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Showing 11 - 20 of 21 Standards

Standard Identifier: 6-8.DA.7

Grade Range: 6–8
Concept: Data & Analysis
Subconcept: Storage
Practice(s): Developing and Using Abstractions (4.4)

Standard:
Represent data in multiple ways.

Descriptive Statement:
Computers store data as sequences of 0s and 1s (bits). Software translates to and from this low-level representation to higher levels that are understandable by people. Furthermore, higher level data can be represented in multiple ways, such as the digital display of a color and its corresponding numeric RGB value, or a bar graph, a pie chart, and table representation of the same data in a spreadsheet. For example, students could use a color picker to explore the correspondence between the digital display or name of a color (high-level representations) and its RGB value or hex code (low-level representation). Alternatively, students could translate a word (high-level representation) into Morse code or its corresponding sequence of ASCII codes (low-level representation).

Standard Identifier: 6-8.DA.9

Grade Range: 6–8
Concept: Data & Analysis
Subconcept: Inference & Models
Practice(s): Developing and Using Abstractions, Testing and Refining Computational Artifacts (4.4, 6.1)

Standard:
Test and analyze the effects of changing variables while using computational models.

Descriptive Statement:
Variables within a computational model may be changed, in order to alter a computer simulation or to more accurately represent how various data is related. Students interact with a given model, make changes to identified model variables, and observe and reflect upon the results. For example, students could test a program that makes a robot move on a track by making changes to variables (e.g., height and angle of track, size and mass of the robot) and discussing how these changes affect how far the robot travels. (CA NGSS: MS-PS2-2) Alternatively, students could test a game simulation and change variables (e.g., skill of simulated players, nature of opening moves) and analyze how these changes affect who wins the game. (CA NGSS: MS-ETS1-3) Additionally, students could modify a model for predicting the likely color of the next pick from a bag of colored candy and analyze the effects of changing variables representing the common color ratios in a typical bag of candy. (CA CCSS for Mathematics 7.SP.7, 8.SP.4)

Standard Identifier: 9-12.AP.14

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Control
Practice(s): Creating Computational Artifacts (5.2)

Standard:
Justify the selection of specific control structures by identifying tradeoffs associated with implementation, readability, and performance.

Descriptive Statement:
The selection of control structures in a given programming language impacts readability and performance. Readability refers to how clear the program is to other programmers and can be improved through documentation. Control structures at this level may include, for example, conditional statements, loops, event handlers, and recursion. Students justify control structure selection and tradeoffs in the process of creating their own computational artifacts. The discussion of performance is limited to a theoretical understanding of execution time and storage requirements; a quantitative analysis is not expected. For example, students could compare the readability and program performance of iterative and recursive implementations of procedures that calculate the Fibonacci sequence. Alternatively, students could compare the readability and performance tradeoffs of multiple if statements versus a nested if statement.

Standard Identifier: 9-12.AP.15

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Control
Practice(s): Creating Computational Artifacts (5.1, 5.2, 5.3)

Standard:
Iteratively design and develop computational artifacts for practical intent, personal expression, or to address a societal issue by using events to initiate instructions.

Descriptive Statement:
In this context, relevant computational artifacts can include programs, mobile apps, or web apps. Events can be user-initiated, such as a button press, or system-initiated, such as a timer firing. For example, students might create a tool for drawing on a canvas by first implementing a button to set the color of the pen. Alternatively, students might create a game where many events control instructions executed (e.g., when a score climbs above a threshold, a congratulatory sound is played; when a user clicks on an object, the object is loaded into a basket; when a user clicks on an arrow key, the player object is moved around the screen).

Standard Identifier: 9-12.CS.1

Grade Range: 9–12
Concept: Computing Systems
Subconcept: Devices
Practice(s): Developing and Using Abstractions (4.1)

Standard:
Describe ways in which abstractions hide the underlying implementation details of computing systems to simplify user experiences.

