Episode Transcript
[00:00:00] Tawnya Means: We know from the research that one to one instruction, or even small
group instruction is the most effective. The tutoring model, the mentoring model, the studio
model. But if we did that, we would be so elite, exclusive, we would be focused on only the few
who could get into that kind of environment.
And so we've said we want to empower as many people as possible to learn. And when we do
that, it requires scaling in ways that remove that effectiveness. So group instruction just isn't as
effective.
So when we think about kind of, I call it the conveyor belt of educational system model.
[00:00:45] Jeff Dillon: Welcome to another episode of the EdTechConnect podcast.
Today's guest is Tanya Means, founding partner and principal at Inspire Higher Ed consultancy
dedicated to helping colleges and universities innovate, grow and thrive in the evolving
landscape of higher education.
With more than two decades of experience guiding institutions through digital transformation,
Tanya has worked closely with educational leaders and administrators to integrate technology
into teaching and learning. Always mindful of preserving the human connection and at the heart
of education.
Under her leadership, Inspire Higher Ed aims to bring thoughtful, accessible and impactful
solutions to institutions of all sizes, helping them adapt to new technologies, reimagine
pedagogy, and expand access for learners.
Through her deep expertise and passion for educational equity and innovation, Tanya has
become a respected voice in higher ed consulting. I'm excited to explore with her how
institutions can navigate change, embrace opportunity, and build a future where learning is more
engaging, inclusive and scalable.
Welcome to the show, Tanya. It is great to have you today.
[00:02:04] Tawnya Means: Thanks for having me, Jeff.
[00:02:05] Jeff Dillon: Before we jump in, I want to say how much I've been looking forward to
this conversation.
Your work really sits, I think, at the intersection of where I spend my time, where technology and
teaching and real student needs collide. Your experience helping institutions really rethink digital
learning, removing friction and modernizing at scale really hits the same themes I hear from
campuses every week. So I'm excited to compare notes and dig into how you see this moment
in higher ed. So start off. Tell me what inspired you to launch Inspire Higher Ed?
[00:02:40] Tawnya Means: Well, first of all, thanks, Jeff, for having me. I'm really excited about this
conversation and looking forward to what we're going to talk about.
My work with Inspire has really come naturally out of the progression of my career. You know,
my background is in educational technology, my master's degree there and in network learning
systems that many years ago, and then my PhD is in information science and learning
technologies focused on learning systems design and development. And so I've really been
heavily involved all the way from my educational background up until my work that I've done for
the last two decades is, is around educational technology and specifically about how we can use
technology to improve and enhance teaching and learning.
And a lot of that work was around online and blended education prior to the launch of ChatGPT
three years ago. And just over the last few years has really come clear that we're experiencing a
fundamental shift in how education is able to be adopted and offered.
But there's also this great concern and hesitancy and kind of like murkiness around, like, how do
we actually do this? Right?
And so the launch of Inspire Higher Ed was really designed to take that knowledge that I have
and the background that I have and the exposure that I have to lots of different institutions and
how they operate and help them not only to understand kind of the vendor promises and the
institutional bureaucracy and reality that we experience and kind of bridge between those and
help to recognize ways in which education is the focus rather than technology.
Technology is a supporting role.
The solutions, so to speak, that come out of that need to be implemented with an understanding
of how learning works and not just as a tool that gets kind of passed into the system and then
who knows what happens with it after that. And so just because education has been a passion of
mine and it's been something that it's so empowered by technologies that I wanted to be able to
be there at the forefront to help people leverage these new technologies in ways that really
enhance learning.
[00:04:57] Jeff Dillon: One thing that really stands out about your career, I think, is just how long
you've been working at this crossroads of higher ed and tech. You've seen the early LMS days,
the rise of online learning, the shift to mobile, and now this. I think the campuses feel this
pressure with AI. We're way over here, they want to be over here. But it's a real scary kind of
transition. And that perspective, I think is rare. It gives a lot of weight to, I think, the work you're
doing now. You've got decades of experience in higher ed and educational technology. How has
that background shaped your, your vision for Inspire?
[00:05:34] Tawnya Means: Well, so what's always been important to me is the teaching first.
