Computer Science Standards
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Showing 11 - 13 of 13 Standards
Standard Identifier: 9-12S.AP.23
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.3)
Standard:
Modify an existing program to add additional functionality and discuss intended and unintended implications.
Descriptive Statement:
Modularity and code reuse is key in modern software. However, when code is modified, the programmer should consider relevant situations in which this code might be used in other places. Students create and document modifications to existing programs that enhance functionality, and then identify, document, and correct unintended consequences. For example, students could take an existing a procedure that calculates the average of a set of numbers and returns an integer (which lacks precision) and modify it to return a floating-point number instead. The student would explain how the change might impact multiple scenarios.
Modify an existing program to add additional functionality and discuss intended and unintended implications.
Descriptive Statement:
Modularity and code reuse is key in modern software. However, when code is modified, the programmer should consider relevant situations in which this code might be used in other places. Students create and document modifications to existing programs that enhance functionality, and then identify, document, and correct unintended consequences. For example, students could take an existing a procedure that calculates the average of a set of numbers and returns an integer (which lacks precision) and modify it to return a floating-point number instead. The student would explain how the change might impact multiple scenarios.
Standard Identifier: 9-12S.AP.24
Grade Range:
9–12 Specialty
Concept:
Algorithms & Programming
Subconcept:
Program Development
Practice(s):
Testing and Refining Computational Artifacts (6.3)
Standard:
Evaluate key qualities of a program through a process such as a code review.
Descriptive Statement:
Code reviews are a common software industry practice and valuable for developing technical communication skills. Key qualities of code include correctness, usability, readability, efficiency, and scalability. Students walk through code they created and explain how it works. Additionally, they follow along when someone else is explaining their code and ask appropriate questions. For example, students could present their code to a group or visually inspect code in pairs. Alternatively, in response to another student's presentation, students could provide feedback including comments on correctness of the code, comments on how code interacts with code that calls it, and design and documentation features.
Evaluate key qualities of a program through a process such as a code review.
Descriptive Statement:
Code reviews are a common software industry practice and valuable for developing technical communication skills. Key qualities of code include correctness, usability, readability, efficiency, and scalability. Students walk through code they created and explain how it works. Additionally, they follow along when someone else is explaining their code and ask appropriate questions. For example, students could present their code to a group or visually inspect code in pairs. Alternatively, in response to another student's presentation, students could provide feedback including comments on correctness of the code, comments on how code interacts with code that calls it, and design and documentation features.
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.
Showing 11 - 13 of 13 Standards
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