AP Syllabus

Big Ideas Guide

CRD - Creative Development
DAT - Data
AAP - Algorithms & Programming
CSN - Computer Systems & Networks
IOC - Impact of Computing

Computational Thinking Practices Guide

CT1 - Computational Solution Design
CT2 - Algorithms & Program Development
CT3 - Abstraction in Program Development
CT4 - Code Analysis
CT5 - Computing Innovations
CT6 - Responsible Computing

Reference: AP Course and Exam Description

CR 1 - Resources

The teacher and students have access to college-level computer science resources, in print or electronic format.

The primary teaching resource in this course is Introduction to Computing, an eTextbook authored by K-State faculty. The textbook consists of lecture material and videos developed and presented by K-State faculty, as well as an annotated bibliography of additional readings and videos from across the internet on each topic. The textbook is used in two college-level courses taught at K-State:

CIS 115 - Introduction to Computing Science
CC 110 - Introduction to Computing

The textbook can be found online at:

Primary Link: https://textbooks.cs.ksu.edu/cc110/
Alternate Link: https://ksu-cs-textbooks.github.io/cszero/
Authors & Contributors: https://core.cs.ksu.edu/authors/

Much of the content in the eTextbook is broadly inspired by two books:

The Pattern on the Stone: The Simple Ideas That Make Computers Work by W. Daniel Hillis
Nine Algorithms That Changed the Future: The Ingenious Ideas That Drive Today’s Computers by John MacCormick

These books are recommended reading for students in the AP version of this course but are not required.

CR 2 - Develop Understanding of Content

The course provides opportunities to develop student understanding of the required content outlined in each of the big ideas described in the AP Course and Exam Description.

The course consists of two major types of content:

Lecture Content, Videos, Discussions, Activities & Quizzes - roughly 2 college credit hours
Programming Content, Labs, and Homeworks - roughly 1 college credit hour

They are separated to allow teachers flexibility in structuring the course each semester. Below is an outline of the modules in each content area.

Lecture Content

Unit 1 - CS Concepts

Chapter 1 - What is Computing Science?

Students are introduced to the field of computer science, including the original definition of a computer. They will learn about the reasons why pioneers such as Babbage and Lovelace desired to build machines to handle computations, reducing the risk of human error when computing mathematical tables.

DAT 3.2 Data Abstraction, 3.16 Simulations
IOC 5.1 Beneficial & Harmful Effects

Chapter 2 - Early Computing Machines

Students learn about the early history of computing machines, including the Antikythera Mechanism, abacus, and slide rule. Students then discuss and explore what features must be present in a device in order for it to be considered a computer, aiming for computation, storage, input, and output. Students are then introduced to key devices that pioneered the development of these features, such as Pascal’s Calculator and the Leibniz Wheel (computation), Jacquard Loom (input via punch cards), Babbage’s Difference Engine (output via press plates), and Babbage’s Analytical Engine (integrating all items and including a storage mechanism). Students will see that the development of computer technology required input from many areas.

CRD 1.1 Collaboration, 1.2 Program Function & Purpose

Chapter 3 - Bits & Boolean Algebra

Students are introduced to the concepts in Boolean logic, including the AND, OR, NOT, and XOR operators. Students then explore Boolean algebra, observing how many of the rules have parallels directly to mathematics. Students also explore DeMorgan’s Theorem. Students work on several examples in class, going from truth tables to Venn diagrams and finally Boolean logic expressions. From there, students see how Boolean logic can be implemented using simple electronic circuits, forming the building blocks of modern computers.

AAP 3.5 Boolean Expressions

Chapter 4 - Programming

Students explore the history of programming and many diverse pioneers such as Grace Hopper, Ada Lovelace and Margaret Hamilton. Students then learn what it means to actually “program” a computer and explore the process of taking code written in a high-level language (such as Java) and using tools such as compilers, interpreters, and assemblers to convert that code to assembly and eventually machine-level instructions that can actually be performed by a computer.

