Grades
Standard
Construct solutions to problems using student-created components, such as procedures, modules and/or objects.
Analyze a large-scale computational problem and identify generalizable patterns that can be applied to a solution.
Use version control systems, integrated development environments (IDEs), and collaborative tools and practices (code documentation) in a group software project.
Develop and use a series of test cases to verify that a program performs according to its design specifications.
Modify an existing program to add additional functionality and discuss intended and unintended implications (e.g., breaking other functionality).
Compare multiple programming languages and discuss how their features make them suitable for solving different types of problems.
Evaluate computational artifacts to maximize their beneficial effects and minimize harmful effects on society.
Evaluate the impact of equity, access, and influence on the distribution of computing resources in a global society.
Predict how computational innovations that have revolutionized aspects of our culture might evolve.
Evaluate licenses that limit or restrict use of computational artifacts when using resources such as libraries.
Evaluate and refine computational artifacts to make them more usable and accessible.
Design and develop computational artifacts working in team roles using collaborative tools.
Document design decisions using text, graphics, presentations, and/or demonstrations in the development of complex programs.
Evaluate the ways computing impacts personal, ethical, social, economic, and cultural practices.
Test and refine computational artifacts to reduce bias and equity deficits.
Demonstrate ways a given algorithm applies to problems across disciplines.
Use tools and methods for collaboration on a project to increase connectivity of people in different cultures and career fields.
Explain the beneficial and harmful effects that intellectual property laws can have on innovation.
Explain the privacy concerns related to the collection and generation of data through automated processes that may not be evident [...]
Evaluate the social and economic implications of privacy in the context of safety, law, or ethics.
Illustrate ways computing systems implement logic, input, and output through hardware components.
Describe the issues that impact network functionality (e.g., bandwidth, load, delay, topology).
Compare ways software developers protect devices and information from unauthorized access.
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Select data collection tools and techniques to generate data sets that support a claim or communicate information.
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
Implement an artificial intelligence algorithm to play a game against a human opponent or solve a problem.
Describe tradeoffs between allowing information to be public and keeping information private and secure.
Explain how abstractions hide the underlying implementation details of computing systems embedded in everyday objects.
Compare levels of abstraction and interactions between application software, system software, and hardware layers.
Develop guidelines that convey systematic troubleshooting strategies that others can use to identify and fix errors.
Evaluate the scalability and reliability of networks, by describing the relationship between routers, switches, servers, topology, and addressing.
Give examples to illustrate how sensitive data can be affected by malware and other attacks.
Recommend security measures to address various scenarios based on factors such as efficiency, feasibility, and ethical impacts.
Compare various security measures, considering tradeoffs between the usability and security of a computing system.
Explain tradeoffs when selecting and implementing cybersecurity recommendations.
Translate between different bit representations of real-world phenomena, such as characters, numbers, and images.
Evaluate the tradeoffs in how data elements are organized and where data is stored.
Grades
Standard
Construct solutions to problems using student-created components, such as procedures, modules and/or objects.
Analyze a large-scale computational problem and identify generalizable patterns that can be applied to a solution.
Use version control systems, integrated development environments (IDEs), and collaborative tools and practices (code documentation) in a group software project.
Develop and use a series of test cases to verify that a program performs according to its design specifications.
Modify an existing program to add additional functionality and discuss intended and unintended implications (e.g., breaking other functionality).
Compare multiple programming languages and discuss how their features make them suitable for solving different types of problems.
Evaluate computational artifacts to maximize their beneficial effects and minimize harmful effects on society.
Evaluate the impact of equity, access, and influence on the distribution of computing resources in a global society.
Predict how computational innovations that have revolutionized aspects of our culture might evolve.
Evaluate licenses that limit or restrict use of computational artifacts when using resources such as libraries.
Evaluate and refine computational artifacts to make them more usable and accessible.
Design and develop computational artifacts working in team roles using collaborative tools.
Document design decisions using text, graphics, presentations, and/or demonstrations in the development of complex programs.
Evaluate the ways computing impacts personal, ethical, social, economic, and cultural practices.
Test and refine computational artifacts to reduce bias and equity deficits.
Demonstrate ways a given algorithm applies to problems across disciplines.
Use tools and methods for collaboration on a project to increase connectivity of people in different cultures and career fields.
Explain the beneficial and harmful effects that intellectual property laws can have on innovation.
Explain the privacy concerns related to the collection and generation of data through automated processes that may not be evident [...]
Evaluate the social and economic implications of privacy in the context of safety, law, or ethics.
Illustrate ways computing systems implement logic, input, and output through hardware components.
Describe the issues that impact network functionality (e.g., bandwidth, load, delay, topology).
Compare ways software developers protect devices and information from unauthorized access.
Use data analysis tools and techniques to identify patterns in data representing complex systems.
Select data collection tools and techniques to generate data sets that support a claim or communicate information.
Evaluate the ability of models and simulations to test and support the refinement of hypotheses.
Implement an artificial intelligence algorithm to play a game against a human opponent or solve a problem.
Describe tradeoffs between allowing information to be public and keeping information private and secure.
Explain how abstractions hide the underlying implementation details of computing systems embedded in everyday objects.
Compare levels of abstraction and interactions between application software, system software, and hardware layers.
Develop guidelines that convey systematic troubleshooting strategies that others can use to identify and fix errors.
Evaluate the scalability and reliability of networks, by describing the relationship between routers, switches, servers, topology, and addressing.
Give examples to illustrate how sensitive data can be affected by malware and other attacks.
Recommend security measures to address various scenarios based on factors such as efficiency, feasibility, and ethical impacts.
Compare various security measures, considering tradeoffs between the usability and security of a computing system.
Explain tradeoffs when selecting and implementing cybersecurity recommendations.
Translate between different bit representations of real-world phenomena, such as characters, numbers, and images.
Evaluate the tradeoffs in how data elements are organized and where data is stored.
