Cogitate and Percolate

This post accompanies my XR will not cause lasting improvement in education video and contains a few more details. I wrote this blog post first, then made and remade the video and I’ve come back to finish the blog post with the final script and my notes.

XR will not cause lasting improvement in education.

That’s an interesting statement to start a video

when I’m known for being pro-XR.

That’s right, I am pro-XR in education.

But I have expectations that learners will not perform higher.

With respect: Rephrased
from the Cambridge Handbook of Multimedia, (2005, pp. 7-9) and Cuban’s
1986 book: Teachers and machines: The classroom use of technology since
1920 (pp. 9-26) and Mayer, R. (2020). Multimedia Learning (3rd ed.).
Cambridge: Cambridge University Press. doi:10.1017/9781316941355.

Generally, educators are on the lookout for what causes learning and we want to encourage more of it. We realize that content is hard to learn and we want as many learners as possible to successfully learn it. This is given– a belief in the general positive well-being of the learning process, the educators and not least, the learners. It IS important to say that because somewhere along the way, one of the counter arguments against that fact that we don’t find learning gains is “the technology was poorly implemented” or “the leaders don’t care for change” and I wanted to cut both of those excuses off right at the beginning. Nope! Educators IN GENERAL are implementing the technology well and leadership IN GENERAL is pro-change.

Next we need to visit the scientific experimental model as it is the basis for the experimental models used in education. That means that we observe an effect, some data, some phenomena, and we ask “What caused this?”

Remember, we are looking for cause and effect.

This is the scientific experimental model.

Controlled variables – things hold them constant so that they don’t change.

Independent variable – what we purposely change to test cause and effect.

Dependent variable – what we measure as the result.

There are other models to gain information from; naturalistic…meaning anything outside of a lab

Or cultural ways of knowing. This could be indigenous or religious knowledge.

Regardless, the Experimental Model is one of our strongest logic systems and it comes through more times than not at finding cause and effect.

We can isolate variables down to determining the cause (a deductive reasoning approach, a la Sherlock Holmes), or we can simply start with as few variables as possible to find the cause.

This is the same experimental model as it appears in educational research.

We have our learners, we add a technology, and we measure the results.

And it’s not like we just started this research.

For the purposes of this video, I’ll go back just over 100 years and use the word technology to mean anything powered by electricity.

For example, Radio

And here are the results: no lasting improvement.

Projectors – no lasting improvement

Television – no lasting improvement

Computers – no lasting improvement

Internet – no lasting improvement

and in the future, cloud-based learning by robots or whatever.

But in all seriousness, this video is about XR, extended reality, cross-reality, mixed reality or whatever you want to call it.

Now RIGHT HERE, some will become upset. They say:

But this is different!

This is learning in 3D!

No, you don’t understand, this is a computer stuck to your face!

We need to implement it correctly and THEN we’ll see the results!

I have a study right here that shows it better when putting VR up against a textbook or a human teacher!

OK for that last one, I toss that right out as non-comparable methods, but that’s a topic for another day.

So let’s look at the results, shall we?

No improvement.

Now for those that are hearing me right now having a really hard time taking this in, I understand that this is not fitting into your schema. What you are feeling is bias. You want the results to be a certain way, and even when the results are not turning out the way you want them to, you want to reject all of the previous results as not predicting what will happen next. Remember that bias, in research, is a bad thing. We don’t want it. So I need to ask you to check your bias and leave it behind.

I’ll give you an example that should be in the recent memory of XR enthusiasts. I’ll use 2022 words to explain a 2022 real world example.

How many studies do we hear of right now that show a spectacular increase in learning with a smartphone (mobile)?

How many times do we hear from learners that they love learning on their smartphone? “Oh it’s so cool!” “Oh it’s the best!” Oh I love that I can learn from a computer in my pocket! Oh, I love that I can learn on this tiny screen!”
~ Oh I love that I’m
being forced to do my workplace learning on my own device (that I paid
for, pay for the internet subscription for, and pay the insurance on, to
say nothing of being tracked by my workplace VIA my own phone!

What’s that?

No one says this?

You’re right.

Why?

Said another way, smartphones are ubiquitous. Actually if you listen closely, there is a STRONG amount of conversation about how learning on the smartphone is boring, forced, poorly designed and/or at least equivalent to learning in the classroom—thanks to COVID and 2020.

So learning on a smartphone is ubiquitous. The learning results have flat-lined.

I’ve made my case that history predicts that XR will also flat-line after it has become ubiquitous.

But….why?

We still didn’t answer that.

I have 2 reasons. One I’ll share, the other, not yet.

Let’s go back and look at that experiment model again.

We said that every technological improvement has proved to produce zero overall learning gains. Learners are simply NOT DOING BETTER.

We can slip in and out all of these technologies and we keep getting goose egg results, nothing. But…look closely at the model. What other variables are there?

We said that technology was a variable and our proposed independent variable– we are purposely changing it).

The results are the dependent variable – they are the output, the effect, or the result of what we are changing and frustratingly, they are NOT CHANGING.

So what else is there?

Look. One more variable is present…

The learners!

Matching my technology examples: 1920s learners

1940s learners

1960s learners

1980s learners

Learners from the year 2000

2010 learners

I mean, everyone knows that 1920s learners were dumb, right? I mean…

Oh, you mean the time when Einstein discovered his E = mc(squared) hypothesis? We were dumb?

1940s? The start of the discovery of the polio vaccine? Saving thousands if not millions of future lives?

We were dumb then?

1960s? Early computers being built? Remember…going to the moon?

1980s? Well no comment from me, I’m from there.

Many smart well-respected people that I acknowledge, say it is a mistake to assume that older generations were not, at least, as smart as us, and in some ways, we can find evidence that they excelled (for example, try learning entirely by oral tradition, no shared writing, READ: no books).

So we can’t say that those learners, educators, and leaders were dumb. They were trying to implement the latest, greatest technology in the best way and certainly there’s been plenty of time to try MANY iterations of the technology. For example, radio for adult learning, radio for kids,

radio for cows. Heh heh, just kidding about the cows, let’s leave them out of this.

~I included cows because there is some research already about there about putting VR headsets on cows and I’m totally befuddled by that. I’m like “Why? Just stop it.”

But the humans are there.

The humans are the same.

I’ll repeat that for emphasis.

The humans are the same.

So we have experiment after experiment; we change out the technology thinking THAT will cause changes in the learning. But the results come out the same.

Could it be the OTHER variable– the humans – causing the non-increase in learning?

I posit, yes it is.

Brain-based learning science (OK, use the word neuroscience if that makes you more comfortable) gives this as it’s prediction.

The humans are the cause of why the learning results are always turning out the same, flat-lining, goose egg in improvements. Humans seem to have a “speed limit” when it comes to learning. We all have it. We can’t break past it. (Why? that’s my second shhhhhhh reason.)

So that’s why I’m so confident that XR will not cause lasting improvements in education.

As long as we are using humans as our test subjects, the results will peg even.

To be clear, I’m all for the improvements in AFFORDANCES that VR will bring; for example, safely learning inside a VR volcano, or added safety information with XR glasses. But those will not cause an overall lasting improvement because eventually everyone should be able to learn inside of a VR volcano or with XR glasses at work. Eventually, VR will be ubiquitous and not…

not the domain of the rich kids.