Search the California Content Standards

Standard:
Explain the privacy concerns related to the collection and generation of data through automated processes.

Descriptive Statement:
Data can be collected and aggregated across millions of people, even when they are not actively engaging with or physically near the data collection devices. Students recognize automated and non-evident collection of information and the privacy concerns they raise for individuals. For example, students could explain the impact on an individual when a social media site's security settings allows for mining of account information even when the user is not online. Alternatively, students could discuss the impact on individuals of using surveillance video in a store to track customers. Additionally, students could discuss how road traffic can be monitored to change signals in real time to improve road efficiency without drivers being aware and discuss policies for retaining data that identifies drivers' cars and their behaviors.

Standard:
Evaluate the social and economic implications of privacy in the context of safety, law, or ethics.

Descriptive Statement:
Laws govern many aspects of computing, such as privacy, data, property, information, and identity. International differences in laws and ethics have implications for computing. Students make and justify claims about potential and/or actual privacy implications of policies, laws, or ethics and consider the associated tradeoffs, focusing on society and the economy. For example, students could explore the case of companies tracking online shopping behaviors in order to decide which products to target to consumers. Students could evaluate the ethical and legal dilemmas of collecting such data without consumer knowledge in order to profit companies. Alternatively, students could evaluate the implications of net neutrality laws on society's access to information and on the impacts to businesses of varying sizes.

Standard:
Compare and contrast security measures to address various security threats.

Descriptive Statement:
Network security depends on a combination of hardware, software, and practices that control access to data and systems. The needs of users and the sensitivity of data determine the level of security implemented. Potential security problems, such as denial-of-service attacks, ransomware, viruses, worms, spyware, and phishing, present threats to sensitive data. Students compare and contrast different types of security measures based on factors such as efficiency, feasibility, ethical impacts, usability, and security. At this level, students are not expected to develop or implement the security measures that they discuss. For example, students could review case studies or current events in which governments or organizations experienced data leaks or data loss as a result of these types of attacks. Students could provide an analysis of actual security measures taken comparing to other security measure which may have led to different outcomes. Alternatively, students might discuss computer security policies in place at the local level that present a tradeoff between usability and security, such as a web filter that prevents access to many educational sites but keeps the campus network safe.

Standard:
Compare and contrast cryptographic techniques to model the secure transmission of information.

Descriptive Statement:
Cryptography is a technique for transforming information on a computer in such a way that it becomes unreadable by anyone except authorized parties. Cryptography is useful for supporting secure communication of data across networks. Examples of cryptographic methods include hashing, symmetric encryption/decryption (private key), and assymmetric encryption/decryption (public key/private key). Students use software to encode and decode messages using cryptographic methods. Students compare the costs and benefits of using various cryptographic methods. At this level, students are not expected to perform the mathematical calculations associated with encryption and decryption. For example, students could compare and contrast multiple examples of symmetric cryptographic techiques. Alternatively, students could compare and contrast symmetric and asymmetric cryptographic techniques in which they apply for a given scenario.

Standard:
Analyze a large-scale computational problem and identify generalizable patterns or problem components that can be applied to a solution.

Descriptive Statement:
As students encounter complex, real-world problems that span multiple disciplines or social systems, they need to be able to decompose problems and apply already developed code as part of their solutions. Students decompose complex problems into manageable subproblems that could potentially be solved with programs or procedures that can be reused or already exist. For example, in analyzing an Internet radio app, students could identify that users need to create an account and enter a password. They could identify a common application programming interface (API) for checking and displaying password strength. Additionally, students could recognize that the songs would need to be sorted by the time last played in order to display the most recently played songs and identify a common API for sorting dates from most to least recent. Alternatively, in analyzing the problem of tracking medical treatment in a hospital, students could recognize that patient records need to be stored in a database and identify a database solution to support quick access and modification of patient records. Additionally, they could recognize that records in the database need to be stored securely and could identify an encryption API to support the desired level of privacy.

Standard:
Construct solutions to problems using student-created components, such as procedures, modules, and/or objects.

Descriptive Statement:
Programmers often address complex tasks through design and decomposition using procedures and/or modules. In object-oriented programming languages, classes can support this decomposition. Students create a computational artifact that solves a problem through use of procedures, modules, and/or objects. This problem should be of sufficient complexity to benefit from decomposition and/or use of objects. For example, students could write a flashcard program in which each card is able to show both the question and answer and record user history. Alternatively, students could create a simulation of an ecosystem in which sprites carry out behaviors, such as consuming resources.

Standard:
Demonstrate code reuse by creating programming solutions using libraries and APIs.

Descriptive Statement:
Code reuse is critical both for managing complexity in modern programs, but also in increasing programming efficiency and reliability by having programmers reuse code that has been highly vetted and tested. Software libraries allow developers to integrate common and often complex functionality without having to reimplement that functionality from scratch. Students identify, evaluate, and select appropriate application programming interfaces (APIs) from software libraries to use with a given language and operating system. They appropriately use resources such as technical documentation, online forums, and developer communities to learn about libraries and troubleshoot problems with APIs that they have chosen. For example, students could import charting and graphing modules to display data sets, adopt an online service that provides cloud storage and retrieval for a database used in a multiplayer game, or import location services into an app that identifies points of interest on a map. Libraries of APIs can be student-created or publicly available (e.g., common graphics libraries or map/navigation APIs).

Standard:
Categorize and describe the different functions of operating system software.

Descriptive Statement:
Operating systems (OS) software is the code that manages the computer’s basic functions. Students describe at a high level the different functions of different components of operating system software. Examples of functions could include memory management, data storage/retrieval, processes management, and access control. For example, students could use monitoring tools including within an OS to inspect the services and functions running on a system and create an artifact to describe the activity that they observed (e.g., when a browser is running with many tabs open, memory usage is increased). They could also inspect and describe changes in the activity monitor that occur as different applications are executing (e.g., processor utilization increases when a new application is launched).

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.