three types of cognitive load theory

what i've learned (so far) about cognitive load theory

If you're in the data visualization industry, you may have heard about cognitive load. Cognitive Load (CL) is the amount of work that your working (short-term) memory has to do.  What I learned is that the Cognitive Load Theory (CLT) originated as a teaching theory developed by John Sweller.

My knowledge of CLT was basically limited to the definition. But after reading a few articles, my mind was blown at how much I didn't know and how much more there is to know.

For example, I learned that there are three (3) types of cognitive load.  

Intrinsic (how complex the task is)

Extraneous (what we are typically concerned with...not letting the extra stuff increase the load)

Germane (linking new info to info in our long-term memory)

This got me thinking about these concepts in terms of data and data visualization. 

Intrinsic CL is how complex the domain knowledge or the information underlying the data point is. For example, for someone who is learning about how past due loans relate to bank failures,  the concept of solvency ratio might be understood on the surface.  But, the data has business logic built in it (like, loans 30 days past due don't have as much risk of causing the bank to lose money versus a loan that is 90 days past due) and all of that (and more) is baked into one ratio.  

And if all of that made your head spin, then I think that's a good example of intrinsic cognitive load.  If you're in lending in banking, then past due loans and solvency might not be that big of a load, but if you're not familiar, then your brain is like: whooaaaaa, you're making me work.  

Extraneous CL is not letting the noise increase the load.  This might be the colors we use, the type of charts, the fonts in data visualization.  I think this is might be the easiest for us in data vis to cure.  And of course, my accessibility loving heart also likes this because being intentional with what we use in data vis helps create more accessible visualizations. From a data point perspective, I think it might be the extra information behind the data (but this is something I would need to further understand).  

Germane CL is linking the new information with known info. From a data vis perspective, I think of it like learning about a spike in the trend with what I know what typically happens when spikes occur.  Or maybe it's tying what you know about past due loans to how it affects solvency. 

What struck me was that while I learned something new about the three types of cognitive load and those by itself can be a lot and can be addressed individually, is there a cumulative or exponential effect of two or three of these types of cognitive load?  That's something else to learn.

To keep in the spirit of trying to not overload your short-term working memory, I'll finish what I learned about cognitive load.  🤓

Reference:
Education Corner. Cognitive Load Theory--The Definitive Guide. Loveless, Becton. https://www.educationcorner.com/cognitive-load-theory/