CRD 1.1 Collaboration, 1.2 Program Function & Purpose
AAP 3.2 Data Abstraction

Chapter 5 - Universal Computers

Students learn about the work of Alan Turing and the concepts behind a universal computer like the Turing Machine. Students work through an example to build a simple Turing machine to mimic Boolean logic operators using a few simple instructions. From there, students see how the concept of a universal computer, coupled with the prior concepts from other historical computers, led to the creation of the Von Neumann Architecture that is used in most modern computers.

CRD 1.1 Collaboration
AAP 3.2 Data Abstraction, 3.9 Developing Algorithms, 3.16 Simulations

Chapter 6 - Algorithms

Students learn about Al-Khwarizmi and the history of the word “algorithm” before exploring simple algorithms such as Euclid’s Algorithm. Students then go through an activity using playing cards to learn about four different sorting algorithms - insertion/selection sort, bubble sort, merge sort, and quicksort. At each step, students discuss how many “steps” it took to complete the algorithm, and then use that data to explore algorithmic complexity. Students are then introduced to Big-O notation as a way to compare the running time of algorithms, and by analyzing quicksort they also learn about the difference between worst-case and expected-case performance. Students are then introduced to the Traveling Salesman problem as a way to explore heuristics and the development of faster algorithms to find a good answer, but not necessarily the best answer.

AAP 3.9 Developing Algorithms, 3.17 Algorithmic Efficiency

Chapter 7 - Encoding

Students learn about the work of George Stibitz and the creation of the Model K computer, one of the first to use binary values when performing calculations. Using that motivation, students learn about binary numbers and representation, including twos complement for negative values, floating-point for decimal values, ASCII for text, and both vector and raster image formats. Students also briefly see the basics of compression by replacing repeated data with smaller representations, but also see a case study showing how that can lead to loss of data and errors if done improperly.

DAT 2.1 Binary Numbers, 2.2 Data Compression, 2.3 Extracting Information from Data
AAP 3.2 Data Abstraction

Chapter 8 - Computer Architecture

Students learn about the development of the integrated circuit, seeing how it was the culmination of many small advancements by many different groups and how it helped solve the “Tyranny of Numbers” complexity problem of computers at that time. From there, students learn about Moore’s Law and how more and more components are placed on integrated circuit chips, leading to the first microprocessor in the Intel 4004 chip. Students also are re-introduced to Von Neumann Architecture and the parts of a modern computer. Finally, students perform an in-class exercise introducing finite state machines and how they can be used to represent real-world ideas in a computer program.

CRD 1.1 Collaboration
AAP 3.3 Data Abstraction, 3.9 Developing Algorithms, 3.16 Simulations

Chapter 9 - Software Engineering

Students learn about the practice of software engineering, including the software crisis and the recognition of the need for better language structures and processes. Students explore the various stages of the software development life cycle and different methodologies such as waterfall, iterative/incremental development, and agile.

CRD 1.1 Collaboration, 1.3 Program Design & Development
IOC 5.1 Beneficial & Harmful Effects

Chapter 10 - Human-Computer Interaction

Students are introduced to the field of human-computer interaction, starting with the work of Douglas Engelbart and the “Mother of all Demos” exploring his NLS system. Students then learn about the history of modern computer interfaces, including the creation of the desktop metaphor used in most modern systems. Students also learn about some failed experiments such as Microsoft Bob and discuss what makes a good or bad interface. Students see the work of Don Norman and user-centered design. Finally, students are introduced to several new and interesting concepts in HCI and future computer interfaces, such as virtual/augmented reality, multi-touch interfaces, and examples of building accessible interfaces.

