Macquarie University
Artificial Intelligence (AI) Education for Teachers
Macquarie University

Artificial Intelligence (AI) Education for Teachers

Taught in English

Some content may not be translated

17,190 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Dr Anne Forbes
Dr Markus Powling

Instructors: Dr Anne Forbes

4.7

(407 reviews)

Beginner level

Recommended experience

16 hours to complete
3 weeks at 5 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • 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

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Assessments

14 quizzes

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There are 6 modules in this course

In this module we'll introduce you to the course, tell you a little bit about why we think it's important that you and your students know about artificial intelligence (AI), and share with you some additional resources that might be useful.

What's included

2 videos8 readings3 discussion prompts

In his book, “Make. Think. Imagine”, John Browne writes: “Artificial intelligence seems to be everywhere”. Some of its recent applications and achievements are well known; its potential to help build – or undermine – our civilisation is immense. As teachers, it’s hard for us to ignore this potential. AI is changing the tools we have at our disposal and adds to the impetus for a curriculum which incorporates the so-called "21st century skills". In this module, you will think about how AI may be defined, particularly in relation to human intelligence, and how it has taken different forms. You will consider how it has evolved over the last 70 years and come to show promise in so many different applications.

What's included

1 video17 readings4 quizzes6 discussion prompts2 plugins

Both design thinking, and critical and creative thinking (CCT), embrace skills which are important for teams working to solve problems with AI. In design thinking, these skills include collaboration, solving a problem with constraints, coming up with an idea, testing it, and if necessary, going back to the drawing board. The process is iterative. As for CCT, creative thinking is required to identify opportunities for AI, and critical thinking can help us evaluate its application. In this module, you will learn about the key principles and stages in the design thinking process. You will consider CCT from the perspective of convergent and divergent thinking, de Bono's Six Hats, and ACARA's four quadrant model. Examples of "creative AI" will be examined to help us understand the barriers to machine creativity.

What's included

1 video21 readings3 quizzes4 discussion prompts3 plugins

When it comes to computational thinking skills, there are two people who’ve been very influential in bringing them to the classroom. One is Seymour Papert who in the 1960s developed a computer program for children. The other influential person is Jeanette Wing, a data scientist, who wrote a short article advocating the use of computational thinking. In this module, you’ll appreciate that human or AI decision-making depends crucially on the quality of data. You’ll think about what data is, how it takes different forms and can be represented in different ways. Using the website, Machine Learning for Kids, we will look at what has been a classic problem in image recognition: being able to distinguish between cats and dogs. You’ll also learn about just what computational thinking is, its place in the Australian Curriculum, and the ideas and skills behind it. You’ll see how these skills can be developed with both “unplugged” and computer-based activities.

What's included

1 video20 readings4 quizzes3 discussion prompts2 plugins

Back in the 1940s, one of the grand masters of science fiction, Isaac Asimov, introduced into his stories the "laws of robotics" which were designed to protect humans from wayward machines. While machine intelligence has not evolved in ways that Asimov could have foreseen, there is still a need to ensure that AI works for the good of society. In this module, we will explore some of the ethical issues associated with AI. We will look at a CSIRO framework to help deal with these issues. We will see that decisions or predictions based on AI can be just as biased and prejudicial as those made by human individuals and groups. The Human Rights Commission recently reported the results of a poll designed to garner support for a variety of protective measures (Hunter, F. 'Human Rights Commission warns government over “dangerous” use of AI.' SMH, August 15, 2020). For example, it might be considered important that people should know when a decision which affects them, has been made by computer and that they have the right to appeal against such a decision.

What's included

1 video12 readings3 quizzes2 discussion prompts1 plugin

In this module we'll summarise the course, and remind you of some options you might like to utilise in your future teaching practice.

What's included

1 video2 readings1 discussion prompt

Instructors

Instructor ratings
4.6 (212 ratings)
Dr Anne Forbes
Macquarie University
1 Course17,190 learners
Dr Markus Powling
Macquarie University
1 Course17,190 learners

Offered by

IBM

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