The Attention Span Myth: Ronald Yaros on What’s Really Failing Students

In this conversation, Mason Pashia sits down with Dr. Ronald Yaros, Associate Professor at the University of Maryland’s Philip Merrill College of Journalism and Director of the Digital Engagement Lab, to examine one of the most misdiagnosed problems in modern education: the so-called attention span crisis. Drawing on four decades of experience spanning Emmy-award-winning broadcast journalism and rigorous cognitive science research, Dr. Yaros challenges the assumption that students simply cannot focus, arguing instead that the real failure is a failure of content architecture. Together, Mason and Ronald explore the neuroscience of continuous partial attention, the concept of the digital diet, and why the medium we choose to deliver information shapes what students actually retain.

The conversation moves from theory into practice as Dr. Yaros introduces the Smart Story Suite, an adaptive AI tool developed through the Digital Engagement Lab that restructures existing long-form content into selectable, navigable learning paths without generating or altering the underlying information. Grounded in the Digital Engagement Model and validated through studies involving more than three thousand diverse participants, the tool demonstrated significant gains in perceived interest, interactivity, and credibility compared to traditional linear text. Dr. Yaros also introduces the SPICE framework, which describes content that is Scannable, Personalized, Interactive, Curiosity-raising, and Emotion-generating, offering educators a practical lens for redesigning how learning experiences are structured. Whether you lead a classroom, a school, or a district, this episode reframes the engagement conversation from a student problem to a systemic design opportunity.

Transcript

How we spend our days is, of course, how we spend our lives.” This quote is often attributed to Annie Dillard and is a continuation of a lineage of thinkers. The Stoic Epictetus says, “You become what you pay attention to.” Attention is a muscle.

It’s honed and trained, and it won’t be a surprise to any of our listeners that this often feels like a losing battle. In the words of Dr. Graham Burnett, founder of the Strother School of Radical Attention, “Your minds are being fracked.” So what, then, is the role of K-12 education in this fight for our own attention?

What is the role of education at all in this fight? And beyond focus, what can and should we be learning about the vast wells of attentional research that’s been happening over the last few decades? Today, I’m really excited to have this conversation, leaning in on attention and engagement and how we can learn from the many tools that have been created over the last few years.

So I’m joined by Dr. Ronald Yaros, an associate professor at the University of Maryland’s Philip Merrill College of Journalism, and also the director of the Digital Engagement Lab. He’s the author of “The Digital Engagement Model” and has a new tool that he’s here to talk about and show us a little bit, called the Smart Story Suite.

So, Ronald, thank you so much for joining me today.

Ronald: Really appreciate the invite.

Mason: This is one of my favorite topics. I’ve broached it in a number of ways, in many different conversations, so I’m really excited to just dig in on it. But I want to start off with a hard question, and one I don’t think we spend enough time with.

So, with time being a famously scarce human resource, do humans actually have a limited attentional capacity? Is it really a zero-sum game, where if you spend attention on something, you can’t spend it on something else, either in the scope of a day or in the scope of a moment?

Ronald: Excellent question. And yes, we do have limitations. Anyone who tries to multitask with one hundred percent efficiency is obviously going to have some problems along the line. You cannot, for instance, drive and text at the same time. You don’t want to do that, because your mind is focused on only one thing at a time. Lang at Indiana University says we have a cognitive capacity of resources, and when we direct those resources to something, that’s it — we cannot really do a lot more. Linda Stone, a former IBM employee and now a researcher, has done a lot of work I use. Instead of multitasking, which is obviously two things at one time that you do to be productive, she says — and I agree — that with devices, we don’t multitask. We have continuous partial attention. That’s a really cool title to describe what we’re all seeing day in and day out, particularly with younger people in our classrooms who are always checking their phones at every idle moment — and that idle moment might be a boring slide. So continuous partial attention is what I like to use.