CRD 1.2 Program Function & Purpose
IOC 5.1 Beneficial & Harmful Effects, 5.4 Crowdsourcing

Unit 2 - The Internet

Chapter 11 - The History of the Internet

Students explore the history of the internet, starting with J.C.R. Licklider and his “Intergalactic Computer Network” concept, leading to the creation of the ARPANET. Students see videos and information from many pivotal figures in the history of the internet including Leonard Kleinrock, Vint Cerf, and Tim Berners-Lee. Students learn how the development of HTML and the world wide web helped bring the internet to the public, and how the dot-com bubble was a major turning point in the early internet before the rise of social media.

CRD 1.1 Collaboration
CSN 4.1 The Internet
IOC 5.1 Beneficial & Harmful Effects, 5.4 Crowdsourcing

Chapter 12 - How the Internet Works

Students learn about the developments that lead to the technology behind the internet, such as packet-switching, and the various protocols that make up the seven layer OSI network model. Students learn how these developments were meant to build robust, fault-tolerant networks that can work in a variety of conditions.

CSN 4.1 The Internet, 4.2 Fault Tolerance

Chapter 13 - Web Programming

Students learn the basics of web programming including HTML and CSS, and build a simple JavaScript Tic-Tac-Toe game to explore interactivity on webpages.

CRD 1.3 Program Design & Development
AAP 3.12 Calling Procedures, 3.13 Developing Procedures
CSN 4.1 The Internet

Unit 3 - CS Topics

Chapter 14 - High Performance Computing

Students learn about the concepts behind high-performance computing and why we need larger and more powerful computers to tackle some of the world’s biggest problems. Students explore ways that large problems can be broken down into smaller parts and run in parallel on multiple computers. Students also see some real-world examples of problems that high-performance computing can solve. Finally, students are given a virtual tour through K-State’s own supercomputer.

CRD 1.1 Collaboration, 1.3 Program Design & Development
Data 2.4 Using Programs with Data
CSN 4.3 Parallel & Distributed Computing
IOC 5.1 Beneficial & Harmful Effects

Chapter 15 - Compression & Error Checking

Students explore various ways that data can be compressed, including run-length encoding and Huffman coding. Students also learn about methods for detecting and correcting errors in data, such as checksums.

DAT 2.2 Data Compression, 2.3 Extracting Information from Data
AAP 3.2 Data Abstraction, 3.9 Developing Algorithms
CSN 4.2 Fault Tolerance

Chapter 16 - Cryptography

Students learn the fundamental concepts and history of cryptography, starting with simple substitution ciphers. Students follow a case-study of the enigma machine and how it was defeated by the work of Alan Turing and others during the second world war. Students learn about modern cryptography principles including public-key cryptography, digital signatures, and perform a simple example of RSA encryption.

CSN 4.1 The Internet
IOC 5.1 Beneficial & Harmful Effects, 5.4 Crowdsourcing

Chapter 17 - Cybersecurity

Students explore the basics of cybersecurity, including a math-based discussion of passwords and relative password strength, as well as how passwords can be stored securely in a program. Students also learn about various cybersecurity threats such as social engineering.

CSN 4.1 The Internet
IOC 5.1 Beneficial & Harmful Effects, 5.5 Legal & Ethical Concerns, 5.6 Safe Computing

Chapter 18 - Artificial Intelligence

Students explore the field of artificial intelligence and what it means to say a machine is intelligent. Students engage in a discussion around the Turing Test and the Chinese Room counterexample. Students learn about intelligent agents and how they are used throughout the world, and explore other AI advancements such as neural networks and deep learning.

DAT 2.3 Extracting Information from Data, 2.4 Using Programs with Data
AAP 3.16 Simulations
IOC 5.1 Beneficial & Harmful Effects, 5.3 Computing Bias

Chapter 19 - Search & Information Retrieval

Students explore the basics of databases and relational data. Students also learn about how information can be indexed and searched, followed by an introduction to ranking and the process of page rank for web searches.

