Computer Science Standards
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Showing 1 - 9 of 9 Standards
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)
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)
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).
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: 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).
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)
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.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.
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.
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).
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.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.
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.
Questions: Curriculum Frameworks and Instructional Resources Division |
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