Mason: I think that’s really smart. There’s been some coverage of the ways that folks at Netflix have talked about how, when they make shows, they should have more oral exposition, because people are likely on their phones. Or, if you’re watching certain shows, it’s like: how can we pace it so that it’s a multi-screen experience, and someone can be scrolling while watching?

So I think that continuous attention is really interesting. You addressed scarcity, or this inability to multitask in a moment. But I’m curious: is there a well, or a reserve, of attention that we have that resets with rest? I’ve heard some things about how, if you start your day scrolling, or listening to a lot of podcasts — except for this one, you should definitely listen to this one — you actually have a harder time learning things later in the day.

You used a lot of that focus, a lot of that intake, early, and then it gets full. I’m curious if you know any research about that, or if I’m just spitballing.

Ronald: The only thing I can think of is that, obviously, when you wake up you’re very alert, and as the day goes on it probably becomes a little more difficult for you to focus. So anyone who teaches a late-afternoon course might—

Mason: Yeah, right.

Ronald: —see that fatigue. That’s kind of what I think you’re talking about. But to be honest with you, I haven’t heard too much about that specifically.

Mason: Okay, cool. Well, listeners, research that yourselves — don’t just believe me. But if that’s an experience you’ve had, maybe it’s also validated.

Ronald: Yes.

Mason: So you argue specifically, I think, that this attention-span crisis we’ve gestured at is commonly misunderstood. We often fault the young person for being distracted, or for any other reason.

But tell me why it’s misunderstood. What are we getting wrong?

Ronald: You’ll hear a lot of teachers say we have short attention spans. Okay, so why do my students spend hours on TikTok and Instagram? Why do they watch video for hours on YouTube? Why do they read — some still do read books — and attend movies, of course? The attention isn’t short in those cases.

So what’s the difference? I’d say it’s structure, it’s content, it’s how we’re presenting content. Since the iPhone came out in 2007, we’re now constantly bombarded with different things to select, and so it looks like a short attention span. But what keeps our attention is good content. If you’re scrolling on TikTok and you definitely want to know what’s next, and that curiosity is there, plus there’s movement because of short videos, it keeps you engaged for hours. So there’s no shortage of attention there.

Mason: Is there actually a hierarchy in the quality of delivery? Do different content types matter — is a book better than a TikTok? Is there something to the idea that you’re still spending attention in both instances, and maybe you have deep attention in both instances, but it’s different in a meaningful way?

Or is it actually just that different mediums suit different content, and that’s where it stops?

Ronald: The digital engagement model has a user side and a content side, which we can talk about later, but right now you’re referring to the user side — I call it the digital diet. The four things everyone brings to this podcast are your demographics, your interests, and your environment — because if you’re on a bus right now, or about to go into a meeting, your environment isn’t equivalent to being in the library.

Mason: Right.

Ronald: The “T” in “diet” is time. Time is absolutely critical right now when it comes to trying to satisfy the needs of people across those variables.

Mason: So how would I use the digital diet in my daily life? Is it about becoming aware of these factors and knowing that I can manipulate them, or is this really informing you as a researcher, in terms of how content might sit differently with different individuals?

Ronald: We’ve all been taught to have a logical, linear presentation of text, video, or a lecture. It’s really important now to recognize that you have to give any person who engages options for what they want to select and learn — we call it progressive disclosure, which I’ll show you in a little bit. Students are actually clicking on what they want to read out of a long-form text.

So that really means everything could be long-form, based on the environment and the time — the digital diet of that student. They could also engage and learn something even short-form. So, realistically, we can’t expect everyone to read the one-size-fits-all page of text. It’s really about structuring our content so it can be consumed both long-form and short-form.

And some of those students who don’t have a lot of attention or time can come back later, because they have options for new material and can select what they’re most interested in, or what’s going to be on the next exam.

Mason: You conducted some research on this, right? With about 1,500 different users. Beyond seeing what they clicked to move forward, what else did you learn from that process — either about intention, the actual creation of content, or about attention in terms of how folks engage with it?

