Search the California Content Standards

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:
Model the role of protocols in transmitting data across networks and the Internet.

Descriptive Statement:
Protocols are rules that define how messages between computers are sent. They determine how quickly and securely information is transmitted across networks, as well as how to handle errors in transmission. Students model how data is sent using protocols to choose the fastest path and to deal with missing information. Knowledge of the details of how specific protocols work is not expected. The priority at this grade level is understanding the purpose of protocols and how they enable efficient and errorless communication. For example, students could devise a plan for sending data representing a textual message and devise a plan for resending lost information. Alternatively, students could devise a plan for sending data to represent a picture, and devise a plan for interpreting the image when pieces of the data are missing. Additionally, students could model the speed of sending messages by Bluetooth, Wi-Fi, or cellular networks and describe ways errors in data transmission can be detected and dealt with.

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:
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:
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:
Describe issues that impact network functionality.

Descriptive Statement:
Many different organizations, including educational, governmental, private businesses, and private households rely on networks to function adequately in order to engage in online commerce and activity. Quality of Service (QoS) refers to the capability of a network to provide better service to selected network traffic over various technologies from the perspective of the consumer. Students define and discuss performance measures that impact network functionality, such as latency, bandwidth, throughput, jitter, and error rate. For example, students could use online network simulators to explore how performance measures impact network functionality and describe impacts when various changes in the network occur. Alternatively, students could describe how pauses in television interviews conducted over satellite telephones are impacted by networking factors such as latency and jitter.

Standard:
Describe the design characteristics of the Internet.

Descriptive Statement:
The Internet connects devices and networks all over the world. Large-scale coordination occurs among many different machines across multiple paths every time a web page is opened or an image is viewed online. Through the domain name system (DNS), devices on the Internet can look up Internet Protocol (IP) addresses, allowing end-to-end communication between devices. The design decisions that direct the coordination among systems composing the Internet also allow for scalability and reliability. Students factor historical, cultural, and economic decisions in their explanations of the Internet. For example, students could explain how hierarchy in the DNS supports scalability and reliability. Alternatively, students could describe how the redundancy of routing between two nodes on the Internet increases reliability and scales as the Internet grows.

Standard:
Compare and contrast fundamental data structures and their uses.

Descriptive Statement:
Data structures are designed to provide different ways of storing and manipulating data sets to optimize various aspects of storage or runtime performance. Choice of data structures is made based on expected data characteristics and expected program functions. Students = compare and contrast how basic functions (e.g.., insertion, deletion, and modification) would differ for common data structures including lists, arrays, stacks, and queues. For example, students could draw a diagram of how different data structures change when items are added, deleted, or modified. They could explain tradeoffs in storage and efficiency issues. Alternatively, when presented with a description of a program and the functions it would be most likely to be running, students could list pros and cons for a specific data structure use in that scenario.

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.