DAT 2.3 Extracting Information from Data, 2.4 Using Programs with Data
AAP 3.9 Developing Algorithms, 3.16 Simulations
CSN 4.1 The Internet
IOC 5.1 Beneficial & Harmful Effects, 5.3 Computing Bias, 5.4 Crowdsourcing

Notes - add bias to discussions

Chapter 20 - Big Data

Students explore the impact of big data in computing and how it is being used to solve large-scale real-world problems in areas such as healthcare. Students are also introduced to the concept of map-reduce in programming.

DAT 2.3 Extracting Information from Data, 2.4 Using Programs with Data
AAP 3.9 Developing Algorithms
CSN 4.3 Parallel & Distributed Computing
IOC 5.1 Beneficial & Harmful Effects, 5.4 Crowdsourcing

Chapter 21 - Ethics

Students explore some of the legal and ethical impacts of computing, including intellectual property, bias, privacy, and fair use. Students also learn about the digital divide and how that impacts access to information and equity.

IOC 5.1 Beneficial & Harmful Effects, 5.2 Digital Divide, 5.3 Computing Bias, 5.4 Crowdsourcing, 5.5 Legal & Ethical Concerns

Notes - this is pretty aspirational?

Chapter 22 - Graphics & Video Games

Students explore the basics of computer graphics and how they have evolved over time. Students learn about the “uncanny valley” effect. Students also see how early video game graphics were built, exploring concepts related to data compression and efficiency on such small systems.

DAT 2.1 Binary Numbers, 2.2 Data Compression
AAP 3.16 Simulations, 3.17 Algorithmic Efficiency

Programming Content

Lab 1 - Introduction

This lab introduces students to the basics of the Codio interface and gives some examples of the various assessments contained in the labs.

Labs 2 & 3 - Basic Programming

These labs introduce students to the basic syntax of both pseudocode and Python. Students learn how to use a simple Linux terminal to navigate the file system and execute programs. Students learn to use print to display output, and explore examples of printing input with and without newline characters. Students learn to create basic variables that store strings. Students explore code tracing both by hand (in pseudocode) and using Python Tutor. Finally, students learn to create functions or procedures, including simple parameters and arguments, and learn how to create a main function or procedure for their programs.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.1 Variables & Assignments, 3.2 Data Abstraction, 3.4 Strings, 3.12 Calling Procedures, 3.13 Developing Procedures

Labs 4 & 5 - Operations & Input

These labs introduce math and string operators in both pseudocode and Python. Students learn about integer and floating-point data types and how to convert between the two. In addition, students learn how to return data from functions or procedures, and explore how to use the basics of function composition to combine expressions into more complex statements, such as using the result of a function call directly as an argument to another function. Students learn how to request input from the user and convert a string into a numerical value.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
DAT - 2.1 Binary Numbers, 2.4 Using Programs with Data
AAP - 3.1 Variables & Assignments, 3.3 Mathematical Expressions, 3.12 Calling Procedures, 3.13 Developing Procedures

Labs 6 & 7 - Conditionals

These labs introduce students to conditional statements in both pseudocode and Python. Students learn about the Boolean data type and a number of Boolean operators and comparators used in Boolean expressions. Students then learn about if and if-else statements, and explore how to test their programs by developing inputs that achieve branch and path coverage.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.1 Variables & Assignments, 3.3 Mathematical Expressions, 3.5 Boolean Expressions, 3.6 Conditionals, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures

Lab 8 - Homework 3

This lab is a stand-in for homework 3, which is partially done in-class along with the unit on web programming. It is discussed below.

