Instructional Design in the Metaverse Part 8
What fights won’t we fight? What is our secret weapon? And what lies ahead? It’s the final part of this series.

What fights won’t we fight? What is our secret weapon? And what lies ahead? It’s the final part of this series.
Welcome to Part 6! Are you alive? By my calculation, when this goes live, 3 intrepid souls have read all of Parts 1-5 before this. (Insert laughter with tears). Indeed, you may have found this in isolation of the other parts! That’s OK, I’m cool with modularization. Feel free to “go around the Horn” at some other point in the future and read Parts 1-5 later.
Oh! And, for those 3 travelers AND everyone else, I am making an explainer video of all of this content. But it comes with 2 caveats:
No references or quotes. Just ideas.
Because it moves with a preset piece of music, each idea will have a limited amount of screen time: 2.4 seconds, to be precise.
Finally, I’ll probably write a full BTS (Behind The Scenes) on this article series on my blog. For those of you that love BTS content, that one will be for you. Translation: these articles were NOT written to be sound-bite worthy. What I write in the BTS will be.
This is basically the second of two parts that were originally together: Part 5 is what is the SAME about designing between 2D and 3D and this is what is different.
Long story short?
Here is where the fun begins.
A learner could learn from a book how to enter a store and buy something. A learner could also learn from entering a real store and buying something. Both are ways to complete the learning, but the designs– that is, how to structure the learning from start to finish, will be different. The book is analogous to direct instruction. There are times when direct instruction will be the better approach. The real store is analogous to experiential learning. There are times when experiential learning will be the better approach. The approaches are different; there is no inherently better approach for all situations.
These elements in this section are not meant to imply that they exclusively belong to XR media. That is, many other forms of media contain these same elements. These items are listed here because they are often found within and indeed are combined in design solutions in XR.
Clark and Mayer observed that humans are sense makers and attempt to derive meaning from life experiences (2016). Learners engage in making meaningful connections when words and pictures align during experiences. Meaning is also deeply embedded in the storytelling approach, where it is often the journey that the protagonist goes through that remains memorable long after a story has ended. D. Clark argued, “learning experiences are exactly that, experiences designed to change us, specifically our long term memories” (2022, p. 7). Further, D. Clark advocated for a balanced use of storytelling, explaining that it can bring life to dry information, but should not be overused and wander into a “Disneyfication of learning as entertainment” (2022, p. 7). Lastly, D. Clark argued that stories for learning should be designed as “always beginnings, never ends-in-themselves” if the learning is to be applicable beyond the experience, into the “long tail of practice, transfer, and performance” (2022, p. 7).
Points for poetry, D. Clark!
“always beginnings, never ends-in-themselves”
Indeed, the storytelling approach in learning pulls the learner through the experience. To use storytelling, the learner should experience a flow through their experience, a beginning and middle of the story. The end could happen in XR or more substantially outside of XR into desired application. The learning experience should be planned and not haphazard. Learners should be guided on a planned route. XR storytelling can be first person or group experiences. Regardless, each learner is a protagonist; their decisions determine what they will experience. Recalling the constructivist learning theory foundation, what the learners experience becomes the learning experience that is being designed for. If learners are exposed to situations where they actively construct their knowledge, then the reality that the learners construct was constructed by them, not constructed by the media or by others. Further, learners do not arrive as empty vessels to be passively filled with information if they are the protagonists of their own learning event. Learners add, sort, emphasize, or suppress new experiences when compared to old experiences. Subsequently, a learner already experienced in real life (non-XR) is bringing those experiences into XR with them. In summary, learners arrive already ready to experience a story. Thus, narrative plot or a story arc is a good approach to XR instructional design.
Plot, narrative, or narrative plot are all descriptions of phases within storytelling. There are slight variances in names but the phases generally focus on the user’s (or in our case, the learner’s) experience (Lichaw, 2016).
These phases describe what is happening to the protagonist. In the case of XR, the learner is the star and they should be brought through these phases in an effective design plan. Table 1 compares a storytelling arc with the Pixar story arc, a story arc example of Cinderella, an XR story arc, and an XR narrative plot example.
Pixar story arc from Khan Academy. (2017). Pixar in a box: Introduction to storytelling [Video]. YouTube. https://youtu.be/1rMnzNZkIX0 Cinderella story arc derived from Kurt Vonnegut, as documented by Derek Sivers. (2009, September 1). https://sive.rs/drama
Introduction. The who, what, where, why, when of the experience is explained. The scene opens. This starts before the digital experience begins and lasts 30 seconds to a few minutes into the experience, depending on how much needs to be explained. This is the beginning of the exposition.