Ronald: Our digital engagement model is now supported by what we call adaptive AI. It doesn’t generate any new information, nor does it just summarize it. Adaptive means it divides a long-form text into choosable sections, combined with bullet points, visuals, and what I call explanatory subheads — meaning that in the middle of a text, if you see something in bold, and it’s a declarative sentence, not a title, but an actual sentence that’s really important, you’ll scan it and won’t say to yourself, “This is just a page of text, I’m out of here.” You’ll say, “Oh, that’s interesting — I just learned something by reading that subhead.” Little things like that are what we tested. We did it three different times, actually, so we’ve had well over three thousand participants nationwide in a diverse audience.

That means ages eighteen to eighty-one — it wasn’t just students. The results were that, compared to the same content presented as a linear page of text, there were significant increases in perceived interest, interactivity, and even credibility of that information. In one case, it’s really interesting: they spent more time on the linear text, but they learned more from the Smart Story Suite, which actually goes against what all the audience-analytics people say — that the more time you spend on something, the more you’re going to learn. Maybe it’s, in part, making it easier for students to navigate.

Mason: That’s really interesting. I don’t know if this is a question so much as a parallel observation I’m making, just based on the fact that The Odyssey movie just came out — the big blockbuster. In some ways, that’s an adaptive version of a poem or story that’s been told for 3,000 years, with many iterations along the way.

I was listening to a conversation with someone talking about how The Odyssey was told in the old days. Was it recited? They said it’s actually kind of like an album — someone would say, “I love the Cyclops part, will you tell it to me?” There’s this really interesting thing where we accordion content over time: we do a comprehensive three-hour film, or a comprehensive 300-page, 1,000-line poem, and then we also chunk that into little bits, so it’s either more transferable over time, more easily learned, or just more resonant.

Sometimes you don’t want the fatigue of going into the 100th, or the 18th, book of The Odyssey. You want to hear your favorite part with the receptivity and freshness you bring to the situation. So I’m curious — does that resonate with you at all?

And I think there’s a sub-question in there around intention, because every time somebody reinterprets that story, there’s a new layer of meaning — this new thing happening. I’m curious if that also happens with adaptive AI, or if it’s actually able to be pretty objective in how it parses information.

Ronald: You’re asking excellent questions, and this is where we get to content specifically. In terms of combining the digital diet with content that keeps your attention, I call it SPICE content. It’s Scannable, Personalized, Interactive, raises Curiosity, and, when possible, generates Emotion. That basically describes TikTok, but it also applies to a lot of what you’re describing in the movie. Any good movie will build curiosity with the story. But emotion is also really big — being afraid because something is scary, or something being funny or sad, is a very powerful engagement tool.

Mason: I think you sit in this interesting space — between journalism, digital engagement, and, loosely, neuroscience or the science of learning, among other areas. Tell me if this question should come later, after we spend some time with the tool, but at a purely philosophical level, how should educators or education leaders be thinking about this in terms of changing their own practice?

Does it mean the resources they’re curating need to look different, or is this actually about delivery in the classroom — how you’re speaking to folks? Can it embed at every level of what you’re doing, or is it more in a curatorial sense?

Ronald: That’s a good question. First of all, the model isn’t a silver bullet — I’m not saying everyone who applies it is going to get one hundred percent engagement from students all the time. Second, the way a teacher teaches isn’t the way I teach, so I’ll just explain what I do. It’s an online course with seventy students.

It’s a gen-ed course, so I’ve got people not from journalism, but from across campus. In thinking about SPICE and diet with limited time, my Zooms never exceed thirty minutes, even though the class period is one hour. I always have assignments due on a Monday — we meet on Mondays, and I call it the “Monday Mission.” They have to complete something by the end of that class period. That’s number one. Number two: to make sure they can consume information whenever they want, the second meeting, on Wednesday, is strictly video, and I don’t produce one long video.

