Computer Science Standards
Results
Showing 11 - 20 of 23 Standards
Standard Identifier: 6-8.IC.21
Grade Range:
6–8
Concept:
Impacts of Computing
Subconcept:
Culture
Practice(s):
Fostering an Inclusive Computing Culture (1.2)
Standard:
Discuss issues of bias and accessibility in the design of existing technologies.
Descriptive Statement:
Computing technologies should support users of many backgrounds and abilities. In order to maximize accessiblity, these differences need to be addressed by examining diverse populations. With the teacher's guidance, students test and discuss the usability of various technology tools, such as apps, games, and devices. For example, students could discuss the impacts of facial recognition software that works better for lighter skin tones and recognize that the software was likely developed with a homogeneous testing group. Students could then discuss how accessibility could be improved by sampling a more diverse population. (CA CCSS for ELA/Literacy SL.6.1, SL.7.1, SL.8.1)
Discuss issues of bias and accessibility in the design of existing technologies.
Descriptive Statement:
Computing technologies should support users of many backgrounds and abilities. In order to maximize accessiblity, these differences need to be addressed by examining diverse populations. With the teacher's guidance, students test and discuss the usability of various technology tools, such as apps, games, and devices. For example, students could discuss the impacts of facial recognition software that works better for lighter skin tones and recognize that the software was likely developed with a homogeneous testing group. Students could then discuss how accessibility could be improved by sampling a more diverse population. (CA CCSS for ELA/Literacy SL.6.1, SL.7.1, SL.8.1)
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.
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.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.IC.23
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Culture
Practice(s):
Fostering an Inclusive Computing Culture, Recognizing and Defining Computational Problems (1.2, 3.1)
Standard:
Evaluate the ways computing impacts personal, ethical, social, economic, and cultural practices.
Descriptive Statement:
Computing may improve, harm, or maintain practices. An understanding of how equity deficits, such as minimal exposure to computing, access to education, and training opportunities, are related to larger, systemic problems in society enables students to create more meaningful artifacts. Students illustrate the positive, negative, and/or neutral impacts of computing. For example, students could evaluate the accessibility of a product for a broad group of end users, such as people who lack access to broadband or who have various disabilities. Students could identify potential bias during the design process and evaluate approaches to maximize accessibility in product design. Alternatively, students could evaluate the impact of social media on cultural, economic, and social practices around the world.
Evaluate the ways computing impacts personal, ethical, social, economic, and cultural practices.
Descriptive Statement:
Computing may improve, harm, or maintain practices. An understanding of how equity deficits, such as minimal exposure to computing, access to education, and training opportunities, are related to larger, systemic problems in society enables students to create more meaningful artifacts. Students illustrate the positive, negative, and/or neutral impacts of computing. For example, students could evaluate the accessibility of a product for a broad group of end users, such as people who lack access to broadband or who have various disabilities. Students could identify potential bias during the design process and evaluate approaches to maximize accessibility in product design. Alternatively, students could evaluate the impact of social media on cultural, economic, and social practices around the world.
Standard Identifier: 9-12.IC.24
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Culture
Practice(s):
Fostering an Inclusive Computing Culture (1.2)
Standard:
Identify impacts of bias and equity deficit on design and implementation of computational artifacts and apply appropriate processes for evaluating issues of bias.
Descriptive Statement:
Biases could include incorrect assumptions developers have made about their users, including minimal exposure to computing, access to education, and training opportunities. Students identify and use strategies to test and refine computational artifacts with the goal of reducing bias and equity deficits and increasing universal access. For example, students could use a spreadsheet to chart various forms of equity deficits, and identify solutions in existing software. Students could use and refine the spreadsheet solutions to create a strategy for methodically testing software specifically for bias and equity.
Identify impacts of bias and equity deficit on design and implementation of computational artifacts and apply appropriate processes for evaluating issues of bias.
Descriptive Statement:
Biases could include incorrect assumptions developers have made about their users, including minimal exposure to computing, access to education, and training opportunities. Students identify and use strategies to test and refine computational artifacts with the goal of reducing bias and equity deficits and increasing universal access. For example, students could use a spreadsheet to chart various forms of equity deficits, and identify solutions in existing software. Students could use and refine the spreadsheet solutions to create a strategy for methodically testing software specifically for bias and equity.
Standard Identifier: 9-12.IC.25
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Culture
Practice(s):
Recognizing and Defining Computational Problems (3.1)
Standard:
Demonstrate ways a given algorithm applies to problems across disciplines.
Descriptive Statement:
Students identify how a given algorithm can be applied to real-world problems in different disciplines. For example, students could demonstrate how a randomization algorithm can be used to select participants for a clinical medical trial or to select a flash card to display on a vocabulary quiz. Alternatively, students could demonstrate how searching and sorting algorithms are needed to organize records in manufacturing settings, or to support doctors queries of patient records, or to help governments manage support services they provide to their citizens.
Demonstrate ways a given algorithm applies to problems across disciplines.
Descriptive Statement:
Students identify how a given algorithm can be applied to real-world problems in different disciplines. For example, students could demonstrate how a randomization algorithm can be used to select participants for a clinical medical trial or to select a flash card to display on a vocabulary quiz. Alternatively, students could demonstrate how searching and sorting algorithms are needed to organize records in manufacturing settings, or to support doctors queries of patient records, or to help governments manage support services they provide to their citizens.
Standard Identifier: 9-12.IC.26
Grade Range:
9–12
Concept:
Impacts of Computing
Subconcept:
Culture
Practice(s):
Communicating About Computing (7.2)
Standard:
Study, discuss, and think critically about the potential impacts and implications of emerging technologies on larger social, economic, and political structures, with evidence from credible sources.
Descriptive Statement:
For example, after studying the rise of artifical intelligence, students create a cause and effect chart to represent positive and negative impacts of this technology on society.
Study, discuss, and think critically about the potential impacts and implications of emerging technologies on larger social, economic, and political structures, with evidence from credible sources.
Descriptive Statement:
For example, after studying the rise of artifical intelligence, students create a cause and effect chart to represent positive and negative impacts of this technology on society.
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.
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.
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.
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.
Showing 11 - 20 of 23 Standards
Questions: Curriculum Frameworks and Instructional Resources Division |
CFIRD@cde.ca.gov | 916-319-0881