1. Citizen Science
2. Stop Motion Animation
3. Astronomy & Stargazing
4. Virtual Field Trips
5. Coding & Robotics
6. Weather Tracking
7. Plant a Garden
8. Music & Sound Experiments
9. Augmented Reality Science
10. Other Experiments & Simulations
TWENTY amazing lessons to teach computer science to Grades 3 to 5.
The curriculum is organized into 5 units: Scratch Review, Creative Commons, Makey Makey, Conditionals and Final Project.
If you need something easier be sure to use the Green level (Level 1) by using the tabs at the top of the website or finding it in the resource bank. If you need something harder head to Purple (Level 3) using the same method.
This fabulous resource has everything you need to get started coding and computer science with your students TODAY!
TWENTY amazing lessons to teach computer science to Grades 3 to 5.
The curriculum is organized into 5 units: Scratch review, variables, Makey Makey, advanced games and final project.
If you need something easier be sure to use the Green level (Level 1) or Blue level (Level 2) by using the tabs at the top of the website or finding it in the resource bank.
This fabulous resource has everything you need to get started coding and computer science with your students TODAY!
Today we’re going to discuss how 3D graphics are created and then rendered for a 2D screen. From polygon count and meshes, to lighting and texturing, there are a lot of considerations in building the 3D objects we see in our movies and video games, but then displaying these 3D objects of a 2D surface adds an additional number of challenges. So we’ll talk about some of the reasons you see occasional glitches in your video games as well as the reason a dedicated graphics processing unit, or GPU, was needed to meet the increasing demand for more and more complex graphics.
Over 40 free online escape rooms to use with your class. They are already made and free!
ASP is a powerful tool for making dynamic and interactive Web pages.
In our ASP tutorial you will learn about ASP, and how to execute scripts on your server.
So now that we’ve built and programmed our very own CPU, we’re going to take a step back and look at how CPU speeds have rapidly increased from just a few cycles per second to gigahertz! Some of that improvement, of course, has come from faster and more efficient transistors, but a number hardware designs have been implemented to boost performance. And you’ve probably heard or read about a lot of these - they’re the buzz words attached to just about every new CPU release - terms like instruction pipelining, cache, FLOPS, superscalar, branch prediction, multi-core processors, and even super computers! These designs are pretty complicated, but the fundamental concepts behind them are not. So bear with us as we introduce a lot of new terminology including what might just be the best computer science term of all time: the dirty bit. Let us explain.
Today we’re going to take a step back from programming and discuss the person who formulated many of the theoretical concepts that underlie modern computation - the father of computer science himself: Alan Turing. Now normally we try to avoid “Great Man" history in Crash Course because truthfully all milestones in humanity are much more complex than just an individual or through a single lens - but for Turing we are going to make an exception. From his theoretical Turing Machine and work on the Bombe to break Nazi Enigma codes during World War II, to his contributions in the field of Artificial Intelligence (before it was even called that), Alan Turing helped inspire the first generation of computer scientists - despite a life tragically cut short.
In the first of two sequential lessons, students create mobile apps that collect data from an Android device's accelerometer and then store that data to a database. This lesson provides practice with MIT's App Inventor software and culminates with students writing their own apps for measuring acceleration. In the second lesson, students are given an app for an Android device, which measures acceleration. They investigate acceleration by collecting acceleration vs. time data using the accelerometer of a sliding Android device. Then they use the data to create velocity vs. time graphs and approximate the maximum velocity of the device.
Instructors can now freely access "App Development with Swift" through the Canvas Commons. The course includes lessons, teacher guides and developer tools for use in the classroom.
You will need to work with apple products or iOS for this resource.
AppML stands for Application Modeling Language.
AppML runs in any HTML page. No installation is required.
AppML is a tool for bringing data to HTML applications:
From objects
From files
From databases
"Quick, grab-and-go lessons to help your students think critically about AI and its impact.
Artificial intelligence (AI) is rapidly transforming the world we live in. From using generative AI for schoolwork to dealing with misinformation and befriending AI chatbots, students have a lot to consider when it comes to this ever-evolving technology.
This collection of quick lessons (20 minutes or less!) provide an introduction to AI and help address its social and ethical impacts. Through these lessons, students will:
Understand what AI is and how it works
Consider some of its potential benefits and risks
Think critically about how we can be responsible and ethical users of AI"
Note - you will need to sign up for a free account to access lessons.
Verbs for ideas for projects or activities for each level of Bloom's Taxonomy,
Today, Carrie Anne is going to take a look at how those transistors we talked about last episode can be used to perform complex actions. With the just two states, on and off, the flow of electricity can be used to perform a number of logical operations, which are guided by a branch of mathematics called Boolean Algebra. We’re going to focus on three fundamental operations - NOT, AND, and OR - and show how they were created in a series of really useful circuits. And its these simple electrical circuits that lay the groundwork for our much more complex machines.
Aperçu : Bienvenue dans une autre leçon de codage Make Stuff Move. Cette deuxième leçon va vous montrer comment déplacer un servo à l'aide du bouton sur votre bouclier d'animation.
Students learn about the similarities between the human brain and its engineering counterpart, the computer. Since students work with computers routinely, this comparison strengthens their understanding of both how the brain works and how it parallels that of a computer. Students are also introduced to the "stimulus-sensor-coordinator-effector-response" framework for understanding human and robot actions.
"Thunkable enables anyone to build their own beautiful mobile apps. Using drag and drop code, students can start from scratch or remix a sample app. Created app projects are accessible on both iOS and Android platforms. Thunkable has an active community with regular design challenges to keep students thinking outside the box with their app creations." (AASL)
"With the free version of Thunkable, all app projects are set to public mode. This means that all projects are automatically included in the Thunkable Public Gallery, for anyone to preview and remix. With a PRO membership, you have the ability to create and edit private projects. This means that no one else will have access to your apps." There are paid versions available as well.
In the companion activity, students experimented with Arduino programming to blink a single LED. During this activity, students build on that experience as they learn about breadboards and how to hook up multiple LEDs and control them individually so that they can complete a variety of challenges to create fun patterns! To conclude, students apply the knowledge they have gained to create LED-based light sculptures.
In this lesson, students go further into the collection and interpretation of data, including cleaning and visualizing data. Students first look at the how presenting data in different ways can help people to understand it better, and they then create visualizations of their own data. Using a the results of a preferred pizza topping survey, students must decide what to do with data that does not easily fit into the visualization scheme that they have chosen. Finally, students look at which parts of this process can be automated by a computer and which need a human to make decisions.
In this lesson students get practice making decisions with data based on some problems designed to be familiar to middle school students. Students work in groups discussing how they would use the data presented to make a decision before the class discusses their final choices. Not all questions have right answers and in some cases students can and should decide that they should collect more data. The lesson concludes with a discussion of how different people could draw different conclusions from the same data, or how collecting different data might have affected the decisions they made.