I produce three short videos so they can watch whenever they want, and that’s completed with a “Wednesday Wrap-Up” assignment. In the meantime, both on Monday and in the Wednesday recording, there are a lot of assignments that ask students to contribute their ideas, thoughts, and reactions. Video is used during my lecture — it’s not just me on Wednesday in a recording, but it’s personalized, because we all know that one of the biggest complaints about online learning is that it isn’t very personable; it doesn’t feel like a classroom. That’s just one thing I do. And finally, I use a tool where, at least fifteen times during my brief Zoom session, students have to use their phones to respond. So even though I’m hoping they’re not on TikTok at that moment, I’m using a lot of interactivity, not just showing slides.

Mason: That’s great — I really appreciate that example, to ground some of this in practice. I don’t know if you’ve been following the Alpha School conversation, but there’s a new learning model called Alpha School that’s taking the K-12 world by storm. It’s a two-hour-a-day learning model that’s hyper-AI-concentrated, closely modeled on the algorithms of TikTok — it’s watching you on camera, and if you look away, it changes the content.

If you do a certain thing, it changes the content. So it’s sort of a radical engagement engine. I have some concerns with it, and a lot of people have questions — like, “Sure, if you have two hours, great, but what do you do with the other six?” That might be the most important learning part of the day.

How do you do real-world work that matters, and so on? One concern is that if something is so adaptive, so spoon-feeding you how you learn, it reduces some of the cognitive friction you actually face most of the time in the real world. Most of the time when you’re learning, you’re not in your ideal environment.

You’re in a boarding terminal at the airport, people are calling out names, and you’re trying to read a white paper — not saying that’s my experience, but I am curious: can you become too adaptive with these technologies? How do you think about that when designing tools or advising on this?

Ronald: I think that’s one of the biggest concerns educators have — that generative AI is going to provide everything students need.

Mason: Right.

Ronald: We use adaptive AI, which means it takes a particular piece of information and simply restructures it through the digital engagement model.

But when it becomes too adaptive, I agree with you — that’s not learning, and that’s not good. It’s interesting, because all my students immediately think of generative AI when I mention AI. When I say, “This tool is just going to provide short chunks of information for you to select — it’s not going to generate anything for you, or do your homework,” I think that’s maybe a nice middle ground, where AI can be efficient without doing the work — without adapting to them one hundred percent.

Mason: Yeah, I want to sit on this for just a little longer before we look at the tool. We’re at a really interesting time, where truth is kind of on the chopping block. There are a lot of different truths being held right now about what you teach in schools, and what books you read.

In some ways, we’ve lost the idea of a common text, as a country and as a world. There are a lot of ways we’re personalizing based on region and place, and it’s lovely — but we have less of a shared experience, and maybe that’s a challenge, or maybe it isn’t. I think a lot about poetry.

That’s something I care a lot about. When you translate a poem, you miss a lot, even doing the best job you possibly can. There’s a poem called, roughly translated, “Maybe Madness,” by Osip Mandelstam, a Russian poet. If you look at different translations — from Christian Wiman and from Czesław Miłosz — they’re radically different.

There’s not one word that’s the same between the two, and completely different meanings emerge. Even with The Odyssey movie, there are huge things that were left out that completely change who a character is. So when you’re creating an adaptive version of something — let’s say a text — how do you ensure the truth remains intact?

How are you not giving every student a different experience, such that there’s actually less common ground? Or am I just too far off, philosophizing in what-if land, by raising that question?

Ronald: No, it’s a good question, and I think it needs to be answered. I’m not sure we have all the answers yet, but I’ll tell you two things. One is that, again, adaptive AI doesn’t generate any new information —

Mason: Of course.

