In the past two years I have worked with hundreds of educators in K-12 and Higher Education, helping them to understand the ethical and practical implications of generative artificial intelligence. Often, once people see what tools like ChatGPT and Claude are capable of, conversations turn to curriculum design, lesson planning, and the creation of resources.
But this important area of a teacher’s profession has also been treated as “low hanging fruit” by edtech companies and governments. Just recently in Western Australia, for example, the state government has earmarked $4.7 million for a GenAI pilot to “reduce teacher workload” and admin, with “lesson planning” one of the only administrative tasks mentioned.
Edtech companies such as the incredibly popular Magic School similarly prioritise these areas, with at least 40 of the 60+ “tools” on its site related to lesson planning and resource creation. “Lesson Plan” is also the first button on Khan Academy’s Khanmigo product, which was recently launched to the Australian audience at a major edtech conference.
It’s understandable that these companies and governments would target lesson planning as a quick-fix for AI, and it’s not even limited to this technology. In recent years in Australia, education think tanks have proposed off-the-shelf lesson plans and resources as a solution to the “teacher workload crisis”. Of course, these same think tanks are ready to swoop in and save the profession with these very resources.
Many educators, myself included, think that this is the wrong approach.
In this post, I’ll argue that the current push to use AI and other technologies for lesson planning and resource creation is misguided. This approach not only misses the mark on addressing real teacher workload issues but also risks undermining the professional autonomy and expertise of educators. I’ll take a look at some actual research into teacher workload, compare that to the claims of edtech companies and education think tanks, and explore the complex web of interests at play.
What Actually Contributes to Teacher Workload?
If you ask any group of educators about their administrative tasks, you’ll get a comprehensive list of jobs which extend far beyond teaching and learning. There is a great deal of research across the world exploring teacher workload, and quick scan reveals some interesting findings.
In a 2018 NSW study, for example, 91% of teachers reported feeling burdened by data collection, paperwork, compliance, and reporting. The AITSL 2020 review of “red tape” similarly highlights a range of administrative tasks including extensive data collection and reporting, financial accountability measures, compliance with various regulations, and tasks which significantly detract from core teaching and learning activities.
Creagh et al.’s 2023 research synthesis, Workload, work intensification and time poverty for teachers and school leaders, also reveals several major contributors to teacher and school leader workload. These include administrative tasks often referred to as “paperwork”, increasing accountability requirements such as reporting and meetings, data collection and analysis related to student performance and behaviour, implementation of curricular reforms, and various non-teaching duties like pastoral care.
Frequently though, something is missing… Where are all of the teachers concerned with the burden of lesson planning? That’s where it starts to get even more complicated.
Is Lesson Planning a Burden?
The AITSL report mentioned above, for example, deliberately excludes tasks which “contribute to school improvement” including planning and professional learning. In similar workload research from the UK, the Department focuses on everything except lesson planning, including health and safety, attendance, photocopying, excursions, incursions, and updating the school website. An Australian Education Union report features lesson planning as a very high component of teacher workload, but the teachers surveyed also report that if they were given more time they’d choose to spend it on “planning effectively to meet your students’ individual learning needs”.
In fact, you have to look hard to find evidence of teachers blaming their workload on the supposed burden of lesson planning and resource creation. Specifically, you have to turn to the kind of research from think tanks mentioned earlier, such as the report Ending the Lesson Lottery produced by the Grattan Institute in Australia.
Deakin University’s Carly Sawatzki critiques the approach in a recent blog post for AARE. The article questions the neoliberal approach to education policy in Australia, arguing that market-driven reforms and standardisation have negatively impacted teaching and learning. Framing schools as production lines with standardised inputs and outputs has led to increased administrative burdens on teachers, reduced professional autonomy, and the rise of “edupreneurism” – commercial solutions promising quick fixes.
I would now include AI-powered lesson planning apps in that category. The connections between the “lesson lottery” approach and that taken by edtech have many similarities. They each come with the caveat that they’re not trying to “replace teachers” or devalue teacher expertise, but it is hard to see how encouraging reliance on commercially generated or produced lesson plans and resources does anything but.
Dr Jordana Hunter, program director at Grattan Institute, chaired a panel earlier this week featuring Sal Khan of Khan Academy. The panel came on the back of Khan’s headline act, introducing the “free” AI-powered product Khanmigo into the Australian market. Questions centred on the need for solutions which reduce teacher workload while respecting their professionalism.
The language these organisations use is remarkably similar, from Grattan’s call for governments to “Reduce the need for teachers to ‘re-invent the wheel’ in curriculum and lesson planning, to ease their workload and boost teaching quality” to Khan Academy’s platform “designed to significantly reduce the time educators spend on preparatory tasks, which studies show can consume more than 50% of their workload.”
But again, it’s hard to see how engendering a reliance on pre-prepared or AI generated lesson plans celebrates teacher autonomy. While Early Career Teachers and out of field teachers in particular might benefit from more support, it doesn’t necessarily have to be produced by these organisations.
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Complex Networks
Finally, it’s worth interrogating the relationships between all of these various players. Deakin University’s Emma Rowe does a fantastic job of this in papers like this one exploring the impact of philanthropy in public education.
At the risk of sounding like I need to grab my tin foil hat, there are deep, broad, and complex connections between the tech companies, venture philanthropists, and not-for-profit education organisations who are the most vocal in promoting the reduction of workload through offloading lesson planning and curriculum design.
Take, for example, the recent announcement of Khan Academy’s AI-powered Khanmigo being made free for teachers globally. This initiative is funded by Microsoft, who also invest heavily in the GPT large language model that powers the platform. Meanwhile, organisations like the Bill & Melinda Gates Foundation indirectly influence education policy through their funding of various intermediaries including philanthropic organisations like SVA, who are deeply connected to AERO, an evidence and research organisation in turn promoted by Grattan in their recommendations.*
These interconnections raise important questions about the motivations behind the push for AI-powered lesson planning tools. Are these solutions truly aimed at addressing teacher needs, or are they driven by commercial interests and a particular vision of education that aligns with the goals of tech companies and venture philanthropists? As educators and policymakers, we need to critically examine these relationships and their potential impact on the future of teaching and learning.
So How Can AI Really Help?
When I sat down this morning, I intended on writing a totally different post. I was going to suggest a framework for curriculum design which keeps educators in the driving seat whilst using Generative AI, and which does not rely on commercially produced or generated resources but instead on the expertise of the educators themselves. I’ll make that post next week instead.
I think it’s important that we first come to terms with the complexity underpinning narratives around these platforms, and the uses of technology like Generative AI in curriculum design.
The research into teacher workload tells us the aspects of education that educators want to reduce: data collection and interpretation, administration, compliance, communications, behaviour management, and reporting. These are, with the possible exception of behaviour, all areas where AI can assist. In fact, there are much more suitable technologies which can help reduce the burden of data management which have nothing at all to do with Generative AI.
Before grabbing for the low hanging fruit of lesson plans, edtech companies, government, and other interested organisations should have serious discussions with educators about how they want to use AI.
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* This comment was corrected as it originally stated that AERO is a beneficiary of funding from the Bill and Melinda Gates Foundation – this was an error which was pointed out by a Director at AERO.
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