Cognitive Load & Clarity — How Generative AI Helps Students Avoid Overwhelm

Towards the end of the semester, my workload increases significantly. Exams, assignments, and summatives for multiple subjects require a lot of dense reading and comprehension of subjects with complex explanations. Sometimes I get a bit overwhelmed and don’t do as well as I like. It’s not that I’m bad at the topic; it’s just delivered in a way that overloads my memory. I recently listened to a podcast discussing the Cognitive Load Theory (CLT), and I recommend you take some time to listen, because it may help you or your student understand why they might be struggling with certain subjects at school. 

There are three types of loads according to the CLT. Intrinsic load is the inherent complexity of the subject itself. Extraneous load is the unnecessary effort caused by poor explanations or unclear structure. The last one is germane load, which is the effort exerted actually to learn and build understanding. Effective learning happens when teachers can properly manage intrinsic load, minimize extraneous load as much as possible, and maximize germane load. With teachers who handle multiple subjects, this can become challenging. However, there is a solution: well-designed AI tools that reduce confusion and create clarity, whilst still keeping the learning process meaningful and enjoyable.

To properly manage each load, it is helpful to first understand why overload happens. Psychologist George A. Miller proposed a theory that the human brain is only able to hold about 7 items at a time, give or take 2 – one of the reasons why early phone numbers were made up of 7 digits. The podcast touched on the concept of 4 things at a time, because modern research has shown that the true capacity is actually closer to that, especially under duress. In previous posts, I’ve mentioned how the brain organizes data into chunks, removing items deemed irrelevant and strengthening connections for oft-used memories. Having too many new concepts, unclear explanations, and a lack of structure messes with this process, resulting in overloading. So, the key to preventing cognitive overload is not about doing less; it’s about clearing the clutter to allow real learning to resume.

Here are some ways AI tools can help prevent or reduce cognitive overload for students through effective management of each cognitive load:

Intrinsic load

We can manage this by prompting AI to turn long readings into bullet points, outlines, or flowcharts. We can also request different levels of explanations: beginner, intermediate, or advanced. 

Extraneous load

Dense notes and unfamiliar jargon can be rewritten in simpler terms and clearer language, adapted to our level of understanding, and remove confusion, and we can also use AI as a checking tool, identifying common misconceptions and gaps in our knowledge. 

Germane load

AI can optimize this by showing how ideas within the topic relate to one another. Remember that the brain thrives on patterns, so creating interconnections between core ideas will help improve uptake and build understanding.

Let me walk you through an example of how AI could help me with a topic we covered in History class, the French Revolution.

Before class

I prompt AI to “Explain the French Revolution in very simple terms. No dates for now. Just the main idea”. I read through the explanation, and later, during class, I hear familiar terms like inequality, taxes, and the bourgeoisie, and my brain undergoes recall, strengthening the connection to that memory.

Revision

I prompt AI to “Group causes of the French Revolution into 3-4 clusters,” and it organizes them into social, economic, and political. My brain now has headings for each cluster, and the data is grouped accordingly.

Concept simplification

I copied a section from an assigned textbook that has a lot of jargon and unfamiliar words. I prompt AI to “Rewrite this section to a Year 10 level of understanding. Keep the meaning but make it simpler to read. Define terms that I would be unfamiliar with”. I am now able to understand this section without having to go back and forth between different resources or having prior knowledge of the terms used.

Essay writing

I prompt AI to “Give me a simple 3-part outline for an essay on the causes of the French Revolution”. When I am happy with the structure, I begin to write my essay. When I need references or am unsure whether my statements are factual, I prompt it to “Give me references for these sentences or tell me if it is inaccurate”, and I can check to ensure my statements are correct.

That’s but one example of what AI could help me do. There's a plethora of other features that I have yet to explore. However, I must always remind myself that AI can make mistakes. Instead of requesting summaries, I must always refer to the original material, for fear that important facts are omitted or taken out of context. We must maintain balance, because reducing cognitive load absolutely does not mean eliminating effort, and the educator’s role is paramount here. I also want to stress that we must never, ever, prompt AI to write for us. Writing, whether it be creative or technical, is a basic human skill that we must not lose by deferring it to AI. The goal is not to make it do all the thinking for me; it’s to free up my mind so I can think better! When used responsibly, generative AI can help remove some of that extraneous load, helping students focus on what really matters: understanding.