Search the California Content Standards

Standard:
Evaluate algorithms in terms of their efficiency.

Descriptive Statement:
Algorithms that perform the same task can be implemented in different ways, which take different amounts of time to run on a given input set. Algorithms are commonly evaluated using asymptotic analysis (i.e., “Big O”) which involves exploration of behavior when the input set grows very large. Students classify algorithms by the most common time classes (e.g., log n, linear, n log n, and quadratic or higher). For example, students could read a given algorithm, identify the control constructs, and in conjunction with input size, identify the efficiency class of the algorithm.

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.

Standard:
Examine the scalability and reliability of networks, by describing the relationship between routers, switches, servers, topology, and addressing.

Descriptive Statement:
Choice of network topology is determined, in part, by how many devices can be supported and the character of communication needs between devices. Each device is assigned an address that uniquely identifies it on the network. Routers function by comparing addresses to determine how information on the network should reach its desgination. Switches compare addresses to determine which computers will receive information. Students explore and explain how network performance degrades when various factors affect the network. For example, students could use online network simulators to describe how network performance changes when the number of devices increases. Alternatively, students could visualize and describe changes to the distribution of network traffic when a router on the network fails.

Standard:
Explain how the characteristics of the Internet influence the systems developed on it.

Descriptive Statement:
The design of the Internet includes hierarchy and redundancy to help it scale reliably. An end-to-end architecture means that key functions are placed at endpoints in the network (i.e., an Internet user's computer and the server hosting a website) rather than in the middle of the network. Open standards for transmitting information across the Internet help fuel its growth. This design philosophy impacts systems and technologies that integrate with the Internet. Students explain how Internet-based systems depend on these characteristics. For example, students could explain how having common, standard protocols enable products and services from different developers to communicate. Alternatively, students could describe how the end-to-end architecture and redundancy in routing enables Internet users to access information and services even if part of the network is down; the information can still be routed from one end to another through a different path.