Lab 9 - Nested Conditionals

In this lab, students explore the concepts being nesting and chaining conditionals. Students learn about the usefulness of mutual exclusion when designing conditional statements, and also explore the concept of variable scope and blocks of code.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.5 Boolean Expressions, 3.6 Conditionals, 3.7 Nested Conditionals, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures

Labs 10 & 11 - Loops

This lab introduces the concepts of loops and iteration in both pseudocode and Python. Students will see both for loops (iterating across a collection or range) and while loops (iterating while a Boolean condition is true). Students also learn how to use loops to prompt for input and repeat until a valid input is received. Students learn to test loops using inputs that achieve branch and path coverage. Students also learn how to import the random library in Python and generate random integer values in a range.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.5 Boolean Expressions, 3.8 Iteration, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures, 3.14 Libraries, 3.15 Random Values

Lab 12 - Nested Loops

This lab reinforces previous learning on loops with examples on how to nest a loop inside of another loop. Students will learn how skills for tracing execution through these loops by hand and using Python tutor. Students also learn skills for testing these loops and developing inputs that properly explore the edge cases.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.5 Boolean Expressions, 3.8 Iteration, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures

Lab 13 - Lists

This lab introduces students to the list data structure in Python. Students learn about the list data type, including accessing elements by index and adding elements. Students explore how to use loops with lists to iterate through elements. Students learn that lists are handled in a “pass by reference” way when used as arguments to functions. Students learn that strings can also be treated like lists, and that lists can be sliced in a variety of ways.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
DAT - 2.4 Using Programs with Data
AAP - 3.1 Variables & Assignments, 3.2 Data Abstraction, 3.4 Strings, 3.9 Developing Algorithms, 3.10 Lists, 3.12 Calling Procedures, 3.13 Developing Procedures

Lab 14 - Dictionaries

This lab introduces the dictionary data structure in Python. Students learn how to add and access elements in a dictionary, and how to iterate through all elements in a dictionary, including both keys and values. Students also see that dictionaries are treated similar to lists when used as function arguments.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
DAT - 2.4 Using Programs with Data
AAP - 3.1 Variables & Assignments, 3.2 Data Abstraction, 3.4 Strings, 3.9 Developing Algorithms, 3.10 Lists, 3.12 Calling Procedures, 3.13 Developing Procedures, 3.16 Simulations

Homework 1

The first homework typically involves some sort of mathematical simulation, such as compound interest. It reinforces the topics of variables, numeric and string data types, reading input, using math operators, and formatting output.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.1 Variables & Assignments, 3.2 Data Abstraction, 3.3 Mathematical Expressions, 3.4 Strings, 3.5 Boolean Expressions, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures, 3.16 Simulations

Homework 2

The second homework typically involves conditional statements as well as mathematical operators and more practice with input, output, and functions.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
AAP - 3.1 Variables & Assignments, 3.3 Mathematical Expressions, 3.5 Boolean Expressions, 3.6 Conditionals, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures, 3.16 Simulations

Homework 3

The third homework introduces students to creating websites with HTML and CSS. Students also follow a tutorial to create a simple game in JavaScript to explore interactivity on web pages.

AAP - 3.2 Data Abstraction, 3.14 Libraries
CSN - 4.1 The Internet

Homework 4

The fourth homework covers the use of nested conditional statements, as well as user input and handling functions with parameters and return values.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
DAT - 2.3 Extracting Information from Data, 2.4 Using Programs with Data
AAP - 3.1 Variables & Assignments, 3.2 Data Abstraction, 3.3 Mathematical Expressions, 3.4 Strings, 3.5 Boolean Expressions, 3.6 Conditionals, 3.7 Nested Conditionals, 3.9 Developing Algorithms, 3.12 Calling Procedures, 3.13 Developing Procedures, 3.16 Simulations

Homework 5

The fifth homework covers the use of loops and advanced data structures such as lists or dictionaries. It usually involves a larger amount of input, either a string or a list of values.

CRD - 1.2 Program Function & Purpose, 1.3 Program Design & Development, 1.4 Identifying & Correcting Errors
DAT - 2.3 Extracting Information from Data, 2.4 Using Programs with Data
AAP - 3.1 Variables & Assignments, 3.2 Data Abstraction, 3.3 Mathematical Expressions, 3.4 Strings, 3.5 Boolean Expressions, 3.6 Conditionals, 3.7 Nested Conditionals, 3.8 Iteration, 3.9 Developing Algorithms, 3.10 Lists, 3.12 Calling Procedures, 3.13 Developing Procedures, 3.16 Simulations

CR 3 - Develop Understanding of Big Ideas

The course provides opportunities to develop student understanding of the big ideas.