Ronald: — it just restructures it. So I think this tool is going to be a lot better than a generative AI tool that begins to interpret things, in many cases, the way it likes to interpret them. Secondly, in our testing, you’ll see that, in addition to the chunks of text being rearranged, it can also add fact-checking. We found that when the population exposed to our Smart Story Suite had that fact-checking button, for instant verification of information, across three measures we used that were reliable — because we definitely tested those beforehand — the perceived credibility and accuracy of that information went up, even though it was the same content as the linear version that others saw. So I think it’s a combination of things: maybe not only convincing people that it’s not generating any new information, but also providing instant fact-checking when possible, because we all tell our students they need to check and verify things.

Mason: Right, right. And at some point you get so far into the weeds that you’re like, “I don’t even really know what I’m verifying anymore.” What’s an opinion, and what’s just something from the source?

Ronald: Exactly.

Mason: Yeah, right, of course. Okay, I think I’m ready to see the tool. Give me a little demo of what this looks like.

Ronald: So our first stop is the higher-education funding report from the NEA, which does initially give us a nice summary, but then quickly moves into linear pages of text. Even if you add a bullet point — well, it’s nice to have a map there, so that’s interactivity, that’s good, and you can roll over a state to look at the funding for education there — even a page of bullet points is still a page of text. What we’re trying to do is show that, first of all, manually, if you look at the digital engagement model, you’d see that type of information presented not only with bullet points, but with each page having a main subhead in bold, along with the main text. It also lets you select your state, and adds the fact-checking as well. Okay, so now if I go back to the original story — but go to our tool, you can see it, right? Okay, good. So in this prototype — it’s just a prototype — it’ll take maybe thirty seconds, because what it’s doing, especially with all that content on the page, is verifying that nothing new is being generated. The adaptive AI is going to do several things. First, it’ll give us the headline; it’ll give us instant bullet points; it’ll give us manageable text. It’ll break the entire page into multiple sections, which will appear on the left-hand side with the red buttons you saw on the manual version. On the right side, it’ll give us a selection of photos or graphics we can bring up full-screen. It’ll also give us the percentage of the original information it used in generating the report. This is the analyzer — the AI tool that immediately divides the entire page into selectable sections, so, for instance, “legislative budget review” and “severely restricted states.” Whatever you click on gives you a chunk of information — especially useful if you have limited time and want to look at something very specific for the next quiz, or if you missed the notes on it. And then it’ll say, “Okay, eighty-seven percent of the original page” — which was really filled with a lot of media — “eighty-seven percent of that has been used.” That doesn’t mean it generated anything new; it means it condensed some sentences, rewrote some for grammar or clarity — AI is really efficient at that kind of writing — so it condensed some information, but it wasn’t generative AI. The “detailed view” lets me revert to the linear portion if that’s what I want. But even in the linear portion, we have the explanatory subheads for scanners, if you like that version.

But the summary view is where it’s at, because whether it’s a news story, a research paper, or a long-form report, you’re able to select what you want. Any of the images, of course, are full-screen, and they’re also embedded. So worst case, if I have limited time, I’ll read the bullets.

If I have more time, I’ll read the summary. And if I really want to study the long form, I get everything that was on the original page, available for selection. What do you think?

Mason: That’s great. I don’t know if you do much cooking, but I think every recipe site on the internet needs this tool — those are nightmares to navigate.

Ronald: Yes.

Mason: No, it’s super helpful. So, am I correct that all the text on this page is essentially the original webpage, just restructured with headings and chunked into these grabbable bits?

Like this FY23 budget outlook — has this not been rephrased? Or these state recovery proposals — is that from the original site?

Ronald: The text is 87% original, and the rest was dropped for whatever reason.

Mason: Right. Okay.

Ronald: And the only thing it generated was a summary of that particular section.

Mason: Okay, so the summary is—

Ronald: Yeah.

Mason: So, in some ways, this turns us into machines in how we’re reading content, in a way that’s super useful for understanding information. I love it.

Ronald: From a human-computer-interaction standpoint, this is your basic homepage when you go to a site.

Mason: Yeah.

Ronald: What it does now is take that individual page and make it a lot more consumable for different types of students. We’re also starting to test this in neurodiversity classrooms, to see whether it can be adapted and be more beneficial for students with ADHD or autism.