Set the scene. Provide guidance on the affordances within the experience, how to communicate, walk, navigate, where is help (e.g. where is a digital companion). The learner is invited to move, change appearance, and communicate.
Dilemma. Introduce the conflict or the scenario that the learner will participate in. The learner is presented with a challenge or problem. This is the inciting incident and rising action phases. This can be a great time to guide and practice small solutions to small problems.
Crisis. The learner must act and initiate some sort of change. It is action-oriented, and the learner is on center stage.
Change or Denouement. The results of the change have an impact on consequences or the environment. Said another way, the change ripples through the experience to change it for the learner. The results are non-trivial and not haphazard.
Resolution or End. The mission is complete, and the world has changed around the learner. The learner is living out the consequences of their decision.
Some research has shown that most of the instructional emphasis does not need to be within the XR experience itself. Dede (2021), when reflecting on what he now believes after over five decades of immersive learning research, said:
“I used to believe that if you had resources, you should spend 95% of the resources on the immersive experience and then you just do a little thinking about what kind of induction you use before people go into immersion and what kind of post experience debriefing you do. I’ve come to believe now that the induction and debriefing is where the learning takes place predominantly, and so designing those is very important.”
This indicates the importance of the on-boarding and the follow up experiences. The story of an experience begins before something is activated and ends long after.
The main point of keeping a narrative plot mindset in ID XR design is to keep the learner at the center of the experience. Every step of the narrative plot approach focuses on what the protagonist- that is, the learner- experiences: dilemmas, crisis, change, etc. This approach, then, keeps the ID focused on the learner’s experience, not the technology. For example, let’s say a platform can recreate the school environment down to the desks and chairs. An ID might reason, ‘This a great place to hold a class! I can assign classes to virtual rooms and the instructor can use web-sharing boards.’
Don’t try this in VR
That approach puts the technology first and does not consider the learner. It also recreates the problems of regular in-person classrooms and throws in a few more virtual problems as well (i.e., poor internet connections might have avatars distractedly appearing and disappearing). Rather, a learner-centric approach might ask “What is the main experience or emotion that the instructor wants the learners to have in this lesson?” As Mayer stated, “How can we adapt multimedia technology to aid human cognition?” (2020, p. 15). This might cause the ID to look at the entire XR event differently and not recommend a virtual classroom. There is more on emotion in design in Section 5.2.
Credit: https://fbvisualisation.blogspot.com/2014/04/narrative-charts-tell-tale.html
For the ID, the added visual depth and sound possibilities beyond 2D must be designed. However, more to design means more risk. With XR, the added ability to put information anywhere has more risk of overwhelming the learner than helping the learner. Indeed, D. Clark (2022) agrees that Mayer’s Principles lean towards less is more.
Alger (2015) noted these basic principles for visual range called the Comfortable Content Zone: 77 degrees of viewing range side to side and a range of 0.5 to 20 meters in depth. There are Periphery Zones to the sides and above, but the learner should be only prompted to use those.
Credit: Alger, 2015
This reflects real life. If one was working at a workstation, critical information would be within easy viewing and reach. Other information could be available in what Alger calls the Curiosity Zone – behind and below the learner, but learners should be prompted, as in real life, by sound, light, or foreknowledge, to engage with that non-obvious space (2015).
Alger (2015) further proposes that the visual hierarchy matches the importance of information. To find information in 3D, we look at the center ahead first, then left and right, then below, then above, then finally at our own bodies. Everything above eye level is for things beyond the learner’s control like weather, time, or authority notifications. Everything at or below eye level is within the learner’s control.
These user interface principles skew towards conservatism in detail; less is better. IDs should design minimal spaces, with prompts, and within easy arm reach. IDs can create storyboards with isomorphic qualities that both curve around the learner and contain planning space for the foreground, mid-ground, and background visuals.
Immersive sound is a rising field within XR design. Poor sound can ruin an XR experience. Experiences can have spatial sound where the loudness drops off over virtual distance or flat sound where the loudness is the same throughout the entire space. As much as possible, it is good accessible practice that all senses should have learner controls: brightness, sound, movement, and intensity.
Many platforms and experiences already contain volume controls for separate parts of the experience (e.g., voice chat, environment, or notifications all have separate volume controls). Learners should be trained on these controls at on-boarding.
Generally, for information that is necessary for the learning event:
If the information is in speech, provide text equivalents (e.g., transcript).
If the information is in sound (environmental sounds or notifications), it should have equivalent visual and/or text indicators.
If the information is in text only, provide sound equivalents.
