Search the California Content Standards

Standard:
Decompose the steps needed to solve a problem into a sequence of instructions.

Descriptive Statement:
Decomposition is the act of breaking down tasks into simpler tasks. For example, students could break down the steps needed to make a peanut butter and jelly sandwich, to brush their teeth, to draw a shape, to move a character across the screen, or to solve a level of a coding app. In a visual programming environment, students could break down the steps needed to draw a shape. (CA CCSS for Mathematics K.G.5, 1.G.1, 2.G.1) Alternatively, students could decompose the planning of a birthday party into tasks such as: 1) Decide when and where it should be, 2) List friends and family to invite, 3) Send the invitations, 4) Bake a cake, 5) Decorate, etc.

Standard:
Collect and present data in various visual formats.

Descriptive Statement:
Data can be collected and presented in various visual formats. For example, students could measure temperature changes throughout a day. They could then discuss ways to display the data visually. Students could extend the activity by writing different narratives based on collected data, such as a story that begins in the morning when temperatures are low and one that begins in the afternoon when the sun is high and temperatures are higher. (CA CCSS for ELA/Literacy RL.K.9, RL.1.9, RL.2.9, W.K.3, W.1.3, W.2.3). Alternatively, students collect peers' favorite flavor of ice cream and brainstorm differing ways to display the data. In groups, students can choose to display and present the data in a format of their choice. (CA CCSS for Mathematics K.MD.3, 1.MD.4, 2.MD.10)

Standard:
Decompose problems into smaller, manageable tasks which may themselves be decomposed.

Descriptive Statement:
Decomposition is the act of breaking down tasks into simpler tasks. This manages complexity in the problem solving and program development process. For example, students could create an animation to represent a story they have written. Students write a story and then break it down into different scenes. For each scene, they would select a background, place characters, and program actions in that scene. (CA CCSS for ELA/Literacy W.3.3, W.4.3, W.5.3) Alternatively, students could create a program to allow classmates to present data collected in an experiment. For example, if students collected rain gauge data once per week for 3 months, students could break down the program tasks: 1) ask the user to input 12 weeks' worth of data, 2) process the data (e.g., add the first four entries to calculate the rain amount for month 1, convert to metric system measurements), and 3) direct the creation or resizing of objects (e.g., one rectangular chart bar for each month) to represent the total number of rainfall for that month. (CA NGSS: 3-ETS-1-2) (CA CCSS for Mathematics 3.MD.2)

Standard:
Organize and present collected data visually to highlight relationships and support a claim.

Descriptive Statement:
Raw data has little meaning on its own. Data is often sorted or grouped to provide additional clarity. Organizing data can make interpreting and communicating it to others easier. Data points can be clustered by a number of commonalities. The same data could be manipulated in different ways to emphasize particular aspects or parts of the data set. For example, students could create and administer electronic surveys to their classmates. Possible topics could include favorite books, family heritage, and after school activities. Students could then create digital displays of the data they have collected such as column histogram charts showing the percent of respondents in each grade who selected a particular favorite book. Finally, students could make quantitative statements supported by the data such as which books are more appealing to specific ages of students. As an extension, students could write an opinion piece stating a claim and supporting it with evidence from the data they collected. (CA CCSS for Mathematics 3.MD.3, 4.MD.4, 5.MD.2) (CA CCSS for ELA/Literacy W.3.1, W.4.1, W.5.1) Alternatively, students could represent data in tables and graphical displays to describe weather experienced in the last several years. They could select the type of graphical display based on the specific data represented (e.g., daily high/low temperatures on a scatter plot, average temperatures for a month across years in a column chart). Students could then make a claim about expected weather in future months based on the data. (CA NGSS: 3-ESS2-1)

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:
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:
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:
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:
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:
Select and use data collection tools and techniques to generate data sets.

Descriptive Statement:
Data collection and organization is essential for obtaining new information insights and revealing new knowledge in our modern world. As computers are able to process larger sets of data, gathering data in an efficient and reliable matter remains important. The choice of data collection tools and quality of the data collected influences how new information, insights, and knowledge will support claims and be communicated. Students devise a reliable method to gather information, use software to extract digital data from data sets, and clean and organize the data in ways that support summaries of information obtained from the data. At this level, students may, but are not required to, create their own data collection tools. For example, students could create a computational artifact that records information from a sonic distance sensor to monitor the motion of a prototype vehicle. Alternatively, students could develop a reliable and practical way to automatically digitally record the number of animals entering a portion of a field to graze. Additionally, students could also find a web site containing data (e.g., race results for a major marathon), scrape the data from the web site using data collection tools, and format the data so it can be analyzed.