Search the California Content Standards

Standard:
Test and analyze the effects of changing variables while using computational models.

Descriptive Statement:
Variables within a computational model may be changed, in order to alter a computer simulation or to more accurately represent how various data is related. Students interact with a given model, make changes to identified model variables, and observe and reflect upon the results. For example, students could test a program that makes a robot move on a track by making changes to variables (e.g., height and angle of track, size and mass of the robot) and discussing how these changes affect how far the robot travels. (CA NGSS: MS-PS2-2) Alternatively, students could test a game simulation and change variables (e.g., skill of simulated players, nature of opening moves) and analyze how these changes affect who wins the game. (CA NGSS: MS-ETS1-3) Additionally, students could modify a model for predicting the likely color of the next pick from a bag of colored candy and analyze the effects of changing variables representing the common color ratios in a typical bag of candy. (CA CCSS for Mathematics 7.SP.7, 8.SP.4)

Standard:
Explain potential security threats and security measures to mitigate threats.

Descriptive Statement:
Cybersecurity is an important field of study and it is valuable for students to understand the need for protecting sensitive data. Students identify multiple methods for protecting data and articulate the value and appropriateness for each method. Students are not expected to implement or explain the implementation of such technologies. For example, students could explain the importance of keeping passwords hidden, setting secure router administrator passwords, erasing a storage device before it is reused, and using firewalls to restrict access to private networks. Alternatively, students could explain the importance of two-factor authentication and HTTPS connections to ensure secure data transmission.

Standard:
Apply multiple methods of information protection to model the secure transmission of information.

Descriptive Statement:
Digital information is protected using a variety of cryptographic techniques. Cryptography is essential to many models of cybersecurity. At its core, cryptography has a mathematical foundation. Cryptographic encryption can be as simple as letter substitution or as complicated as modern methods used to secure networks and the Internet. Students encode and decode messages using encryption methods, and explore different levels of complexity used to hide or secure information. For example, students could identify methods of secret communication used during the Revolutionary War (e.g., ciphers, secret codes, invisible ink, hidden letters) and then secure their own methods such as substitution ciphers or steganography (i.e., hiding messages inside a picture or other data) to compose a message from either the Continental Army or British Army. (HSS.8.1) Alternatively, students could explore functions and inverse functions for encryption and decryption and consider functions that are complex enough to keep data secure from their peers. (CA CCSS for Mathematics 8.F.1)

Standard:
Design algorithms to solve computational problems using a combination of original and existing algorithms.

Descriptive Statement:
Knowledge of common algorithms improves how people develop software, secure data, and store information. Some algorithms may be easier to implement in a particular programming language, work faster, require less memory to store data, and be applicable in a wider variety of situations than other algorithms. Algorithms used to search and sort data are common in a variety of software applications. For example, students could design an algorithm to calculate and display various sports statistics and use common sorting or mathematical algorithms (e.g., average) in the design of the overall algorithm. Alternatively, students could design an algorithm to implement a game and use existing randomization algorithms to place pieces randomly in starting positions or to control the "roll" of a dice or selection of a "card" from a deck.

Standard:
Justify the selection of specific control structures by identifying tradeoffs associated with implementation, readability, and performance.

Descriptive Statement:
The selection of control structures in a given programming language impacts readability and performance. Readability refers to how clear the program is to other programmers and can be improved through documentation. Control structures at this level may include, for example, conditional statements, loops, event handlers, and recursion. Students justify control structure selection and tradeoffs in the process of creating their own computational artifacts. The discussion of performance is limited to a theoretical understanding of execution time and storage requirements; a quantitative analysis is not expected. For example, students could compare the readability and program performance of iterative and recursive implementations of procedures that calculate the Fibonacci sequence. Alternatively, students could compare the readability and performance tradeoffs of multiple if statements versus a nested if statement.

Standard:
Iteratively design and develop computational artifacts for practical intent, personal expression, or to address a societal issue by using events to initiate instructions.

Descriptive Statement:
In this context, relevant computational artifacts can include programs, mobile apps, or web apps. Events can be user-initiated, such as a button press, or system-initiated, such as a timer firing. For example, students might create a tool for drawing on a canvas by first implementing a button to set the color of the pen. Alternatively, students might create a game where many events control instructions executed (e.g., when a score climbs above a threshold, a congratulatory sound is played; when a user clicks on an object, the object is loaded into a basket; when a user clicks on an arrow key, the player object is moved around the screen).

Standard:
Decompose problems into smaller subproblems through systematic analysis, using constructs such as procedures, modules, and/or classes.

Descriptive Statement:
Decomposition enables solutions to complex problems to be designed and implemented as more manageable subproblems. Students decompose a given problem into subproblems that can be solved using existing functionalities, or new functionalities that they design and implement. For example, students could design a program for supporting soccer coaches in analyzing their teams' statistics. They decompose the problem in terms of managing input, analysis, and output. They decompose the data organization by designing what data will be stored per player, per game, and per team. Team players may be stored as a collection. Data per team player may include: number of shots, misses, saves, assists, penalty kicks, blocks, and corner kicks. Students design methods for supporting various statistical analyses and display options. Students design output formats for individual players or coaches.

Standard:
Create computational artifacts using modular design.

Descriptive Statement:
Computational artifacts are created by combining and modifying existing computational artifacts and/or by developing new artifacts. To reduce complexity, large programs can be designed as systems of interacting modules, each with a specific role, coordinating for a common overall purpose. Students should create computational artifacts with interacting procedures, modules, and/or libraries. For example, students could incorporate a physics library into an animation of bouncing balls. Alternatively, students could integrate open-source JavaScript libraries to expand the functionality of a web application. Additionally, students could create their own game to teach Spanish vocabulary words using their own modular design (e.g., including methods to: control scoring, manage wordlists, manage access to different game levels, take input from the user, etc.).

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:
Refine computational models to better represent the relationships among different elements of data collected from a phenomenon or process.

Descriptive Statement:
Computational models are used to make predictions about processes or phenomena based on selected data and features. They allow people to investigate the relationships among different variables to understand a system. Predictions are tested to validate models. Students evaluate these models against real-world observations. For example, students could use a population model that allows them to speculate about interactions among different species, evaluate the model based on data gathered from nature, and then refine the model to reflect more complex and realistic interactions.