Skip to main content
California Department of Education Logo

Computer Science Standards




Results


Showing 1 - 10 of 13 Standards

Standard Identifier: K-2.AP.11

Grade Range: K–2
Concept: Algorithms & Programming
Subconcept: Variables
Practice(s): Developing and Using Abstractions (4.4)

Standard:
Model the way programs store data.

Descriptive Statement:
Information in the real world can be represented in computer programs. Students model the digital storage of data by transforming real-world information into symbolic representations that include text, numbers, and images. For example, after identifying symbols on a map and explaining what they represent in the real world, students could create their own symbols and corresponding legend to represent items on a map of their classroom (HSS.K.4.3, 1.2.3, 2.2.2) Alternatively, students could invent symbols to represent beat and/or pitch. Students could then modify symbols within the notation and explain how the musical phrase changes. (VAPA Music K.1.1, 1.1.1, 2.1.1, 2.2.2)

Standard Identifier: K-2.CS.3

Grade Range: K–2
Concept: Computing Systems
Subconcept: Troubleshooting
Practice(s): Testing and Refining Computational Artifacts, Communicating About Computing (6.2, 7.2)

Standard:
Describe basic hardware and software problems using accurate terminology.

Descriptive Statement:
Problems with computing systems have different causes. Accurate description of the problem aids users in finding solutions. Students communicate a problem with accurate terminology (e.g., when an app or program is not working as expected, a device will not turn on, the sound does not work, etc.). Students at this level do not need to understand the causes of hardware and software problems. For example, students could sort hardware and software terms on a word wall, and refer to the word wall when describing problems using "I see..." statements (e.g., "I see the pointer on the screen is missing", "I see that the computer will not turn on"). (CA CCSS for ELA/Literacy L.K.5.A, L.1.5.A, SL K.5, SL1.5, SL 2.5) (Visual Arts Kinder 5.2) Alternatively, students could use appropriate terminology during collaborative conversations as they learn to debug, troubleshoot, collaborate, and think critically with technology. (CA CCSS for ELA/Literacy SL.K.1, SL.1.1, SL.2.1)

Standard Identifier: K-2.DA.7

Grade Range: K–2
Concept: Data & Analysis
Subconcept: Storage
Practice(s): Developing and Using Abstractions (4.2)

Standard:
Store, copy, search, retrieve, modify, and delete information using a computing device, and define the information stored as data.

Descriptive Statement:
Information from the real world can be stored and processed by a computing device. When stored on a computing device, it is referred to as data. Data can include images, text documents, audio files, and video files. Students store, copy, search, retrieve, modify, and delete information using a computing device and define the information stored as data. For example, students could produce a story using a computing device, storing it locally or remotely (e.g., in the cloud). They could then make a copy of the story for peer revision and editing. When the final copy of the story is complete, students delete any unnecessary files. They search for and retrieve data from a local or remote source, depending on where it was stored. (CA CCSS for ELA/Literacy W.K.6, W.K.5, W1.6, W.1.5, W.2.6, W.2.5) Alternatively, students could record their voices singing an age-appropriate song. They could store the data on a computing device, search for peers' audio files, retrieve their own files, and delete unnecesary takes. (VAPA Music K.2.2, 1.2.2, 2.2.2)

Standard Identifier: K-2.DA.9

Grade Range: K–2
Concept: Data & Analysis
Subconcept: Inference & Models
Practice(s): Developing and Using Abstractions (4.1)

Standard:
Identify and describe patterns in data visualizations, such as charts or graphs, to make predictions.