Mason: Hmm.

Ronald: — by presenting content in this way.

Mason: That’s great. I’m curious — full transparency, we’ve built a publication type on our website that aspired to a similar level of interactivity, where you could traverse different pages or sections. The benefit is it gives us granularity into what people are reading and where they go next, much more than a PDF, which typically just rots on a desktop and dies somewhere.

The challenge is we now have visibility that, if someone comes to the page, they typically don’t click through everything. So there’s a benefit to being able to choose what you read, but it changes your relationship to the piece — you can poke in and poke out for what you’re interested in, and you don’t read the whole thing.

I’m curious about your research — and again, we’re in a fully optional setting, where people just want to learn something, so they come to us. It’s not a class, it’s not those other settings where your goal is to understand the material. In your research, did you find that this interactivity led people to engage with the whole piece, just in a new way?

Or was it actually more of a small nibble out of a larger thing? Not to say those are different or bad — I’m just curious, from a user-experience perspective.

Ronald: About 25% of those tested on the Smart Story Suite chose the linear version. They went to the detailed—

Mason: Nice.

Ronald: —version and read it, because apparently they were interested, so they spent more time. So you have that option.

Mason: It’s really interesting. There’s a lot — especially with AI — I think we’re going to enter a moment where everyone is making everything interactive, and I think interactive on its own isn’t enough. It has to serve the content. It has to be the way the content is received.

The structuring has to be useful. So I think whatever research comes out of this specific structure, and whatever comes next, will be really useful both in the design of tools and in how we make content mean something again. You have media theorists, like Marshall McLuhan, who say the medium is the message.

So if the medium is this, what’s the message of that? Whereas with Twitter, the medium is the message is that you have a very confined text box, and therefore you lack a lot of context — you have a lot of bad behavior, maybe we’ll say. So I don’t know if there’s a question in there, but I’m curious if that sparks anything for you.

How do you think about the format serving the content, and where would that adjust?

Ronald: Okay, so we’re starting with today’s dominant behavior of younger people on their phones — that’s the starting point. And if you’ve observed them — and that’s why we’re here, right, we’re talking about attention span — I’m talking about structure and—

Mason: Yeah.

Ronald: —about content. So, with content that’s of interest to you — in educational psychology, this has been around for a long time — individual interest is something you’re invested in; you might have expertise, maybe you’re taking a class you need for your major, something you’re passionate about, and that’s your target audience. But we’re looking beyond the target audience, generating what educational psychologists call situational interest — how the content is presented. That’s where it becomes critical in a gen-ed class, where you’ve got all these different majors taking the class just because they need the credit — they have to check a box somewhere. So there’s a big difference between classrooms that teach things students want to know, because it’s their major, and things they may not want to know but have to know. So interest becomes part of that, and it has a lot to do with the content point you made.

Mason: Yeah, it’s really interesting. I think you could get really interesting motivation data out of something like this as well — where are people losing motivation to keep going? Assuming we’re able to restructure and recombine this in any way, that would be really interesting.

I want to do a little test run with you, and feel free to tell me if this falls flat — that’s totally fine. I want to show a screen, hold on. This is going to be dangerous, because I think my YouTube recommendations are going to show, and YouTube has a very sensitive algorithm. Okay.

So YouTube recently rolled out a new feature called “Ask YouTube.” At the top, you can now say “I want” something. So if I say, “I want to host an elegant wine-tasting party” — because why wouldn’t I? — it shows a readout with some kind of generated content, these immersive video distributions.

So, applying your framework to this structure: where is this going right, and where do you think it could improve, assuming I just want to learn how to host an elegant wine party?