Interactions in XR could be reaching, grabbing, and moving. Good experimental research exists from organizations like IEEE VR or ACM IUI on 3D user interface recommendations. Alger’s (2015) design advice showed a seated avatar seated work will be more comfortable than standing in XR.
Credit: Alger, 2015
Almost every new XR user has walked their avatar into a wall. It happens.
You stay in that corner until you can act like a good avatar, Peter!
Given that the wall isn’t real, mistakes like this are forgiven quickly. IDs can ask learners to move.
(And Peter knew I took his picture at this moment above.)
Movement in XR is an advantage of the metaverse. While research does not indicate that movement causes learning, it can greatly assist in the storytelling aspect of bringing a learner through an experience by requesting that the avatar move through the story in virtual space time.
Movement is relative in this media. Frame of reference can be manipulated. The avatar can move, or the avatar can stay in one place and the scenes can move or change around them. There are a LOT of choices for movement in XR. From gaming research, it looks like most of the possibilities are aiming to reduce vestibular mismatch.
In this area, movement-based engagement can be an area of exploration in designs. For example, asking learners to move to one side of the room or another is an interesting way to run a poll. XR movement often includes dancing and flying. Future research should explore the use of controllers or hand detection for learning.
Many social XR platforms have incorporated emojis and they can be used for their apparent reasons: love, happy, sad, clapping, or raised hand. Within designs, learners can use them differently, that is for feedback, poll indicators, or silent ‘I need help’ indicators. Learners have been known to redefine emojis to mean whatever makes sense to them during a learning event.
Part 7 will cover designing and building XR experiences for learning. See you there!
Photo by Dan DeAlmeida on Unsplash
I’ve received some questions on my video and transcript posted here: https://heatheredodds.blogspot.com/2022/09/xr-will-not-cause-lasting-improvements.html
So I’ll add some clarifications:
1. There are weak points in my argument:
A. I argue that the learner is the still as-yet undiscovered cause of the flat lining of learning objective results media to media. I have NO data to back that up. That is a supposition by me. I suspect the data will have to come from brain studies.
B. My argument that learners in previous generations were NOT dumb is a bit of low…err…high?…blow. Certainly, there were dumb learners in the past.
However, I do not buy the modernist argument that when technology gets “better”, learning gets better. Nope. No. As I mentioned in the video, humans appear to have a learning speed limit. Said another way, the neural pathways of learning in a human brain are set. (Yup, I’m referring to brain-based learning theory here. You might know it as neuroscience.) Short of something like “Lawnmower Man” or a “Flowers for Algernon” royal technology/drug-induced fuck up, I don’t see humans getting smarter.
2. Let me be clear on my argument about results flat-lining and there being no “lasting improvement”. The “lasting improvement” that I’m mentioning are ONLY learning objectives. So said another way, if there was an exam covering X taught with media Y where students score Z right now….in 10 to 30 years, learners will still score Z even if XR is the media. I’m sticking to apples to apples comparisons. I’m NOT talking about other things like XR affordances, which would introduce apples to kiwi to melon comparisons….which are not comparisons and are not fair.
So I’m not talking about XR doing things like increasing access to resources due to manipulations of time, space, geography, physics, etc. Those things are affordances, the characteristics that belong or sort-of stick to a media form.
The conversation about affordances is fascinating and I’d love to have it! As a designer, knowing the positives and negatives about each media is my specialty! (See my XR platforms writing.) However, I’m also bound as designer to not force any decision about the “best” media upon a client. The clients decides what they will select, what they will pay for, what they will invest in long-term and thus the client accepts both the positive and negative consequences of their decision, their “opportunity cost”. So by default, I almost never like to say this is “the best” when it comes to an XR platform.
3. Timeline = I used smartphones as an example in the video but I’m really brief about it. But it is in somewhat recent memory that smartphones went from a new technology to everyone having one. How long did that take? Hmm… lemme check:
First arguable smartphone: 1992.
2022: as shown in the video there are enough smartphones in the US for every adult to have one. Translation = the US market is saturated. Smartphones are ubiquitous.
1992 to 2022. So that took 30 years.
I’m fine with adding in Moore’s Law here. So the adoption of XR until the point of it being ubiquitous and saturated– how long will that take?
Hmm… I’m guessing but I’m more comfortable saying closer the 10 years from 2022 than 5 years. That puts my guess at 2032.
Now now, you pro-XR folks out there! I heard your cry! 10 years!! Don’t be sad. Remember what is between HERE and THERE: a great big increase, an expansion, a bubble, GROWTH. It will be a good 10 years. (Imagine what the first 10 years was like for smartphone manufacturers Nokia and Apple, whoohoo!)
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.