Big Idea 1 - Creative Development

The course includes several programming assignments that are completed by the student. Each assignment requires the student to write code that solves a problem and meets an expected structure. Students will also write a reflection for each assignment that discusses their program design process, any problems solved or debugging performed, and resources or assistance used. Current homework assignments are described above in detail. Most assignments fit one or more of these categories:

Simple calculator program
Cash register or purchase simulator
HTML website and simple game
Decision tree simulator
Simple cipher program
Grade calculator
Random number simulator

Big Idea 2 - Data

Students in this course explore data in a variety of ways. Students participate in an activity to see how data is represented in binary as integers and floating point, and how those numbers can be translated to text using ASCII, as well as colors and vectors to create images and videos. Another activity has students explore data compression and error checking. Students also participate in an activity to learn how data is used to train a neural network.

Big Idea 3 - Algorithms & Programming

Students participate in an activity using a deck of cards to learn various sorting algorithms (bubble sort, insertion sort, merge sort, and quicksort). Students also participate in an activity to simulate the random surfer model used by page rank. Students also learn about Turing machines and participate in a simple activity to develop an algorithm for a Turing machine that simulates a Boolean operator, such as “xor” on two binary values.

In addition, students perform many guided programming labs and unguided homeworks to further explore algorithms and programming, both in pseudocode as well as Python.

Big Idea 4 - Computer Systems & Networks

Students participate in an activity to simulate a packet-switched network as part of a number guessing game. Each team chooses a secret number and is assigned a name. Then, teams use a simulated DHCP protocol to be assigned an address, and then they can use a simulated DNS protocol to find the addresses assigned to other teams. Then, teams can send simulated HTTP packets to guess the receiving team’s number, and they respond with HTTP response codes whether the correct number is “higher” or “lower” than the guess. Throughout the activity, students are encouraged to think about how a real network operates, and teachers are encouraged to allow some “packet loss” or even “reset the router” and force teams to re-connect to the network before continuing. This also leads to discussions of how packet-switched networks include fault tolerance.

In another activity, students simulate a map-reduce algorithm to count the words in a small poem, learning about parallel and distributed systems.

Big Idea 5 - Impact of Computing

Throughout the semester, students participate in many guided discussions about the impact of computing on the world and in society. Some discussion topics include:

Observed changes in Computing Technology over the years
Algorithms in the world and how they impact us
Human-Computer Interaction and UI design
The filter bubble
Evolution/Impact of Computer Graphics
“The Creepy Line” documentary video on ethics

CR 4 - CT Practice 1: Computational Solution Design

The course provides opportunities for students to develop the skills related to Computational Thinking Practice 1: Computational Solution Design, as outlined in the AP Course and Exam Description.

Students will write complete computer programs to solve various homework assignments that must meet a given specification. Students will need to determine the appropriate program structures to be used to solve the problem, and then develop and test their solution.

Through many of the in-class activities, students will also explore and discuss various existing ways computer scientists have solved real-world problems, such as the development of search algorithms, sorting algorithms, data compression, and error checking. Students will also evaluate the various methods and discuss their performance and tradeoffs.

CR 5 - CT Practice 2: Algorithms & Program Development

The course provides opportunities for students to develop the skills related to Computational Thinking Practice 2: Algorithms and Program Development, as outlined in the AP Course and Exam Description.

Students will design and implement algorithms to solve a variety of computing tasks. Students will discuss the importance of carefully developing algorithms and using clear, explicit instructions through activities such as the classic “make a sandwich” unplugged activity. In the homework assignments, students will implement algorithms to make change in a transaction, guide users through a decision tree, and use a simple cipher to encode and decode secret messages.