Descriptive Statement:
Data can be used to make inferences or predictions about the world. For example, students could record the number of each color of candy in a small packet. Then, they compare their individual data with classmates. Students could use the collected data to predict how many of each colored candy will be in a full size bag of like candy. (CA CCSS for Mathematics K.MD.3, 1.MD.4, 2.MD.10) Alternatively, students could sort and classify objects according to their properties and note observations. Students could then create a graph or chart of their observations and look for connections/relationships (e.g., items that are hard are usually also smooth, or items that are fluffy are usually also light in weight.) Students then look at pictures of additional objects and make predictions regarding the properties of the objects pictured. (CA NGSS: 2-PS1-1, 2-PS1-2)

Standard Identifier: 3-5.DA.7

Grade Range: 3–5
Concept: Data & Analysis
Subconcept: Storage
Practice(s): Developing and Using Abstractions (4.2)

Standard:
Explain that the amount of space required to store data differs based on the type of data and/or level of detail.

Descriptive Statement:
All saved data requires space to store it, whether locally or not (e.g., on the cloud). Music, images, video, and text require different amounts of storage. Video will often require more storage and different format than music or images alone because video combines both. The level of detail represented by that data also affects storage requirements. For instance, two pictures of the same object can require different amounts of storage based upon their resolution, and a high-resolution photo could require more storage than a low-resolution video. Students select appropriate storage for their data. For example, students could create an image using a standard drawing app. They could save the image in different formats (e.g., .png, .jpg, .pdf) and compare file sizes. They should also notice that different file sizes can result in differences in quality or resolution (e.g., some pictures could be more pixelated while some could be sharper). Alternatively, in an unplugged activity, students could represent images by coloring in squares within a large grid. They could model how a larger grid requires more storage but also represents a clearer image (i.e., higher resolution).

Standard Identifier: 3-5.DA.9

Grade Range: 3–5
Concept: Data & Analysis
Subconcept: Inference & Models
Practice(s): Communicating About Computing (7.1)

Standard:
Use data to highlight and/or propose relationships, predict outcomes, or communicate ideas.

Descriptive Statement:
The accuracy of data analysis is related to how the data is represented. Inferences or predictions based on data are less likely to be accurate if the data is insufficient, incomplete, or inaccurate or if the data is incorrect in some way. Additionally, people select aspects and subsets of data to be transformed, organized, and categorized. Students should be able to refer to data when communicating an idea, in order to highlight and/or propose relationships, predict outcomes, highlight different views and/or communicate insights and ideas. For example, students can be provided a scenario in which they are city managers who have a specific amount of funds to improve a city in California. Students can collect data of a city concerning land use, vegetation, wildlife, climate, population density, services and transportation (HSS.4.1.5) to determine and present what area needs to be focused on to improve a problem. Students can compare their data and planned use of funds with peers, clearly communicating or predict outcomes based on data collected. (CA CCCS for ELA/Literacy SL.3.1, SL.4.1, SL.5.1) Alternatively, students could record the temperature at noon each day to show that temperatures are higher in certain months of the year. If temperatures are not recorded on non-school days or are recorded incorrectly, the data would be incomplete and ideas being communicated could be inaccurate. Students may also record the day of the week on which the data was collected, but this would have no relevance to whether temperatures are higher or lower. In order to have sufficient and accurate data on which to communicate the idea, students might use data provided by a governmental weather agency. (CA NGSS: 3-ESS2-1)

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.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.13

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Variables
Practice(s): Developing and Using Abstractions (4.1)

Standard:
Create more generalized computational solutions using collections instead of repeatedly using simple variables.

Descriptive Statement:
Computers can automate repetitive tasks with algorithms that use collections to simplify and generalize computational problems. Students identify common features in multiple segments of code and substitute a single segment that uses collections (i.e., arrays, sets, lists) to account for the differences. For example, students could take a program that inputs students' scores into multiple variables and modify it to read these scores into a single array of scores. Alternatively, instead of writing one procedure to find averages of student scores and another to find averages of student absences, students could write a single general average procedure to support both tasks.

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.

Showing 1 - 10 of 13 Standards


Questions: Curriculum Frameworks and Instructional Resources Division | CFIRD@cde.ca.gov | 916-319-0881