Students explore the underlying behavior of variables through an unplugged activity. Using notecards and string to simulate variables within a program, students implement a few short programs. Once comfortable with this syntax, students use the same process with sprite properties, tracking a sprite's progress across the screen.

By running a simple simulation in Sprite Lab, students will experience how computing can be used to collect data that identify trends or patterns. After running the simulation multiple times, students will have an opportunity to make a prediction about how changing a variable in the simulation might impact the outcome, and then test that hypothesis.

In this lesson students explore the benefits (and potential security concerns) associated with routing traffic across the Internet. Building on their introduction to IP addresses in the previous lesson, students use a version of the Internet Simulator that allows messages to be sent only to an intended recipient, as indicated by the IP address. The Internet Simulator also allows students to examine the traffic that goes through all of the (simulated) routers on the network. They will discover that messages go through many different routers, may not always take the same path to reach the final destination, and that the routers (and their owners) can *see all of this traffic*!

This lesson is the last of the algorithm series. Building off of the previous lesson about shortest path algorithms, the activity in this lesson shows how routers learn about the rest of the Internet in order to route traffic so it takes the shortest path. In the previous lessons, students use the Internet Simulator to send packets to other students through simulated routers. The path that the packet follows, and how the router knows where to send it, however, has been largely untouched. Today, students simulate the process of a router joining a network and generating a router table that would allow them to send packets to anyone else in their network as efficiently as possible. They then reflect on the process by comparing the similarities between the SSSP problem and the process the used today, and how it facilitates the structure of the Internet.

In this lesson student develop a protocol for reliably sending a message over an unreliable internet. The Internet Simulator has been setup for this lesson to restrict messages to no more than 8 characters each, and messages get dropped messages with some probability on every hop.

Students are given time to experiment with the Internet Simulator and develop their own protocol, possibly testing or demonstrating their protocol to their peers. At the conclusion of the lesson, students watch a short video explaining how these challenges are addressed in the real world with [v TCP] - the Transmission Control Protocol.

The core idea of this lesson occurs in the unplugged activity that kicks off the lesson, in which students try to keep track of IP addresses that had been randomly assigned to each student in the class, while at the same time the teacher occasionally changes students' addresses. This leads to identifying the need for an authoritative system for name-to-address mappings, known as the Domain Name System or [v DNS].

Students then briefly experiment with a DNS protocol in the Internet Simulator. The activity is similar, in that students will have to grapple with IP addresses changing in real time and use the built in DNS protocol to resolve the issues.

The lesson ends with students doing some rapid research about DNS and some of its vulnerabilities, particularly what are known as Denial of Service Attacks.

Students are introduced to the Internet Simulator, a tool they will return to many times in the first two units of the course. Today, the Internet Simulator will be used to simulate a single shared wire, connecting two people. The wire can only be in one of two possible states (state A or state B) and either partner may set or read the state of the wire at any time, but this is the only way in which students may communicate. Students must invent a binary call-response [v protocol] using this system. Coordination, speed and timing are problems that need to be solved. At the conclusion of the lesson, students compete to demonstrate the speed and accuracy of their protocols, and calculate the [v bit rate] of their message exchange.

In this lesson students will return to the Internet Simulator in order to send a simple line drawing to a classmate. Students will be presented a grid on which they will draw an image (connecting 3-7 dots with straight lines). They must develop a protocol which will allow them to send any image they might create on their grids, paying particular attention to how many bits are used to represent each binary number. Students will therefore have additional practice encoding and decoding binary numbers and develop further intuitions about the properties of binary numbers in a hands-on way. The lesson concludes by testing protocols using a teacher-supplied test-image to transmit.

In this lesson, students create their own system for representing text in binary and explore how their newfound ability to convert between binary and decimal numbers helps in this process. In the warm up students quickly create a system for representing the 50 states in binary. They then move to the main activity where they create a system for representing text using only numbers while communicating on the Internet Simulator. At the end of the main activity they briefly review the ASCII system. The wrap up discussion introduces the concept of abstraction and its connection to the chapter. Following this lesson there is a chapter assessment that reviews the contents of this and the previous lessons.

In this lesson, students explore more deeply how communication between multiple computers can work over the Internet. They do this by playing a simplified game of Battleship, in which the first game is played unplugged, in their table groups, and the second game is played using the Internet Simulator, so that multiple students can connect to each other and see each other’s messages. Students must devise a messaging protocol that makes it clear who is sending the message and who the intended recipient is.

Students then devise a *binary protocol* for playing this game which will entail developing an addressing system for players, as a well as a formal packet structure for transmitting data about the state of the game.

**NOTE**: this is a large lesson that will likely need to span 2 days of class.

This lesson asks students to consider carefully the assumptions they make when interpreting data and data visualizations. The class begins by examining how the Google Flu Trends project tried and failed to use search trends to predict flu outbreaks. They will then read a report on the Digital Divide which highlights how access to technology differs widely by personal characteristics like race and income. This report challenges a widespread assumption that data collected online is representative of the population at large. To practice identifying assumptions in data analysis, students are provided a series of scenarios in which data-driven decisions are made based on flawed assumptions. They will need to identify the assumptions being made (most notably those related to the digital divide) and explain why these assumptions lead to incorrect conclusions.

