Search the California Content Standards

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)

Standard:
Develop guidelines that convey systematic troubleshooting strategies that others can use to identify and fix errors.

Descriptive Statement:
Troubleshooting complex problems involves the use of multiple sources when researching, evaluating, and implementing potential solutions. Troubleshooting also relies on experience, such as when people recognize that a problem is similar to one they have seen before and adapt solutions that have worked in the past. For example, students could create a list of troubleshooting strategies to debug network connectivity problems such as checking hardware and software status and settings, rebooting devices, and checking security settings. Alternatively, students could create troubleshooting guidelines for help desk employees based on commonly observed problems (e.g., problems connecting a new device to the computer, problems printing from a computer to a network printer).

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:
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:
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:
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:
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:
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:
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:
Evaluate computational artifacts with regard to improving their beneficial effects and reducing harmful effects on society.

Descriptive Statement:
People design computational artifacts to help make the lives of humans better. Students evaluate an artifact and comment on aspects of it which positively or negatively impact users and give ideas for reducing the possible negative impacts. For example, students could discuss how algorithms that screen job candidates' resumes can cut costs for companies (a beneficial effect) but introduce or amplify bias in the hiring process (a harmful effect). Alternatively, students could discuss how turn-by-turn navigation tools can help drivers avoid traffic and find alternate routes (a beneficial effect), but sometimes channel large amounts of traffic down small neighborhood streets (a harmful effect). Additionally, students could discuss how social media algorithms can help direct users' attention to interesting content (a beneficial effect), while simultaneously limiting users' exposure to information that contradicts pre-existing beliefs (a harmful effect).