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Showing 11 - 20 of 23 Standards

Standard Identifier: 6-8.AP.14

Grade Range: 6–8
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Developing and Using Abstractions (4.1, 4.3)

Standard:
Create procedures with parameters to organize code and make it easier to reuse.

Descriptive Statement:
Procedures support modularity in developing programs. Parameters can provide greater flexibility, reusability, and efficient use of resources. Students create procedures and/or functions that are used multiple times within a program to repeat groups of instructions. They generalize the procedures and/or functions by defining parameters that generate different outputs for a wide range of inputs. For example, students could create a procedure to draw a circle which involves many instructions, but all of them can be invoked with one instruction, such as “drawCircle.” By adding a radius parameter, students can easily draw circles of different sizes. (CA CCSS for Mathematics 7.G.4) Alternatively, calculating the area of a regular polygon requires multiple steps. Students could write a function that accepts the number and length of the sides as parameters and then calculates the area of the polygon. This function can then be re-used inside any program to calculate the area of a regular polygon. (CA CCSS for Mathematics 6.G.1)

Standard Identifier: 9-12.AP.12

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.1)

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 Identifier: 9-12.AP.13

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Variables
Practice(s): Developing and Using Abstractions (4.1)

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 Identifier: 9-12.AP.16

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Recognizing and Defining Computational Problems (3.2)

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 Identifier: 9-12.AP.17

Grade Range: 9–12
Concept: Algorithms & Programming
Subconcept: Modularity
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.3, 5.2)

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 Identifier: 9-12S.AP.10

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Recognizing and Defining Computational Problems, Communicating About Computing (3.1, 7.2)

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 Identifier: 9-12S.AP.11

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Recognizing and Defining Computational Problems, Creating Computational Artifacts (3.1, 5.3)

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 Identifier: 9-12S.AP.12

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Developing and Using Abstractions, Creating Computational Artifacts (4.2, 5.2)

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 Identifier: 9-12S.AP.13

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Algorithms
Practice(s): Recognizing and Defining Computational Problems (3.3)

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 Identifier: 9-12S.AP.14

Grade Range: 9–12 Specialty
Concept: Algorithms & Programming
Subconcept: Variables
Practice(s): Developing and Using Abstractions (4.2)

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.

Showing 11 - 20 of 23 Standards


Questions: Curriculum Frameworks and Instructional Resources Division | CFIRD@cde.ca.gov | 916-319-0881