Artificial intelligence (AI) is already changing education in Australia, whether we’re ready for it or not. That was the takeaway from George Siemens’ keynote address at the Australian Association for Research in Education conference in November. He went on to suggest that unless researchers and teacher educators are mindful, they may not have a seat at the table in deciding what the future of education will look like.
This article is about the future of AI-generated lesson plans and how we might think about this development today and into the future. Think of it as a concrete case study of exactly what Professor Siemens, who is director of the Centre for Change and Complexity in Learning at UniSA Education Futures, was talking about and where the conclusions might apply to other areas of education.
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What do AI-generated lesson plans look like?
AI-generated lesson plans are already better than many people realise. Here’s an example generated through the GPT-3 deep learning language model. The prompt was: a lesson plan for English for teaching 16-year-old students about the idea of “juxtaposition” within Romeo and Juliet. This is the output from GPT-3 (verbatim, with formatting provided by the algorithm):
Background
Juxtaposition is the act of placing two things side by side, often for contrast. In literature, authors often use juxtaposition to create a certain mood or atmosphere, or to emphasize certain qualities of a character or situation.
In Romeo and Juliet, Shakespeare uses juxtaposition extensively to contrast the two lovers and their families, the Montagues and the Capulets. He also uses juxtaposition to contrast the tragic events of the play with the light-hearted moments.
Objectives
By the end of the lesson, students will be able to:
– Understand the concept of juxtaposition
– Identify examples of juxtaposition in Romeo and Juliet
– Explain how juxtaposition is used to create mood and atmosphere in the play
Materials
– A copy of Romeo and Juliet
– A whiteboard and markers
– A teacher-created handout with examples of juxtaposition from the play (optional)
Procedure
1. Introduce the concept of juxtaposition to the class. Explain that authors often use this literary device to create contrast and emphasize certain qualities.
2. Ask the students to think of an example of two things that are often juxtaposed. Write some of their responses on the board.
3. Tell the students that they are going to be looking for examples of juxtaposition in Romeo and Juliet. Explain that they should pay attention to how the contrast created by the juxtaposition contributes to the mood and atmosphere of the play.
4. Give the students time to read through the play, or assigned sections of the play if time is limited. As they are reading, they should be looking for examples of juxtaposition.
5. Once the students have finished reading, ask them to share the examples of juxtaposition that they found. Write these examples on the board.
6. Finally, ask the students to explain how the juxtaposition affected the mood and atmosphere of the play. What did it emphasize about the characters or the situation?
Extension Activity
Have the students find additional examples of juxtaposition in other works of literature, or in everyday life. They can share their examples with the class and explain how the contrast created by the juxtaposition contributes to the overall effect.
Imagine that you’d set a task for a class of second-year Bachelor of Education students to create a lesson plan with that same prompt. How do you think the AI response would compare with those of some of your students?
Anybody can generate their own lesson plans for a year level, subject area and topic that interests them with a similar prompt.
Concerns and opportunities around AI-generated lesson plans
It is trivially easy to generate useful lesson plans using this technique. One obvious upshot is that setting assessment tasks for any students in initial teacher education that involve them creating lesson plans isn’t a great idea any more. It’s too simple for them to generate one.
Yet there are new opportunities that arise:
- Why not get students to generate a few lesson plans, look at the patterns and write something about the essential structure of this thing that we call a “lesson plan”?
- Why not get them to take a generated lesson plan and improve it, annotating the reasons why their changes have made it better?
Another legitimate concern is that in-service teachers might start to use the next generation of AI-generated lesson plans (which will undoubtedly be an order of magnitude more powerful) without critique – or, worse, that some jurisdictions might request that teachers use such an approach in future.
A word that we need to look to is ‘design’
Consideration of design can address the issues raised by AI regarding lesson plans, and in many other places in education. When design in education is done well (whether that’s learning by design, design thinking or co-design or within the subject area named “design”), it places an emphasis on two things:
- authentic problems, such that the learner must always construct an interpretation of the problem before they can address it
- process and rationale, such that the output that the student produces is impressive only if their process and rationale support what they’ve done.
When assessments follow these two ingredients, educators can give students free rein to use whatever tools they have at their disposal. The adoption of AI stops being a concern. When students are being assessed through their process rather than their output, they can use whatever tools are available. The challenge is integrating use of such tools into solving problems through collaboration, critical thinking, cultural understanding and creativity.
Design as a response to ‘what should be taught’
George Siemens concluded his presentation by suggesting a list (controversially) of what should be taught in the context of an AI future. A summary/interpretation of his key points of what we should be teaching is:
- beingness: what it means to be human in the world, the interconnectedness of all things
- systems thinking: how systems change and what complexity is about
- technology and how to use it: machine learning and data literacy, computational thinking, collaborating with non-human intelligences.
Increasingly, design has become a part of education: design for learning, learning by design, thinking and so on. The epistemic fluency to design using computational tools in a way that enriches material life and human culture is at the root of all three areas.
For any subject area, teaching using a design approach shifts the focus from knowing content to knowing process. It becomes less about how to get from A to B in a straight line and more about knowing how to frame problems, use tools and communicate outcomes. More design in education provides one way of responding to this increased presence of AI in education, whether we’re ready for it or not.
It might even provide a response to Professor Siemens’ provocation about McKinsey, Deloitte or Microsoft trying to get in on a slice of the education sector. Education conceived as design – process rather than output – prioritises the humans involved in the enterprise and makes it harder to sideline educators.
Nick Kelly is a senior lecturer in interaction design in the School of Design, and Kelli McGraw is a lecturer in the School of Teacher Education and Leadership; both in the Faculty of Creative Industries, Education and Social Justice at the Queensland University of Technology.
This is an edited version of the post “The AI future for lesson plans is already here”, which was published on the Australian Association for Research in Education blog, EduResearch Matters, on 29 November 2022.
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