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Showing 11 - 20 of 21 Standards

Standard Identifier: 9-12.AP.12

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.1)

Standard:
Design algorithms to solve computational problems using a combination of original and existing algorithms.

Descriptive Statement:
Knowledge of common algorithms improves how people develop software, secure data, and store information. Some algorithms may be easier to implement in a particular programming language, work faster, require less memory to store data, and be applicable in a wider variety of situations than other algorithms. Algorithms used to search and sort data are common in a variety of software applications. For example, students could design an algorithm to calculate and display various sports statistics and use common sorting or mathematical algorithms (e.g., average) in the design of the overall algorithm. Alternatively, students could design an algorithm to implement a game and use existing randomization algorithms to place pieces randomly in starting positions or to control the "roll" of a dice or selection of a "card" from a deck.

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.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.

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.

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.

Standard Identifier: 9-12S.AP.10

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Recognizing and Defining Computational Problems, Communicating About Computing (3.1, 7.2)

Standard:
Describe how artificial intelligence drives many software and physical systems.

Descriptive Statement:
Artificial intelligence is a sub-discipline of computer science that enables computers to solve problems previously handled by biological systems. There are many applications of artificial intelligence, including computer vision and speech recognition. Students research and explain how artificial intelligence has been employed in a given system. Students are not expected to implement an artificially intelligent system in order to meet this standard. For example, students could observe an artificially intelligent system and notice where its behavior is not human-like, such as when a character in a videogame makes a mistake that a human is unlikely to make, or when a computer easily beats even the best human players at a given game. Alternatively, students could interact with a search engine asking various questions, and after reading articles on the topic, they could explain how the computer is able to respond to queries.

Standard Identifier: 9-12S.AP.11

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Recognizing and Defining Computational Problems, Creating Computational Artifacts (3.1, 5.3)

Standard:
Implement an algorithm that uses artificial intelligence to overcome a simple challenge.

Descriptive Statement:
Artificial intelligence algorithms allow a computer to perceive and move in the world, use knowledge, and engage in problem solving. Students create a computational artifact that is able to carry out a simple task commonly performed by living organisms. Students do not need to realistically simulate human behavior or solve a complex problem in order to meet this standard. For example, students could implement an algorithm for playing tic-tac-toe that would select an appropriate location for the next move. Alternatively, students could implement an algorithm that allows a solar-powered robot to move to a sunny location when its batteries are low.

Standard Identifier: 9-12S.AP.12

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.2)

Standard:
Implement searching and sorting algorithms to solve computational problems.

Descriptive Statement:
One of the core uses of computers is to store, organize, and retrieve information when working with large amounts of data. Students create computational artifacts that use searching and/or sorting algorithms to retrieve, organize, or store information. Students do not need to select their algorithm based on efficiency. For example, students could write a script to sequence their classmates in order from youngest to oldest. Alternatively, students could write a program to find certain words within a text and report their location.

Standard Identifier: 9-12S.AP.13

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Recognizing and Defining Computational Problems (3.3)

Standard:
Evaluate algorithms in terms of their efficiency.

Descriptive Statement:
Algorithms that perform the same task can be implemented in different ways, which take different amounts of time to run on a given input set. Algorithms are commonly evaluated using asymptotic analysis (i.e., “Big O”) which involves exploration of behavior when the input set grows very large. Students classify algorithms by the most common time classes (e.g., log n, linear, n log n, and quadratic or higher). For example, students could read a given algorithm, identify the control constructs, and in conjunction with input size, identify the efficiency class of the algorithm.

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 - 20 of 21 Standards


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