Descriptive Statement:
An abstraction is a representation of an idea or phenomenon that hides details irrelevant to the question at hand. Computing systems, both stand alone and embedded in products, are often integrated with other systems to simplify user experiences. For example, students could identify geolocation hardware embedded in a smartphone and describe how this simplifies the users experience since the user does not have to enter her own location on the phone. Alternatively, students might select an embedded device such as a car stereo, identify the types of data (e.g., radio station presets, volume level) and procedures (e.g., increase volume, store/recall saved station, mute) it includes, and explain how the implementation details are hidden from the user.

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.DA.8

Grade Range: 9–12
Concept: Data & Analysis
Subconcept: Storage
Practice(s): Developing and Using Abstractions (4.1)

Standard:
Translate between different representations of data abstractions of real-world phenomena, such as characters, numbers, and images.

Descriptive Statement:
Computers represent complex real-world concepts such as characters, numbers, and images through various abstractions. Students translate between these different levels of data representations. For example, students could convert an HTML (Hyper Text Markup Language) tag for red font into RGB (Red Green Blue), HEX (Hexadecimal Color Code), HSL (Hue Saturation Lightness), RGBA( Red Green Blue Alpha), or HSLA (Hue Saturation Lightness and Alpha) representations. Alternatively, students could convert the standard representation of a character such as ! into ASCII or Unicode.

Standard Identifier: 9-12.DA.9

Grade Range: 9–12
Concept: Data & Analysis
Subconcept: Storage
Practice(s): Recognizing and Defining Computational Problems (3.3)

Standard:
Describe tradeoffs associated with how data elements are organized and stored.

Descriptive Statement:
People make choices about how data elements are organized and where data is stored. These choices affect cost, speed, reliability, accessibility, privacy, and integrity. Students describe implications for a given data organziation or storage choice in light of a specific problem. For example, students might consider the cost, speed, reliability, accessibility, privacy, and integrity tradeoffs between storing photo data on a mobile device versus in the cloud. Alternatively, students might compare the tradeoffs between file size and image quality of various image file formats and how choice of format may be infuenced by the device on which it is to be accessed (e.g., smartphone, computer).

Standard Identifier: 9-12S.AP.15

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Control
Practice(s): Recognizing and Defining Computational Problems, Communicating About Computing (3.2, 7.2)

Standard:
Demonstrate the flow of execution of a recursive algorithm.

Descriptive Statement:
Recursion is a powerful problem-solving approach where the problem solution is built on solutions of smaller instances of the same problem. A base case, which returns a result without referencing itself, must be defined, otherwise infinite recursion will occur. Students represent a sequence of calls to a recursive algorithm and show how the process resolves to a solution. For example, students could draw a diagram to illustrate flow of execution by keeping track of parameter and returned values for each recursive call. Alternatively, students could create a video showing the passing of arguments as the recursive algorithm runs.

Standard Identifier: 9-12S.CS.1

Grade Range: 9–12 Specialty
Concept: Computing Systems
Subconcept: Devices
Practice(s): Developing and Using Abstractions, Communicating About Computing (4.4, 7.2)

Standard:
Illustrate ways computing systems implement logic through hardware components.

Descriptive Statement:
Computing systems use processors (e.g., a central processing unit or CPU) to execute program instructions. Processors are composed of components that implement the logical or computational operations required by the instructions. AND, OR, and NOT are examples of logic gates. Adders are examples of higher-leveled circuits built using low-level logic gates. Students illustrate how modern computing devices are made up of smaller and simpler components which implement the logic underlying the functionality of a computer processor. At this level, knowledge of how logic gates are constructed is not expected. For example, students could construct truth tables, draw logic circuit diagrams, or use an online logic circuit simulator. Students could explore the interaction of the CPU, RAM, and I/O by labeling a diagram of the von Neumann architecture. Alternatively, students could design higher-level circuits using low-level logic gates (e.g., adders).

Showing 11 - 20 of 21 Standards


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