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Artificial Intelligence (AI) Education for Teachers

Approx. 16 hours to complete

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Course Summary

This course teaches teachers how to integrate artificial intelligence into their classrooms. It covers topics such as machine learning, natural language processing, and computer vision.

Key Learning Points

Learn how to integrate AI into your teaching methods
Understand the basics of machine learning and other AI technologies
Discover how AI can enhance the learning process for students

Learning Outcomes

Ability to integrate AI into teaching methods
Understanding of machine learning and other AI technologies
Improved ability to enhance student learning through AI

Prerequisites or good to have knowledge before taking this course

Basic understanding of programming concepts
Familiarity with educational technology

Course Difficulty Level

Intermediate

Course Format

Online
Self-paced

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Machine Learning for Educators
AI for Everyone
Data Science in Education

Related Education Paths

Notable People in This Field

CEO of the Teaching and Learning Collaborative
Professor of Learner Centred Design at University College London

Related Books

Description

Today’s learners need to know what artificial intelligence (AI) is, how it works, how to use it in their everyday lives, and how it could potentially be used in their future. Using AI requires skills and values which extend far beyond simply having knowledge about coding and technology.

This course is designed by teachers, for teachers, and will bridge the gap between commonly held beliefs about AI, and what it really is. AI can be embedded into all areas of the school curriculum and this course will show you how. This course will appeal to teachers who want to increase their general understanding of AI, including why it is important for learners; and/or to those who want to embed AI into their teaching practice and their students’ learning. There is also a unique opportunity to implement a Capstone Project for students alongside this professional learning course. Macquarie School of Education at Macquarie University and IBM Australia have collaborated to create this course which is aligned to AITSL ‘Proficient Level’ Australian Professional Standards at AQF Level 8.

Knowledge

Compare AI with human intelligence, broadly understand how it has evolved since the 1950s, and identify industry applications
Identify and use creative and critical thinking, design thinking, data fluency, and computational thinking as they relate to AI applications
Explain how the development and use of AI requires ethical considerations focusing on fairness, transparency, privacy protection and compliance
Describe how thinking skills embedded in Australian curricula can be used to solve problems where AI has the potential to be part of the solution

Outline

Introduction
Welcome and introduction to Artificial Intelligence (AI) for Teachers
Overview of course structure
Why do teachers and students need to know about AI?
Course background and accreditation
Course structure and learning outcomes
Learning activities and resources
Student resources
Research study
Podcast with Professor Garry Falloon
Podcast with Toby Flavell

Knowledge Module: What is AI, History of AI, and Applications of AI
Introduction to AI, its history and applications
About this module
What is intelligence? (continued)
Strong AI
The development of narrow AI
Machine learning
Machine Learning for Kids
Definitions of AI
Intelligence augmentation
Relationships between AI and related areas
The Turing Test
Developments in computer hardware
Podcast with Professor Deborah Richards
Jeopardy
Autonomous cars
Types of AI
Podcast with Dr Bhavna Antony
Knowledge Module: Activities and resources
Topic 1
Topic 2
Topic 3
Knowledge Module

Skills Module - Part A: Design Thinking, and Critical and Creative Thinking
Overview of design thinking, and critical and creative thinking
About this module
History of design thinking
An important principle
What is design thinking?
Design thinking defined
Models of design thinking
Applying design thinking in an educational context
Podcast with Steve Nouri
Developing thinking skills
Unhelpful stereotypes of critical and creative thinking
Defining critical and creative thinking
Creativity in STEM
Creativity in STEM (continued)
Art as a catalyst for critical thinking
Introducing convergent and divergent thinking
Strategies for fostering thinking skills
Four elements of critical and creative thinking in the Australian Curriculum
ACARA's critical and creative thinking model
Creative AI
Podcast with Professor Emily Cross
Skills Module — Part A: Activities and resources
Topic 4
Topic 5
Skills Module — Part A

Skills Module — Part B: Data Fluency, and Computational Thinking
Overview of data fluency, and computational thinking
About this module
What is data fluency?
What is data?
Data in education
Definitions from the Mathematics Syllabus glossary
Garbage in, garbage out (GIGO)
Accuracy of decision-making
Examining a data set
Decision-making: Dog or cat?
Photographic data sets of dogs and cats
Training a machine learning model in MLFK
Data within a machine learning project
Podcast with Dr Cormac Purcell
Computational thinking influencers
Computational thinking in the Science and Technology syllabus
Computational thinking concepts
Unplugged activities
Device-based activities
Podcast with Dr Rolf Schwitter
Skills Module - Part B: Activities and resources
Data and decision-making in AI applications
Topic 6
Topic 7
Skills Module - Part B

Values Module: Ethical Decision Making, and Bias Awareness
Introduction to ethical decision making, and bias awareness
About this module
Closed-circuit television (CCTV) in schools
Personality-quiz app data
Pilots and AI
Podcast with Kaaren Koomen
Calling the shot
Bias in more consequential decisions
Cognitive biases
Prejudice rather than cognition
"The data is the code."
AI and discrimination
Values Module: Activities and resources
Topic 8
Topic 9
Values Module

Conclusion
Conclusion
Next steps

Summary of User Reviews

This course on artificial intelligence in education for teachers has received positive reviews from users. Many appreciated the comprehensive content and practical applications provided in the course, making it a valuable resource for educators looking to integrate AI into their teaching methods.

Pros from User Reviews

Clear explanations of AI concepts
Hands-on exercises to apply AI to education
Real-world examples of AI in education
Engaging and knowledgeable instructors
Useful resources and tools provided

Cons from User Reviews

Some technical concepts may be difficult to grasp for beginners
Limited interaction with other students
Course pacing may be too fast for some learners
Not enough focus on ethical considerations of AI in education
Assignments can be time-consuming

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