The technology is a tool that sequence matters between looking at the teaching first and then
finding tools that match.
I've worked with lots of different institutions, either as a full time role or as a consultant, and
everything from community colleges to big research institutions where the focus is different
depending on, on the institutional context you're in. And I've really learned that efforts at
Transformation will fail if they're done at people rather than with people.
And so for me, the conversations that are always most empowering to everyone is when we're
focused on what are we trying to accomplish, what's important, the value that we bring through
education.
And then how can we leverage tools that will help to support that vision?
[00:06:31] Jeff Dillon: I've looked through some of your work and something really jumps out to
me.
People use the word innovation constantly, but you actually work with institutions where it has to
show up in real decisions, real classrooms, real budget constraints. You see what campuses are
trying to push forward and what's holding them back.
And it gives you this practical view of what progress actually looks like right now. So when you
talk about innovation in higher education, what does that look like in practice today, especially for
institutions grappling with digital transformation?
[00:07:07] Tawnya Means: One of the things that I think our educational system has kind of, it's
always kind of been this way and has become more so as we've found ways to scale up
education.
There's kind of this competing value here, right? We want to provide people with education, we
want to provide as many people as possible with that education, but we have limited capacity to
be able to do so. So we know from Bloom's two sigma problems, one that I talk about quite
frequently, we know from the research that one to one instruction, or even small group
instruction is the most effective. The tutoring model, the mentoring model, the studio model. But
if we did that, we would be so elite, exclusive, you know, we would be focused on only the few
who could get into that kind of environment.
And so we've said we want to empower as many people as possible to learn. And when we do
that, it requires scaling in ways that remove that effectiveness. So group instruction just isn't as
effective.
So when we think about kind of, I call it the conveyor belt of educational system model, we
basically say that we have to bring people in at a certain point, we have to progress them at a
certain point. We have to give them the certain things, you know, the scalable things that we
can, that we can do. Well, I think that if we can move back to that creative model without
reducing the accessibility of the learning both in terms of, know, accommodations that people
need for differences in capabilities, but also your background, your experience, your interests,
your passions, your, all of those things make it so that we can have a studio based model if we
can leverage technology appropriately. So the innovation when we think about now is not about
adopting new tools. It's not necessarily about, you know, what kinds of Processes and tools do
we bring into the system? But what kinds of learning experiences are now available at scale, and
how can we empower those so that it's not just, oh, we're going to automate feedback, or we're
going to automate grading, or we're going to check everything that everyone does in some kind
of a mechanism way. But it's about how we can take your individual, personalized background,
experiences, interests, ideas, and use them so that students have a thought partner, have a
mentor, have a guide that can help them through the parts that it makes sense for the
technology to do. But they also have access to the human piece that makes empathy, judgment,
wisdom, relationships a part of things that we couldn't do in the past. And so it's kind of like, how
can we bring those two together?
[00:09:57] Jeff Dillon: I love that. I think too often higher ed is looking at transformation is like,
for example, moving forms to a digital process, like just transferring it to digital.
It's not just moving things to digital. There's just a bigger scope we need to look at. And of
course, none of this really happens in a vacuum. Every institution you and I talk to wants to
modernize how learning happens. But they often are navigating this maze of legacy systems and
competing priorities and very real resource limits. You've had a front row seat to what actually
slows progress down and what keeps leaders up at night. What do you see as the biggest
challenges colleges and universities face right now in trying to modernize their approach to
learning?
[00:10:45] Tawnya Means: I think that there's some kind of rote answers that people often give. Oh,
it's the institution. Oh, it's the bureaucracy, it's this. But I really think that there's some real
reasons that institutions are challenged. One of them is, especially lately, change fatigue. I
mean, the idea that we're asking faculty to, especially if we just think just since the pandemic, I
mean, it was happening before, but not at the pace, you know, we had the pandemic. We had
everybody having to do remote teaching online.
We've had LMS changes for years. This one's better than that one, and let's switch to that one.
And. And now we have AI that in and of itself just AI. I mean, we've got 75 years of history of
artificial intelligence and machine learning. That's not surprising and new, but the fact that
everyone has it in their pocket now, that's the part that's new. And the fact that it changes almost
on a weekly or sometimes even daily basis, if you look at all the different models and their
capabilities and what they're being able to do.