Ronald: Well, if you come to this content with the motivation to learn something, that’s actually the video people spend the most time on — something they’re searching for. YouTube is the world’s largest search engine, believe it or not. In that case, it does the job, because you’re getting a specific answer to a specific question. On the other hand, what if I really don’t know what to ask, in the context of some new information in my class — I’m not yet even knowledgeable about it? I’m supposed to be consuming information, not asking questions, until I know something about it. Then, yes, go to YouTube and ask more questions about it. There’s a major news organization — I won’t name it — that has a feature called “Deeper Dive,” and underneath the headline is the exact same thing: you can ask questions. My problem with that is: how do I know what to ask? I haven’t even read the news story yet.

Mason: Yeah.

Ronald: It has a lot to do with your motivation, and whether or not you’re seeking something specific.

Mason: Gotcha. From a pure content-structure perspective, do you think it’s better to give someone a menu of options? In this case, we have about twenty visible video links, where you could choose one that matches your interest based on the title — shorts are kind of weird, but still. Or do you think, for something like this, a guided journey is actually better — a one-two-three-four-five step guide?

You can opt in wherever you think you are, but there’s also some benefit to progressing through that phased, step-by-step process.

Ronald: Yeah, when you get into the word “personalization,” it gets tricky, because you may have some knowledge, but at the same time, you might be personalized by an algorithm feeding you things you really don’t want to see, or weren’t even searching for. The level of personalization depends on the person, depends on your individual interest — and if you’re just looking for something interesting, that’s situational interest, and video, by definition, is one of the best mediums for generating situational interest.

Mason: I love it. Okay, so we’ve talked about the benefits, and we’ve talked about a few of the challenges, or things we’re still learning. I have one final question: in the next few years, how do you see the role of an educator changing because of technology like this?

Does it become curatorial in nature? Does it become more important which sources you pick, and does the way people engage with them matter less? Does this have implications for assessment as well? Multimodal intake is amazing, but multimodal contribution is incredible — if I can contribute a video rather than writing, maybe that serves me really well as a learner or an author.

So I’m curious how you think this role is changing, specifically.

Ronald: Well, even though you can’t tell, I’ve been teaching a long time, and anyone my age who was in the classroom fifteen or twenty years ago already knows the answer to your question. It’s constantly changing, and it has changed. The question is: have we changed? Because we’re going to talk about change.

I’ll also say that our brains, and the way we process information, and the limitation we talked about at the beginning of this podcast, haven’t changed — it’s hardwired. What has changed is the technology, the mobilization, and the amount of choices. So I think education should be looking even more closely — which is why I’m doing what I’m doing — at ways we can promote more engagement, and hope we can communicate at least a portion of information, as opposed to completely turning students off, where they end up ignoring it.

We have a big problem in journalism, where a lot of younger people are now ignoring news for several reasons. But we don’t want people ignoring a page of text — we want to make that text consumable. Even in video, we’re starting to dabble in that: you take a five-minute video, and what if you get a specific menu of specific things within it?

We know you can already select certain points in some videos on YouTube. But what if you got more information about that video? What if someone just wanted to see my AI tool, and immediately picked that little segment of your podcast — that would just show that? So I think that even if people bounce around and select different things, eventually, if they’re interested, they’ll select most or all of it, because they’re interested. So the key is generating interest — situational interest, in particular.

Mason: Absolutely. So if we’ve generated interest, where can people go to learn more about what you’re working on, and read more about your framework or the tool?

Ronald: Thank you. I have a LinkedIn page where I post three things every week — short chunks of information. If you really want the full story, go to digitalengagementlab.org, one word. That describes the model, along with some videos to explain it.

Just keep in mind that the model is cognitive, and the AI is adaptive. It’s not just AI, and it’s not just cognition — we’re trying to synthesize both.

Mason: That’s important, yeah. That’s the water we swim in these days — it’s never an either/or. Well, I know this podcast is going to come out as a long one, but we’ll do our best to publish it across formats.

Links

• Ronald Yaros on LinkedIn
• Medium Profile and HCIL Speaker Series YouTube Video
• Digital Engagement Lab
• The Digital Engagement Lab,