Leon Furze

Over the past few weeks I have introduced six new strategies for using Generative AI in education. These posts have focused in particular on text-based LLMs like GPT and Claude 3.5 Sonnet, and have explored the following six areas:

• Designing
• Differentiating
• Engaging
• Imagining
• Editing
• Evaluating

If you haven’t already, make sure you check out those two posts:

This post kicks off a series where I’ll explore each Strategy in much more depth, looking at the ideas which underpin each area, how the technology has developed in the past 18 months, and applying the three levels of AI use from an earlier post. These posts are intended to deepen your understanding of GenAI in education whether you’re a beginner or you’ve been using these tools for a long time.

In my experience working with educators and Generative AI for over two years, I’ve experienced time and again that teachers and university lecturers want to understand both the technical strengths and limitations, and the pedagogical rationale for using these tools. It’s not enough to throw around a bunch of acronyms for prompting, or platforms which “add sparkle” and generate lesson plans with button clicks.

Each of these Strategies has a clear purpose in an educational context. They are designed for educators to use in their day-to-day work and have been refined and developed through work with hundreds of teachers and lecturers. since the release of ChatGPT in November 2022.

I’m starting with Designing.

The Importance of Design

First, a little bit of theory. When I say “Design”, I’m not just talking about the process or the act of sketching out lesson plans and resources. I’m bouncing off Gunther Kress and Theo Van Leeuwen’s concept of design in education, which examines the intentional shaping of learning experiences through multiple modes of communication. It views curriculum development as a creative act, sensitive to social and cultural contexts.

Historically, educators had significant autonomy in curriculum design. They were seen as curriculum makers, actively involved in crafting what and how students learn. In my context – teaching English in Victoria, Australia – this can be seen through work like Fleur Diamond and Scott Bulfin’s article Care of the profession: teacher professionalism and learning beyond performance and compliance.

The article describes a period in Victoria during the 1980s and early 1990s when teachers had significant input into curriculum and assessment reform. It highlights that during this time, there was a government-supported infrastructure for teacher professional development and curriculum implementation that positioned teachers as key stakeholders and decision-makers. This included regional consultants, teacher networks, and committees where teachers had representation. Diamond and Bulfin frame this time as a “high watermark of teacher input into curriculum, assessment and educational practice”, contrasting it with later retrenchments that reduced teacher autonomy.

Over time, curriculum reforms have shifted educators from designers to deliverers of curriculum. This change stems from pushes for standardisation, increased accountability measures, centralised decision-making, efficiency-driven reforms, and the integration of more and more technology in education.

These reforms have often resulted in reduced teacher autonomy, increased focus on delivering pre-designed content, and less emphasis on contextual adaptation. Critics (myself included) argue this diminishes teachers’ professional role and may lead to less engaging and effective learning experiences.

Generative AI could be fuel to this fire.

We are already seeing a tsunami of sparkly apps which position AI as a magical solution to workload, stress, and the “problem” of lesson planning and resource creation. Viewed from the perspective of teachers as designers, these apps are not an innovative technological solution: they’re simply an extension of approaches which began in the 80s and 90s and have increasingly deprofessionalised educators.

Although it’s common for new graduate teachers – and even experienced ones – to feel overwhelmed when they enter a new school without curriculum materials, the answer doesn’t lie in off-the-shelf lesson resources, AI generated or not. Instead, the solution involves developing a culture of professional learning and collaboration that empowers teachers to engage in curriculum design as a thoughtful, committed practice.

When using generative AI tools for lesson planning or curriculum development, it’s important to keep this concept of ‘design’ at the forefront. These tools should be seen as aids to spark ideas or provide starting points, not as replacements for teacher expertise and creativity. Teachers should approach AI-generated content critically, adapting and refining it to suit their students’ needs, their educational philosophy, and the specific context of their classroom and community. This way, teachers remain active designers of learning experiences, using technology to enhance rather than replace their professional skills and judgment.

Designing with GenAI

In the first More Practical Strategies post I gave two examples of ‘Designing’ prompts: using AI to draft a comparison of cross-curriculum achievement standards, and uploading curriculum documents to draft a unit plan aligned with the design thinking cycle.

To further demonstrate how AI might be used for “design” work, here are five more ideas:

First of all, a curriculum design prompt which uses resources from the local community and an internet-connected model (such as GPT-4o, Copilot, or Gemini) to connect the local issues to the UNSDG. The prompt is comprehensive and detailed, and relies on the educator to provide the additional local context.

