Computer Science Standards
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Showing 21 - 25 of 25 Standards
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.
Standard Identifier: 9-12S.DA.9
Grade Range:
9–12 Specialty
Concept:
Data & Analysis
Subconcept:
Inference & Models
Practice(s):
Developing and Using Abstractions (4.4)
Standard:
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
Descriptive Statement:
A model could be implemented as a diagram or a program that represents key properties of a physical or other system. A simulation is based on a model, and enables observation of the system as key properties change. Students explore, explain, and evaluate existing models and simulations, in order to support the refinement of hypotheses about how the systems work. At this level, the ability to accurately and completely model and simulate complex systems is not expected. For example, a computer model of ants following a path created by other ants who found food explains the trail-like travel patterns of the insect. Students could evaluate if the output of the model fits well with their hypothesis that ants navigate the world through the use of pheromones. They could explain how the computer model supports this hypothesis and how it might leave out certain aspects of ant behavior and whether these are important to understanding ant travel behavior. Alternatively, students could hypothesize how different ground characteristics (e.g., soil type, thickness of sediment above bedrock) relate to the severity of shaking at the surface during an earthquake. They could add or modify input about ground characteristics into an earthquake simulator, observe the changed simulation output, and then evaluate their hypotheses.
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
Descriptive Statement:
A model could be implemented as a diagram or a program that represents key properties of a physical or other system. A simulation is based on a model, and enables observation of the system as key properties change. Students explore, explain, and evaluate existing models and simulations, in order to support the refinement of hypotheses about how the systems work. At this level, the ability to accurately and completely model and simulate complex systems is not expected. For example, a computer model of ants following a path created by other ants who found food explains the trail-like travel patterns of the insect. Students could evaluate if the output of the model fits well with their hypothesis that ants navigate the world through the use of pheromones. They could explain how the computer model supports this hypothesis and how it might leave out certain aspects of ant behavior and whether these are important to understanding ant travel behavior. Alternatively, students could hypothesize how different ground characteristics (e.g., soil type, thickness of sediment above bedrock) relate to the severity of shaking at the surface during an earthquake. They could add or modify input about ground characteristics into an earthquake simulator, observe the changed simulation output, and then evaluate their hypotheses.
Standard Identifier: 9-12S.NI.5
Grade Range:
9–12 Specialty
Concept:
Networks & the Internet
Subconcept:
Cybersecurity
Practice(s):
Creating Computational Artifacts (5.3)
Standard:
Develop solutions to security threats.
Descriptive Statement:
Designing and implementing cybersecurity measures requires knowledge of software, hardware, and human components and understanding tradeoffs. Students design solutions to security threats and compare tradeoffs of easier access and use against the costs of losing information and disrupting services. For example, students could refine a technology that allows users to use blank or weak passwords. Alternatively, students could implement a firewall or proxy protection between an organization's private local area network (LAN) and the public Internet. Additionally, students could find and close exploitable threats on an infected computer in order to protect information.
Develop solutions to security threats.
Descriptive Statement:
Designing and implementing cybersecurity measures requires knowledge of software, hardware, and human components and understanding tradeoffs. Students design solutions to security threats and compare tradeoffs of easier access and use against the costs of losing information and disrupting services. For example, students could refine a technology that allows users to use blank or weak passwords. Alternatively, students could implement a firewall or proxy protection between an organization's private local area network (LAN) and the public Internet. Additionally, students could find and close exploitable threats on an infected computer in order to protect information.
Standard Identifier: 9-12S.NI.6
Grade Range:
9–12 Specialty
Concept:
Networks & the Internet
Subconcept:
Cybersecurity
Practice(s):
Recognizing and Defining Computational Problems, Developing and Using Abstractions (3.3, 4.2)
Standard:
Analyze cryptographic techniques to model the secure transmission of information.
Descriptive Statement:
Cryptography is essential to many models of cybersecurity. Open standards help to ensure cryptographic security. Certificate Authorities (CAs) issue digital certificates that validate the ownership of encrypted keys used in secured communications across the Internet. Students encode and decode messages using encryption and decryption methods, and they should understand the different levels of complexity to hide or secure information. For example, students could analyze the relative designs of private key vs. public key encryption techniques and apply the best choice for a particular scenario. Alternatively, students could analyze the design of the Diffie-Helman algorithm to RSA (Rivest–Shamir–Adleman) and apply the best choice for a particular scenario. They could provide a cost-benefit analysis of runtime and ease of cracking for various encryption techniques which are commonly used to secure transmission of data over the Internet.
Analyze cryptographic techniques to model the secure transmission of information.
Descriptive Statement:
Cryptography is essential to many models of cybersecurity. Open standards help to ensure cryptographic security. Certificate Authorities (CAs) issue digital certificates that validate the ownership of encrypted keys used in secured communications across the Internet. Students encode and decode messages using encryption and decryption methods, and they should understand the different levels of complexity to hide or secure information. For example, students could analyze the relative designs of private key vs. public key encryption techniques and apply the best choice for a particular scenario. Alternatively, students could analyze the design of the Diffie-Helman algorithm to RSA (Rivest–Shamir–Adleman) and apply the best choice for a particular scenario. They could provide a cost-benefit analysis of runtime and ease of cracking for various encryption techniques which are commonly used to secure transmission of data over the Internet.
Showing 21 - 25 of 25 Standards
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