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Computer Science Standards




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Showing 1 - 10 of 10 Standards

Standard Identifier: K-2.DA.8

Grade Range: K–2
Concept: Data & Analysis
Subconcept: Collection, Visualization, & Transformation
Practice(s): Developing and Using Abstractions, Communicating About Computing (4.4, 7.1)

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 Identifier: K-2.IC.19

Grade Range: K–2
Concept: Impacts of Computing
Subconcept: Social Interactions
Practice(s): Collaborating Around Computing (2.1)

Standard:
Work respectfully and responsibly with others when communicating electronically.

Descriptive Statement:
Electronic communication facilitates positive interactions, such as sharing ideas with many people, but the public and anonymous nature of electronic communication also allows intimidating and inappropriate behavior in the form of cyberbullying. Responsible electronic communication includes limiting access to personably identifiable information. Students learn and use appropriate behavior when communicating electronically (often called "netiquette"). For example, students could share their work on a classroom blog or in other collaborative spaces online, taking care to avoid sharing information that is inappropriate or that could personally identify themselves to others. (CA CCSS for ELA/Literacy W.K.6, W.1.6, W.21.6) Alternatively, students could provide feedback to others on their work in a kind and respectful manner. They could learn how written words can be easily misinterpreted and may seem negative when the intention may be to express confusion, give ideas, or prompt further discussion. They could also learn to identify harmful behavior on collaborative spaces and intervening to find the proper authority to help. (CA CCSS for ELA/Literacy W.K.5, W.1.5, W.2.5) (HSS 1.1.2)

Standard Identifier: 3-5.DA.8

Grade Range: 3–5
Concept: Data & Analysis
Subconcept: Collection, Visualization, & Transformation
Practice(s): Communicating About Computing (7.1)

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 Identifier: 3-5.IC.22

Grade Range: 3–5
Concept: Impacts of Computing
Subconcept: Social Interactions
Practice(s): Fostering an Inclusive Computing Culture (1.1)

Standard:
Seek and explain the impact of diverse perspectives for the purpose of improving computational artifacts.

Descriptive Statement:
Computing technologies enable global collaboration and sharing of ideas. Students solicit feedback from a diverse group of users and creators and explain how this input improves their computational artifacts. For example, students could seek feedback from classmates via user surveys, in order to create an idea and then make a claim as to how to improve the overall structure and function of their computational artifact. Using the feedback students could write an opinion piece supporting their claim. (CA CCSS for ELA/Literacy W.3.1, W.4.1, W.5.1) Alternatively, with guidance from their teacher, students could use video conferencing tools, shared documents, or other online collaborative spaces, such as blogs, wikis, forums, or website comments, to gather and synthesize feedback from individuals and groups about programming projects. (CA CCSS for ELA/Literacy SL.3.1, SL.4.1, SL.5.1)

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: 6-8.IC.22

Grade Range: 6–8
Concept: Impacts of Computing
Subconcept: Social Interactions
Practice(s): Collaborating Around Computing, Creating Computational Artifacts (2.4, 5.2)

Standard:
Collaborate with many contributors when creating a computational artifact.

Descriptive Statement:
Users have diverse sets of experiences, needs, and wants. These need to be understood and integrated into the design of computational artifacts. Students use applications that enable crowdsourcing to gather services, ideas, or content from a large group of people. At this level, crowdsourcing can be done at the local level (e.g., classroom, school, or neighborhood) and/or global level (e.g., age-appropriate online communities). For example, a group of students could use electronic surveys to solicit input from their neighborhood regarding an important social or political issue. They could collaborate with a community artist to combine animations and create a digital community collage informing the public about various points of view regarding the topic. (VAPA Visual Art 8.5.2, 8.5.4)

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.IC.27

Grade Range: 9–12
Concept: Impacts of Computing
Subconcept: Social Interactions
Practice(s): Collaborating Around Computing (2.4)

Standard:
Use collaboration tools and methods to increase connectivity with people of different cultures and careers.

Descriptive Statement:
Increased digital connectivity and communication between people across a variety of cultures and in differing professions has changed the collaborative nature of personal and professional interaction. Students identify, explain, and use appropriate collaborative tools. For example, students could compare ways that various technological collaboration tools could help a team become more cohesive and then choose one of these tools to manage their teamwork. Alternatively, students could use different collaborative tools and methods to solicit input from not only team members and classmates but also others, such as participants in online forums or local communities.

Standard Identifier: 9-12S.DA.7

Grade Range: 9–12 Specialty
Concept: Data & Analysis
Subconcept: Collection, Visualization, & Transformation
Practice(s): Communicating About Computing (7.1)

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.

Standard Identifier: 9-12S.DA.8

Grade Range: 9–12 Specialty
Concept: Data & Analysis
Subconcept: Collection, Visualization, & Transformation
Practice(s): Developing and Using Abstractions, Communicating About Computing (4.1, 7.1)

Standard:
Use data analysis tools and techniques to identify patterns in data representing complex systems.

Descriptive Statement:
Data analysis tools can be useful for identifying patterns in large amounts of data in many different fields. Computers can help with the processing of extremely large sets of data making very complex systems manageable. Students use computational tools to analyze, summarize, and visualize a large set of data. For example, students could analyze a data set containing marathon times and determine how age, gender, weather, and course features correlate with running times. Alternatively, students could analyze a data set of social media interactions to identify the most influential users and visualize the intersections between different social groups.

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