Search the California Content Standards

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:
Describe how artificial intelligence drives many software and physical systems.

Descriptive Statement:
Artificial intelligence is a sub-discipline of computer science that enables computers to solve problems previously handled by biological systems. There are many applications of artificial intelligence, including computer vision and speech recognition. Students research and explain how artificial intelligence has been employed in a given system. Students are not expected to implement an artificially intelligent system in order to meet this standard. For example, students could observe an artificially intelligent system and notice where its behavior is not human-like, such as when a character in a videogame makes a mistake that a human is unlikely to make, or when a computer easily beats even the best human players at a given game. Alternatively, students could interact with a search engine asking various questions, and after reading articles on the topic, they could explain how the computer is able to respond to queries.

Standard:
Implement an algorithm that uses artificial intelligence to overcome a simple challenge.

Descriptive Statement:
Artificial intelligence algorithms allow a computer to perceive and move in the world, use knowledge, and engage in problem solving. Students create a computational artifact that is able to carry out a simple task commonly performed by living organisms. Students do not need to realistically simulate human behavior or solve a complex problem in order to meet this standard. For example, students could implement an algorithm for playing tic-tac-toe that would select an appropriate location for the next move. Alternatively, students could implement an algorithm that allows a solar-powered robot to move to a sunny location when its batteries are low.

Standard:
Implement searching and sorting algorithms to solve computational problems.

Descriptive Statement:
One of the core uses of computers is to store, organize, and retrieve information when working with large amounts of data. Students create computational artifacts that use searching and/or sorting algorithms to retrieve, organize, or store information. Students do not need to select their algorithm based on efficiency. For example, students could write a script to sequence their classmates in order from youngest to oldest. Alternatively, students could write a program to find certain words within a text and report their location.

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:
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.

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.