So being able to keep up with changes is nearly. Well, I'll say it is impossible. I don't think it's
even nearly impossible. I think it's impossible. No one can keep up with all of the changes for
everything. And that's kind of what I love about what you're doing, is you're crowdsourcing all of
this information about technology to be able to bring lots of people together because lots of
people's brains work better than just one or two. And so that change fatigue is not only
challenging just because we get tired of trying to keep up where we feel challenged by our. I just
can't keep up. But the trust in the system is depleted because it used to be that we were like,
okay, if I'm going to move from this LMS to that ms, that's the last move, right?
You know, it's like, sure. And then, oh, maybe we need to change again. So that trust that I'm
going to do a big burst of energy to be able to make this change, and then I'm going to be able
to.
To continue my life this way. And it's like, no, that. That's not ever going to be part of our world
anymore. So that's. That's hard change fatigue.
I also think that the system itself is designed in such a way that there are misaligned incentives.
So what that means is we as institutions say, you know, we want you to be innovative, we want
you to value your students. Their students are the reason why we do everything we do.
But then the reward system doesn't say that. The reward system says, your tenure and
promotion is reliant upon your research. Well, but you want me to do this and that. And so then
when we bring in technology, we're not only saying to faculty, hey, you got your PhD in this
subject matter area. You're an expert. You're really well developed, deeply in this one piece of
subject matter. But we also want you to do this, this, this, this, this. And we start listing all of
these things. And then we say on top of that, you need to be experts in technology. It's like the
incentives aren't aligned for that kind of system. And then the other thing that I think happens is
that we've kind of got this shiny object problem, right?
I actually heard somebody say, hey, Twitter's really cool. Can you help me figure out how to use
it? It's like, well, no, wait a minute.
Twitter is an interesting thing, but that's not why we do what we do. So can we look at the
pedagogy? Can we look at what we're trying to accomplish? Hey, if you're trying to get your
students to think about your lecture content outside of class and you want to have them use X or
Twitter or some other kind of tool to be able to notify or tag something that they've seen in the
world that relates back to what you're talking about in class, that's great because that's a
pedagogical reason, not because it's a tool.
And so I think if we can start to evaluate and bring together a shared language for what we
mean by good teachers teaching how we evaluate technology and how it aligns to that, and then
help people to feel like there's a manageable way to keep up, then I think we overcome some of
those challenges.
[00:14:43] Jeff Dillon: There's a lot of things in there. Earlier on in that response, there was
something that made me think more about. I think we need to look at things as a process and
not a project. Most of the time, like it's too much that's forgotten. And one thing I appreciate
about your work is that you don't only focus on the well resourced giants like you spend a lot of
time with regional publics, community colleges, smaller privates trying to do big things with
modest budgets.
And they want modern learning experiences, but they can't afford to lose the personal element
that really defines who they are. How do smaller institutions or those with limited resources still
benefit from edtech innovations without losing that human touch?
[00:15:29] Tawnya Means: So I think smaller institutions actually have an advantage.
And while they don't maybe have as many dollars or maybe as many people that can focus on
the innovation itself, they have closer student relationships, so they're more able to interact one
on one with individual students.
They also can be more nimble in some ways to make decisions without feeling like they're
turning the entire Titanic in order to be able to make a change.
So piloting something or even adopting something at an institutional level is sometimes easier
because they can be a little bit more nimble. Now I said, can they? Don't always. Because I think
sometimes they also get bogged down in the bureaucracy of making decisions and wanting to
bring together the really large committee that has everybody's voice. And that's not necessarily a
bad thing. There are ways to be able to do that. But to be able to make changes institutionally, I
think sometimes those smaller institutions can do more. If I were to give a little bit of practical
advice or some tips for that is to try to pick one high impact problem to focus on and pilot it and
not try to just change the whole institution, do a campus wide rollout of something, but instead
try and say, well, let's try this in one focused area, let's see how it works and then let's move it
out. And then, you know, smaller institutions often have more visible champions.
