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Showing 11 - 20 of 29 Standards

Standard Identifier: 6-8.AP.13

Grade Range: 6–8
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Recognizing and Defining Computational Problems (3.2)

Standard:
Decompose problems and subproblems into parts to facilitate the design, implementation, and review of programs.

Descriptive Statement:
Decomposition facilitates program development by allowing students to focus on one piece at a time (e.g., getting input from the user, processing the data, and displaying the result to the user). Decomposition also enables different students to work on different parts at the same time. Students break down (decompose) problems into subproblems, which can be further broken down to smaller parts. Students could create an arcade game, with a title screen, a game screen, and a win/lose screen with an option to play the game again. To do this, students need to identify subproblems that accompany each screen (e.g., selecting an avatar goes in the title screen, events for controlling character action and scoring goes in the game screen, and displaying final and high score and asking whether to play again goes in the win/lose screen). Alternatively, students could decompose the problem of calculating and displaying class grades. Subproblems might include: accept input for students grades on various assignments, check for invalid grade entries, calculate per assignment averages, calculate per student averages, and display histograms of student scores for each assignment. (CA CCSS for Mathematics 6.RP.3c, 6.SP.4, 6.SP.5)

Standard Identifier: 6-8.AP.14

Grade Range: 6–8
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Developing and Using Abstractions (4.1, 4.3)

Standard:
Create procedures with parameters to organize code and make it easier to reuse.

Descriptive Statement:
Procedures support modularity in developing programs. Parameters can provide greater flexibility, reusability, and efficient use of resources. Students create procedures and/or functions that are used multiple times within a program to repeat groups of instructions. They generalize the procedures and/or functions by defining parameters that generate different outputs for a wide range of inputs. For example, students could create a procedure to draw a circle which involves many instructions, but all of them can be invoked with one instruction, such as “drawCircle.” By adding a radius parameter, students can easily draw circles of different sizes. (CA CCSS for Mathematics 7.G.4) Alternatively, calculating the area of a regular polygon requires multiple steps. Students could write a function that accepts the number and length of the sides as parameters and then calculates the area of the polygon. This function can then be re-used inside any program to calculate the area of a regular polygon. (CA CCSS for Mathematics 6.G.1)

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.8

Grade Range: 6–8
Concept: Data & Analysis
Subconcept: Collection, Visualization, & Transformation
Practice(s): Communicating About Computing (7.1)

Standard:
Collect data using computational tools and transform the data to make it more useful.

Descriptive Statement:
Data collection has become easier and more ubiquitous. The cleaning of data is an important transformation for ensuring consistent format, reducing noise and errors (e.g., removing irrelevant responses in a survey), and/or making it easier for computers to process. Students build on their ability to organize and present data visually to support a claim, understanding when and how to transform data so information can be more easily extracted. Students also transform data to highlight or expose relationships. For example, students could use computational tools to collect data from their peers regarding the percentage of time technology is used for school work and entertainment, and then create digital displays of their data and findings. Students could then transform the data to highlight relationships representing males and females as percentages of a whole instead of as individual counts. (CA CCSS for Mathematics 6.SP.4, 7.SP.3, 8.SP.1, 8.SP.4) Alternatively, students could collect data from online forms and surveys, from a sensor, or by scraping a web page, and then transform the data to expose relationships. They could highlight the distribution of data (e.g., words on a web page, readings from a sensor) by giving quantitative measures of center and variability. (CA CCSS for Mathematics 6.SP.5.c, 7.SP.4)

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.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.10

Grade Range: 9–12
Concept: Data & Analysis
Subconcept: Collection, Visualization, & Transformation
Practice(s): Creating Computational Artifacts (5.2)

Standard:
Create data visualizations to help others better understand real-world phenomena.

Descriptive Statement:
People transform, generalize, simplify, and present large data sets in different ways to influence how other people interpret and understand the underlying information. Students select relevant data from large or complex data sets in support of a claim or to communicate the information in a more sophisticated manner. Students use software tools or programming to perform a range of mathematical operations to transform and analyze data and create powerful data visualizations (that reveal patterns in the data). For example, students could create data visualizations to reveal patterns in voting data by state, gender, political affiliation, or socioeconomic status. Alternatively, students could use U.S. government data on criticially endangered animals to visualize population change over time.

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).

Showing 11 - 20 of 29 Standards


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