Design a project-based learning unit that integrates local environmental issues with global sustainability goals for Year 10 Geography. Use internet browsing to research current environmental challenges in and connect them to at least three of the UN Sustainable Development Goals. Create a unit outline that includes learning objectives, key activities, and assessment tasks. Ensure the unit incorporates elements of fieldwork, data analysis, and community engagement.

This prompt uses the AI’s ability to research local and global issues, synthesise information, and create a structured unit plan that aligns with curriculum standards and incorporates real-world relevance.

The next example uses GenAI in an administrative context to help plan a collaborative faculty meeting where the team members are designing a curriculum aligned to 21st-century skills (or 6Cs, or General Capabilities, or whatever you call them in your context). AI could also be used to record the minutes of the meeting, transcribe notes, and so on.

Create a faculty meeting agenda focused on reimagining assessment design to better capture 21st-century skills and competencies. The meeting should cover: 1) A review of current assessment practices, 2) An introduction to key 21st-century skills and competencies, 3) Breakout sessions for brainstorming new assessment methods, and 4) Next steps for implementing changes. Include discussion questions and potential resources for each agenda item.

Next, this “artifact” from Anthropic’s Claude creates a tool to help visualise the connections between curriculum areas, based on the actual curriculum documents. This kind of tool might help with curriculum planning meetings and cross-curricular planning.

Design a curriculum mapping tool that visualises connections between Year 8 English and Science, skills, and real-world applications for a K-12 school. The tool should:

1. Allow input of curriculum standards from multiple subjects and grade levels
2. Identify and display cross-curricular connections
3. Link skills and knowledge to potential career paths and real-world scenarios
4. Generate reports highlighting areas of strong integration and gaps in coverage
   

Describe the key features and user interface of this tool, and explain how it could be used to inform curriculum development and instructional planning. Create an artifact.

This prompt demonstrates how Claude can create educational tools, combining curriculum analysis with data visualisation and practical applications. You can look at this prototype and ‘remix’ it here: https://claude.site/artifacts/9ccc1ef7-e55b-4092-a7ae-4ca5d3e23240

Part of designing quality lessons and units of work involves speaking to colleagues, students, and the community. Obviously a huge barrier to that is the amount of time required, and the need for someone to coordinate those efforts. Generative AI can be used to assist in the administrative aspects of this kind of curriculum design work.

Create a collaborative curriculum design survey tool that facilitates input from teachers, students, and community members. The survey should gather feedback on:

1. Current curriculum strengths and areas for improvement
2. Desired learning outcomes and skills
3. Preferences for teaching and learning methods
4. Ideas for community involvement and real-world connections

Design a set of questions for each stakeholder group (teachers, students, parents/community members) and suggest methods for analysing and incorporating the survey results into curriculum planning.

Last of all, AI can be used in the audit/review process when designing new unites and resources, providing an extra perspective on the work.

Conduct a curriculum audit/review to design a system for integrating emerging technologies and future skills into the existing curriculum framework. The audit should:

1. Identify current coverage of technology skills and future-oriented competencies
2. Analyse gaps between current curriculum and projected future skill needs
3. Suggest modifications to existing units or courses to incorporate emerging technologies
4. Propose new courses or learning experiences to address future skills
5. Recommend professional development needs for educators
6. Create a report summarising the audit findings and providing a roadmap for curriculum updates over the next 3-5 years.

This prompt demonstrates how AI can assist in complex curriculum analysis and planning, integrating multiple sources of information to provide advice.

Key ideas for Designing with GenAI

To wrap up this exploration of designing with generative AI in education, here’s a summary of key ideas that educators can keep in mind when approaching the technology.

1. Maintain your agency and creativity in the design process
2. Use GenAI as a tool to enhance, not replace, professional judgement
3. Use GenAI for research and cross-curricular connections by uploading multiple contextual documents
4. Use GenAI to streamline administrative tasks, freeing up time for meaningful design work
5. Gather and analyse diverse perspectives in curriculum development by using GenAI to develop surveys and similar tools

The concept of ‘Design’ stresses the importance of keeping the educator at the centre of the curriculum development process while making use of the GenAI for administrative tasks. In my experience, educators don’t want to click a button that generates their lesson plans: they want the time, the support, and the collaboration needed to create rich and meaningful resources for their students.

Want to learn more about GenAI professional development and advisory services, or just have questions or comments? Get in touch: