level of security implemented. Potential security problems, such as denial-of-service attacks, ransomware, viruses, worms, spyware, and phishing, present threats to sensitive data. Students compare and contrast different types of security measures based on factors such as efficiency, feasibility, ethical impacts, usability, and security. At this level, students are not expected to develop or implement the security measures that they discuss. For example, students could review case studies or current events in which governments or organizations experienced data leaks or data loss as a result of these types of attacks. Students could provide an analysis of actual security measures taken comparing to other security measure which may have led to different outcomes. Alternatively, students might discuss computer security policies in place at the local level that present a tradeoff between usability and security, such as a web filter that prevents access to many educational sites but keeps the campus network safe.
Compare and contrast security measures to address various security threats.
Descriptive Statement:
Network security depends on a combination of hardware, software, and practices that control access to data and systems. The needs of users and the sensitivity of data determine the level of security implemented. Potential security problems, such as denial-of-service attacks, ransomware, viruses, worms, spyware, and phishing, present threats to sensitive data. Students compare and contrast different types of security measures based on factors such as efficiency, feasibility, ethical impacts, usability, and security. At this level, students are not expected to develop or implement the security measures that they discuss. For example, students could review case studies or current events in which governments or organizations experienced data leaks or data loss as a result of these types of attacks. Students could provide an analysis of actual security measures taken comparing to other security measure which may have led to different outcomes. Alternatively, students might discuss computer security policies in place at the local level that present a tradeoff between usability and security, such as a web filter that prevents access to many educational sites but keeps the campus network safe.
Standard Identifier: 9-12.NI.7
Grade Range:
9–12
Concept:
Networks & the Internet
Subconcept:
Cybersecurity
Practice(s):
Recognizing and Defining Computational Problems, Developing and Using Abstractions (3.3, 4.4)
Standard:
Compare and contrast cryptographic techniques to model the secure transmission of information.
Descriptive Statement:
Cryptography is a technique for transforming information on a computer in such a way that it becomes unreadable by anyone except authorized parties. Cryptography is useful for supporting secure communication of data across networks. Examples of cryptographic methods include hashing, symmetric encryption/decryption (private key), and assymmetric encryption/decryption (public key/private key). Students use software to encode and decode messages using cryptographic methods. Students compare the costs and benefits of using various cryptographic methods. At this level, students are not expected to perform the mathematical calculations associated with encryption and decryption. For example, students could compare and contrast multiple examples of symmetric cryptographic techiques. Alternatively, students could compare and contrast symmetric and asymmetric cryptographic techniques in which they apply for a given scenario.
Compare and contrast cryptographic techniques to model the secure transmission of information.
Descriptive Statement:
Cryptography is a technique for transforming information on a computer in such a way that it becomes unreadable by anyone except authorized parties. Cryptography is useful for supporting secure communication of data across networks. Examples of cryptographic methods include hashing, symmetric encryption/decryption (private key), and assymmetric encryption/decryption (public key/private key). Students use software to encode and decode messages using cryptographic methods. Students compare the costs and benefits of using various cryptographic methods. At this level, students are not expected to perform the mathematical calculations associated with encryption and decryption. For example, students could compare and contrast multiple examples of symmetric cryptographic techiques. Alternatively, students could compare and contrast symmetric and asymmetric cryptographic techniques in which they apply for a given scenario.
Standard Identifier: 9-12S.CS.2
Grade Range:
9–12 Specialty
Concept:
Computing Systems
Subconcept:
Hardware & Software
Practice(s):
Communicating About Computing (7.2)
Standard:
Categorize and describe the different functions of operating system software.
Descriptive Statement:
Operating systems (OS) software is the code that manages the computer’s basic functions. Students describe at a high level the different functions of different components of operating system software. Examples of functions could include memory management, data storage/retrieval, processes management, and access control. For example, students could use monitoring tools including within an OS to inspect the services and functions running on a system and create an artifact to describe the activity that they observed (e.g., when a browser is running with many tabs open, memory usage is increased). They could also inspect and describe changes in the activity monitor that occur as different applications are executing (e.g., processor utilization increases when a new application is launched).
Categorize and describe the different functions of operating system software.
Descriptive Statement:
Operating systems (OS) software is the code that manages the computer’s basic functions. Students describe at a high level the different functions of different components of operating system software. Examples of functions could include memory management, data storage/retrieval, processes management, and access control. For example, students could use monitoring tools including within an OS to inspect the services and functions running on a system and create an artifact to describe the activity that they observed (e.g., when a browser is running with many tabs open, memory usage is increased). They could also inspect and describe changes in the activity monitor that occur as different applications are executing (e.g., processor utilization increases when a new application is launched).
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 21 - 30 of 34 Standards
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