In this lesson, students gain more practice using **while** loops as they develop a simulation that repeatedly flips coins until certain conditions are met. The lesson begins with an unplugged activity in which students flip a coin until they get 5 heads in total, and then again until they get 3 heads in a row. They will then compete to predict the highest outcome in the class for each statistic. This activity motivates the programming component of the lesson in which students develop a program that allows them to simulate this experiment for higher numbers of heads and longer streaks.

In this kickoff to the Data Unit, students begin thinking about how data is collected and what can be learned from it. To begin the lesson, students will take a short online quiz that supposedly determines something interesting or funny about their personality. Afterwards they will brainstorm other sources of data in the world around them, leading to a discussion of how that data is collected. This discussion motivates the introduction of the Class Data Tracker project that will run through the second half of this unit. Students will take the survey for the first time and be shown what the results will look like. To close the class, students will make predictions of what they will find when all the data has been collected in a couple weeks.

This is a pretty fun lesson that has two main parts. First students warm up by reflecting on the reasons data visualizations are used to communicate about data. This leads to the main activity in which students look at some collections of (mostly bad) data visualizations, rate them, explain why a good one is effective, and also suggest a fix for a bad one.

In the second part of class students compare their experiences and create a class list of common faults and best practices for creating data visualizations. Finally, students review and read the first few pages of **Data Visualization 101: How to design charts and graphs** to see some basic principles of good data visualizations and see how they compare with the list the class came up with.

Now that students have had the chance to see and evaluate various data visualizations, they will learn to make visualizations of their own. This lesson teaches students how to build visualizations from provided datasets. The levels in Code Studio provide a detailed walkthrough of how to use Google Sheets to create several different kinds of charts. While this lesson focuses on the Google Sheets tool, other tools may be substituted at the teacher’s discretion, and MS Excel support is coming soon to the lesson.

The main activity teaches students to build different chart types (scatter, line, and bar charts) from a single data set. It should be emphasized to students that the purpose of this lesson is to explore and experiment with creating different types of visualizations, not to build the perfect chart. Students will have a chance to create and customize their own charts. At the end of class, students compare their custom visualizations with those of their classmates.

In this lesson, students will collaboratively investigate some datasets and use visualization tools to “discover a data story.” The lesson assumes that students know how to use some kind of visualization tool - in the previous lesson we used the charting tools of a basic spreadsheet program. Students should be working with a partner but without much teacher hand-holding. Most of the time should be spent with students poking around the data and trying to discover connections and trends using data visualization tools. It is up to them to discover a trend, make a chart, and accurately write about it.

This course begins with a review of algebra specifically designed to help and prepare the student for the study of calculus, and continues with discussion of functions, graphs, limits, continuity, and derivatives. The appendix provides a large collection of reference facts, geometry, and trigonometry that will assist in solving calculus problems long after the course is over. Upon successful completion of this course, the student will be able to: calculate or estimate limits of functions given by formulas, graphs, or tables by using properties of limits and LĺÎĺ_ĺĚĺ_hopitalĺÎĺ_ĺĚĺ_s Rule; state whether a function given by a graph or formula is continuous or differentiable at a given point or on a given interval and justify the answer; calculate average and instantaneous rates of change in context, and state the meaning and units of the derivative for functions given graphically; calculate derivatives of polynomial, rational, common transcendental functions, and implicitly defined functions; apply the ideas and techniques of derivatives to solve maximum and minimum problems and related rate problems, and calculate slopes and rates for function given as parametric equations; find extreme values of modeling functions given by formulas or graphs; predict, construct, and interpret the shapes of graphs; solve equations using NewtonĺÎĺ_ĺĚĺ_s Method; find linear approximations to functions using differentials; festate in words the meanings of the solutions to applied problems, attaching the appropriate units to an answer; state which parts of a mathematical statement are assumptions, such as hypotheses, and which parts are conclusions. This free course may be completed online at any time. It has been developed through a partnership with the Washington State Board for Community and Technical Colleges; the Saylor Foundation has modified some WSBCTC materials. (Mathematics 005)

In this tutorial, we will learn to approximate differentiable functions with polynomials. Beyond just being super cool, this can be useful for approximating functions so that they are easier to calculate, differentiate or integrate. So whether you will have to write simulations or become a bond trader (bond traders use polynomial approximation to estimate changes in bond prices given interest rate changes and vice versa), this tutorial could be fun. If that isn't motivation enough, we also come up with one of the most epic and powerful conclusions in all of mathematics in this tutorial: Euler's identity.

This is an undergraduate course on differential calculus in one and several dimensions. It is intended as a one and a half term course in calculus for students who have studied calculus in high school. The format allows it to be entirely self contained, so that it is possible to follow it without any background in calculus.

Spreadsheets Across the Curriculum activity. In advance of an actual lab activity, students virtually simulate the calibration of a laboratory micropipettor. QL: Accuracy and precision.