Artificial Intelligence Lesson Plans (3 results)
Artificial intelligence (AI) is a branch of computer science that enables computers and robots to perform tasks requiring intelligence. The tasks can be as simple as programming a computer to play an easy game like tic-tac-toe or as challenging as having a computer diagnose and treat a sick patient. Sometimes artificial intelligence is used to get machines to do things that humans already do well, like using spoken language to communicate. Other times AI is used to do tasks that are hard for humans, like predicting how new proteins might fold up into 3D structures and how those structures interact with other nearby proteins.
Machine learning is a subfield of AI where a machine "learns" how to do something without the programming telling it exactly how to deal with every step. In machine learning, a computer is given data from which it builds a model, and that model can repeatedly be trained, tested, and have more data added until it performs well. Companies are using machine learning to build robots that walk, self-driving cars, computers that can compose music, and many other types of technology.
You can try your hand at AI and machine learning with these exciting projects and experiments.
Classifying happy and sad faces is an easy task for most humans, but can we teach a machine to do it? In this fun lesson, students will use machine learning to try this out and see how easy it is for bias to creep in. This experiment requires no computer programming skills! In an optional extension, students will also use their imaginations to explore the potential benefits and dangers of artificial intelligence solutions. This lesson will give students an awareness of how prevalent artificial…
NGSS Performance Expectations:
Define the criteria and constraints of a design problem with sufficient precision to ensure a successful solution, taking into account relevant scientific principles and potential impacts on people and the natural environment that may limit possible solutions.
Evaluate competing design solutions using a systematic process to determine how well they meet the criteria and constraints of the problem.
Try our new Science Project Pathways in Google Classroom. One tool to plan, assign, and manage a science project in your class.
Simply enter the project start date to get a customizable science project schedule that breaks the science project into a series of smaller more manageable assignments to keep students on track. The assignments use Science Buddies guide to the scientific method to take students step-by-step through a science project. From the schedule, teachers can make assignments in Google Classroom and view student progress on each assignment.
This eight-part lesson will guide you through building and programming Arduino-controlled autonomous cars with your students. Each part contains a detailed step-by-step video and a supplemental lesson plan PDF with learning objectives, assessment opportunities, and appendices with circuit diagrams and example code. You can present the material yourself or have students follow along with the videos and pause to work on their autonomous cars.
NGSS Performance Expectations:
Design a solution to a complex real-world problem by breaking it down into smaller, more manageable problems that can be solved through engineering.
Using the Netlogo platform to run simulations of a basic neural network called the perceptron, students explore a basic, yet powerful, model of machine learning as they are challenged to understand the logic. Students engage in the perceptron model and discover a weakness of the model. The students then move on to run simulations on Netlogo with the multi-layer perceptron which overcomes the weakness in the original perceptron model. Engineering Connection
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