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Computer Science Standards




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Showing 11 - 19 of 19 Standards

Standard Identifier: 6-8.IC.22

Grade Range: 6–8
Concept: Impacts of Computing
Subconcept: Social Interactions
Practice(s): Collaborating Around Computing, Creating Computational Artifacts (2.4, 5.2)

Standard:
Collaborate with many contributors when creating a computational artifact.

Descriptive Statement:
Users have diverse sets of experiences, needs, and wants. These need to be understood and integrated into the design of computational artifacts. Students use applications that enable crowdsourcing to gather services, ideas, or content from a large group of people. At this level, crowdsourcing can be done at the local level (e.g., classroom, school, or neighborhood) and/or global level (e.g., age-appropriate online communities). For example, a group of students could use electronic surveys to solicit input from their neighborhood regarding an important social or political issue. They could collaborate with a community artist to combine animations and create a digital community collage informing the public about various points of view regarding the topic. (VAPA Visual Art 8.5.2, 8.5.4)

Standard Identifier: 9-12.AP.16

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Recognizing and Defining Computational Problems (3.2)

Standard:
Decompose problems into smaller subproblems through systematic analysis, using constructs such as procedures, modules, and/or classes.

Descriptive Statement:
Decomposition enables solutions to complex problems to be designed and implemented as more manageable subproblems. Students decompose a given problem into subproblems that can be solved using existing functionalities, or new functionalities that they design and implement. For example, students could design a program for supporting soccer coaches in analyzing their teams' statistics. They decompose the problem in terms of managing input, analysis, and output. They decompose the data organization by designing what data will be stored per player, per game, and per team. Team players may be stored as a collection. Data per team player may include: number of shots, misses, saves, assists, penalty kicks, blocks, and corner kicks. Students design methods for supporting various statistical analyses and display options. Students design output formats for individual players or coaches.

Standard Identifier: 9-12.AP.17

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.3, 5.2)

Standard:
Create computational artifacts using modular design.

Descriptive Statement:
Computational artifacts are created by combining and modifying existing computational artifacts and/or by developing new artifacts. To reduce complexity, large programs can be designed as systems of interacting modules, each with a specific role, coordinating for a common overall purpose. Students should create computational artifacts with interacting procedures, modules, and/or libraries. For example, students could incorporate a physics library into an animation of bouncing balls. Alternatively, students could integrate open-source JavaScript libraries to expand the functionality of a web application. Additionally, students could create their own game to teach Spanish vocabulary words using their own modular design (e.g., including methods to: control scoring, manage wordlists, manage access to different game levels, take input from the user, etc.).

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.

Standard Identifier: 9-12.IC.27

Grade Range: 9–12
Concept: Impacts of Computing
Subconcept: Social Interactions
Practice(s): Collaborating Around Computing (2.4)

Standard:
Use collaboration tools and methods to increase connectivity with people of different cultures and careers.

Descriptive Statement:
Increased digital connectivity and communication between people across a variety of cultures and in differing professions has changed the collaborative nature of personal and professional interaction. Students identify, explain, and use appropriate collaborative tools. For example, students could compare ways that various technological collaboration tools could help a team become more cohesive and then choose one of these tools to manage their teamwork. Alternatively, students could use different collaborative tools and methods to solicit input from not only team members and classmates but also others, such as participants in online forums or local communities.

Standard Identifier: 9-12S.AP.16

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Recognizing and Defining Computational Problems, Developing and Using Abstractions (3.2, 4.2)

Standard:
Analyze a large-scale computational problem and identify generalizable patterns or problem components that can be applied to a solution.

Descriptive Statement:
As students encounter complex, real-world problems that span multiple disciplines or social systems, they need to be able to decompose problems and apply already developed code as part of their solutions. Students decompose complex problems into manageable subproblems that could potentially be solved with programs or procedures that can be reused or already exist. For example, in analyzing an Internet radio app, students could identify that users need to create an account and enter a password. They could identify a common application programming interface (API) for checking and displaying password strength. Additionally, students could recognize that the songs would need to be sorted by the time last played in order to display the most recently played songs and identify a common API for sorting dates from most to least recent. Alternatively, in analyzing the problem of tracking medical treatment in a hospital, students could recognize that patient records need to be stored in a database and identify a database solution to support quick access and modification of patient records. Additionally, they could recognize that records in the database need to be stored securely and could identify an encryption API to support the desired level of privacy.

Standard Identifier: 9-12S.AP.17

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.3, 5.2)

Standard:
Construct solutions to problems using student-created components, such as procedures, modules, and/or objects.

Descriptive Statement:
Programmers often address complex tasks through design and decomposition using procedures and/or modules. In object-oriented programming languages, classes can support this decomposition. Students create a computational artifact that solves a problem through use of procedures, modules, and/or objects. This problem should be of sufficient complexity to benefit from decomposition and/or use of objects. For example, students could write a flashcard program in which each card is able to show both the question and answer and record user history. Alternatively, students could create a simulation of an ecosystem in which sprites carry out behaviors, such as consuming resources.

Standard Identifier: 9-12S.AP.18

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts, Testing and Refining Computational Artifacts (4.2, 5.3, 6.2)

Standard:
Demonstrate code reuse by creating programming solutions using libraries and APIs.

Descriptive Statement:
Code reuse is critical both for managing complexity in modern programs, but also in increasing programming efficiency and reliability by having programmers reuse code that has been highly vetted and tested. Software libraries allow developers to integrate common and often complex functionality without having to reimplement that functionality from scratch. Students identify, evaluate, and select appropriate application programming interfaces (APIs) from software libraries to use with a given language and operating system. They appropriately use resources such as technical documentation, online forums, and developer communities to learn about libraries and troubleshoot problems with APIs that they have chosen. For example, students could import charting and graphing modules to display data sets, adopt an online service that provides cloud storage and retrieval for a database used in a multiplayer game, or import location services into an app that identifies points of interest on a map. Libraries of APIs can be student-created or publicly available (e.g., common graphics libraries or map/navigation APIs).

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.

Showing 11 - 19 of 19 Standards


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