Using Bloom’s Taxonomy AI Prompts for Lesson Design

There are plenty of challenges in the modern classroom for a teacher: challenging pupils (Both in terms of ability and behaviour), additional (as well as diverse) learning needs, parental expectations, smartphones, (cyber)bullying; hormones (male and female!). The list can easily go on! But with the advent and widespread adoption of AI into classroom activities, teachers can begin to incorporate this new tool into their daily practice and allow themselves to work a little less hard, but a lot smarter.

While AI can certainly create lesson plans, resource creation, personalised learning, and generate alternative formats for learning content for pupils with additional needs. From the teachers I have observed, chatted to and heard feedback from, lesson design and resource creation has by far made the greatest impact on teachers’ lives in reducing workload, but also ensuring they can continue to deliver high quality teaching and learning to their classes. AI can also incorporate specific pedagogies into our lesson content when we ask it to.  In this post, we’re going to look at how we can incorporate Bloom’s Taxonomy into our classroom teaching content.

An effective prompt that works well to create effective learning is the “Bloom’s Prompt.”  If you want to refresh your knowledge on Bloom’s Taxonomy, then take a look at this resource from Vanderbilt University’s Center for Coaching).

Using the template below, you can customise the prompt based upon your topic, pupil ability or intended learning goals.  Then, enter the prompt into your AI platform of choice (e.g. ChatGPT, Gemini, CoPilot).

“Generate a Bloom’s taxonomy for pupils learning [insert topic, skill, competency].”

Using Gemini, I entered the following prompt: “Generate a Bloom’s taxonomy for pupils learning python programming in year 10 in a UK post-primary school. This prompt generated the following response for me:

As you can see in the slideshow output above, the prompt generated a fairly comprehensive list of objectives across all six cognitive processes of Bloom’s Taxonomy. The infographic below (not AI generated) also shows a structured and itemised list of how we can apply Bloom’s Taxonomy to teaching programming in Key Stage 3.

Like any other AI prompt, with greater specificity comes results with higher quality content.  You can consider adding the following elements to the core prompt above to focus and tailor your AI results to your pupil, their learning needs, ability level and subject area.

1. Add your role. (e.g. “You are a teacher/curriculum designer with experience developing lessons and assessments.”)
2. Add the year group or grade level (depending on your school system/location) and subject area.
3. Add the number of examples you want (e.g. 5) and the format. (e.g. paragraph or bulleted list)
4. Ask the AI to provide more specific examples or differentiation for one (or more) of the listed objectives.

If you are new to AI prompts to help with lesson design, this is a great place to start.  For those that have more experience with AI prompts, try adding even more specificity and pushing the boundaries for how deep and complex the lesson design output can go.

Like all things edtech-related, the learning and the development come through playing with the tool and working the trial/error/improvement process to get an effective result to enhance your classroom teaching.

Have fun and let me know how it goes!