top of page

AI Educator Certificate

ev-gpjvRZyavZc-unsplash.jpg

AI is advancing at rapid rates, leaving educators to guess at how to respond and what to focus on. In this program, Mark Barnett, an educator and  PhD researcher on AI in Education will share the fundamental principles and behaviors that all AI systems have in common, which in simple terms, is just advanced prediction. By learning about the foundations of how AI works, educators will have the necessary information to make decisions about how, when and why AI can be used for a variety of purposes in education.

​

This training will provide a comprehensive exploration into AI to help build an AI literacy and equip teachers with practical AI tools that can be used in the classroom across all subject areas. Most importantly, educators will be able to navigate the changing scene of AI by starting with a strong pedagogical foundation.

 

The AI Educator Certificate training will take place over 3 days consisting of 90 mins of asynchronous training followed by 90 mins of synchronous time for educators to work on assignments. Completion of all activities will result in receiving the AI Educator Certificate.

Audience: K-12 Classroom Teachers, School Leaders

Duration: 3 days - each day consisting of 90 mins of asynchronous training followed by 90 mins of synchronous time for educators to work on assignments

​

Topics of the AI Educator Certificate program:

​

Day 1

Introduction to AI

In this section we will briefly explore how AI has emerged and how AI has advanced.

  • AI as a powerful prediction tool

  • Types and uses of AI systems

  • How does AI learn?

  • Brief history of AI

 

AI in Education
In this section we will learn about ways that AI is being used in Education systems as well as how the teaching of AI is unfolding in schools.

  • AI Tutors

  • AI grading

  • AI learning tools

  • AI chat and writing tools

  • Legality of AI tools (student data)

 

Pedagogy that supports AI

In this section we will explore frameworks about teaching AI to students

  • Big 5 ideas in AI education

  • Constructionism and AI

  • Tinkering and AI

 

Homework:

Explore a variety of language-based AI tools to see how they work, what are the weaknesses and how can they be leveraged

​

Day 2

Explore Machine Learning Foundations (without code)

In this section we will explore some AI tools that educators can use in the classroom for image, sound, and pose classification.

  • What is Machine Learning?

  • Predictions based on training

  • How to train your AI

 

Bias in the Algorithm

In this section we will explore the nature of bias, how it appears, and how to train an AI to reduce bias.

  • Negative effects of bias

  • Pre-trained Neural Networks

  • Adjusting for bias in training data

 

Make your own AI tool

In this section, you will learn to use and train a Machine Learning tool

  • Develop your own image recognition model

  • Train the model using images you provide

  • Test its ability to correctly predict and avoid data bias

 

Homework:

Complete the development of your AI Image Recognition model and test out the accuracy and describe what types of bias exist in your model.

​

Day 3

Enhancing your workflow with ChatGPT (or similar)

In this section, we will explore how language and chat based AI tools can help you write lessons, brainstorm or develop learning materials.

  • Design a prompt to make a new lesson

  • Explore how students can use ChatGPT as a co-author

 

Generative AI Tools

In this section, we will explore AI tools that produce images and videos

  • Make a set of graphics and images for your lessons

  • Make a video avatar of yourself 

 

Going Further
In this section, we will explore some tools and resources for going further

  • MIT Curriculum

  • ISTE Educator Resources

  • Online AI toolkits

  • Using AI across the subject areas

 

Homework:

Complete one of the programming challenges and share your project to the cohort

Please contact info@consiliencelearning.org
if you would like to offer this course for your faculty.

Instructor:

Mark-Barnett.jpg

Mark Barnett is currently pursuing his PhD in Computer Engineering and is studying how students can benefit from learning about AI in ways that help them self-reflect on their own learning process by learning how AI learns. Mark has also developed a globally used AI curriculum that teaches the fundamentals of AI image-recognition. Mark has worked in education for over 15 years as an International educator, consultant, and Ed-tech leader who has provided training in topics such as Maker Learning, Project Based Learning, and Constructionist Pedagogy.

​

Click here to read an article where Mark predicted the shift in AI and how it would affect schools, which was published in the summer of 2022, before the release of ChatGPT.
Click here to read an article about how Mark has helped a school in Bangkok to develop AI literacy for educators.

bottom of page