Students will also explore a variety of computing concepts in pseudocode, requiring them to think and reason clearly about what the program will do, especially since they have no way to run the program and confirm the result directly.

CR 6 - CT Practice 3: Abstraction in Program Development

The course provides opportunities for students to develop the skills related to Computational Thinking Practice 3: Abstraction in Program Development, as outlined in the AP Course and Exam Description.

Students will write several programs that require user input, such as compound interest calculator or cash register simulator. Students will explore how the data input by the user is stored in variables and used to represent various items in the real world.

In another homework, students will use a simple cipher to encode and decode secret messages. Students will explore how text is made up of individual characters, and how we can use a randomized or reordered list of characters as a “key” to encode and decode the data.

CR 7 - CT Practice 4: Code Analysis

The course provides opportunities for students to develop the skills related to Computational Thinking Practice 4: Code Analysis, as outlined in the AP Course and Exam Description.

In many of the lab assignments, students will complete many exercises that involve reading code and determining what is performed or what output is produced. Students will also participate in several code tracing activities (similar to Python Tutor) in both pseudocode and Python to explore procedure calls, passing arguments and returning values.

Students will also be asked to develop a number of test cases for various sample programs in the lab assignments, aiming to achieve either branch coverage or path coverage across code that contains conditional statements or loops.

CR 8 - CT Practice 5: Computing Innovations

The course provides opportunities for students to develop the skills related to Computational Thinking Practice 5: Computing Innovations, as outlined in the AP Course and Exam Description.

Students will explore many computing innovations throughout the course, starting with the history of computing and moving to modern advancements such as neural networks, computer graphics, the internet, and big data, among many others.

Students will also participate in many discussions in-class and/or online on a variety of computing topics, such as how technology has changed during their lifetimes, the “filter bubble,” observable algorithms in daily life, and more. Students will also explore some of the ethical and legal concerns around social media and cybersecurity.

CR 9 - CT Practice 6: Responsible Computing

The course provides opportunities for students to develop the skills related to Computational Thinking Practice 6: Responsible Computing, as outlined in the AP Course and Exam Description.

Students will explore issues related to digital hygiene, such as using secure passwords, avoiding suspicious emails, and combatting social engineering and phishing tactics.

Students will also discuss ways that computer interfaces and websites can be built to me more inclusive for users with limited access or ability to interact with the system. Students will also see examples of instances where artificial intelligence can introduce unintentional bias into the results.

CR 10 - Investigate Computing Innovations

The course provides a minimum of three opportunities for students to investigate different computing innovations.

Computing Innovation 1, Prompt A

Students will participate in a guided discussion in class on the development of Web 2.0, the rise of social media, and its impacts on society. Students will explore both their own experiences interacting with social media, how it has impacted society and culture, and review any recent news articles related to the topic. Based on the discussion, students will write reflection papers to address the beneficial and harmful impacts of social media.

Computing Innovation 2, Prompt B

Students will participate in an activity that simulates training an artificial neural network to identify animals. Each student is given a part of a larger image, and then all students vote on whether the overall image contains a cat or a dog. Students who get the answer correct are given more votes, simulating a higher weight in the neural network. This repeats for several iterations until the network is well trained. Students will discuss how the input data affects the quality of the output, and explore case-studies where training a neural network didn’t work well or introduced unintentional bias in the output. Students will use this knowledge to write a short explanation in their own words of how neural networks work and how they are trained.

Computing Innovation 3, Prompt C

Students will learn about how to properly store and secure passwords in an application, involving the use of a hash function and a randomized salt value. Students will respond to prompts asking them to describe the security, privacy, and data storage concerns related to storing user account information and passwords for an application.

CR 11 - Create Performance Task

Students are provided at least 12 hours of dedicated class time to complete the AP Create Performance Task.

Following the completion of the programming labs, students will be given at least 12 hours of class time across multiple class sessions to complete the AP Create Performance task.

AP Alignment

Subsections of AP Alignment