So because the faculty are sometimes smaller and have more cross disciplinary relationships,
they can be more visible as a champion. So they can say, you know, I tried this in my class and
it really works. Would you like to try it too? As opposed to feeling like it's a mandate that's
coming down from the top. And then I think they also have a little bit more flexibility because of
technologies that are either free or low cost, that if they have good professional development
and people who are trying to help them to spread the adoption, they can actually move forward
with those tools a little bit easier than some of the really large institutions that require a lot more
guardrails and implementation processes.
[00:17:46] Jeff Dillon: You've probably done a lot of thinking where learning is going next. And
with AI maturing so fast and online learning evolving beyond the old models, campuses are
really trying to sort out what these tools actually mean for teaching support the student journey
as a whole. Your perspective here feels really valuable because you've seen multiple waves of
edtech come and go. You mentioned interest in AI online learning. How do you see emerging
technologies like AI influencing the future of higher ed pedagogy and student experience?
[00:18:20] Tawnya Means: So one of the things I write about and talk about quite a bit is the Human
plus AI partnership, the collaboration between the two. And I had often seen it human dash, AI
like it's joined together. It's kind of implied, but I really like the Human plus because it's very
explicit. It's saying these two go together. It's a partnership, it's a collaboration. And so the goal
as we think about AI is not to think of it as a replacement for a human, but as a partner. Whether
it's a thought partner, whether it's a cognitive capability that you're enhancing or expanding, it's
not necessarily about being more productive or more efficient, but as expanding what you could
do yourself. And so when we think about higher ed pedagogy, what I think we need to be really
leaning into is how do we help students and faculty, but especially students, how do we help
them to realize how to learn with AI, not just about AI, or figure out how to use it or what kinds of
things can I have it do instead of me? But how do I, as an individual student, how do I lean on
these tools in a way that doesn't cripple me for the future, doesn't reduce my learning, but
enhances it?
And so that could be things like, maybe I was sitting in lecture class and there was something
the instructor talked about that I didn't quite understand.
I can go to an AI tool and I can say, help me better understand this concept. I'm not asking it to
write an essay for me or solve my homework, but I'm asking it to help me understand. And then
once I understand, then I am better prepared to be able to do the work myself.
In a similar way, it's something like if I am working on my homework and there's some physics
concept that I don't really understand completely, and it's asking me, in a homework problem, to
do something that I don't really know how to do. The easy way out would be to just take a
screenshot of that homework problem, give it to ChatGPT, and say, answer this question. But
then I'm crippling myself for the future, right? Because I don't know the piece that I didn't know
still. And I also just got an answer that I don't know if it's right or wrong because I have no real
way of verifying it. But instead, if I say, I, I'm being asked to do this thing, I don't understand it.
Don't give me the answer. Just help me understand the process.
Now I'm getting a tutor, a mentor, and further instruction, and I'm able to work through that. And
then when I think I understand it and I solve the problem, then I say, okay, give me three more
questions like that. The teacher didn't give me three more problems. I asked for it because I
really want to know if I understand it. And so if we can help students to understand the value to
their future of doing that kind of process, then we're really going to enhance their learning. And
the pedagogical environment in which they're operating in becomes a support to them as
opposed to just helping them check the box to get a degree to get the job.
[00:21:29] Jeff Dillon: I love your philosophy about keeping a human. I call it keeping a human in
the loop. Some of the most powerful AI solutions I've seen out there recently are, are like, let's
say, a grading tool. There's a lot of grading tools out there that are using AI, but really the faculty
member Needs that control. They might give you the head start, but they're clicking the buttons.
Search tools now, you know, you could hand all that off to AI, but even the search tools, the best
ones, are giving control to administrators at campuses to say, hey, I want to connect these dots.
This acronym should go over here.
Those tend to be the best. But I like your perspective on that. I noticed that a lot of your
messaging points to helping institutions innovate, grow and thrive. Those are big promises, but
they only matter when they show up in real outcomes on real campuses. So I'd love to give
listeners a sense of what does that look like in practice. Can you share a real world example of
where Inspire helped an institution achieve those goals?
[00:22:29] Tawnya Means: Of course, yeah. So one of the things that I've developed is what I call a
three tier framework for education for AI in education. And it's basically looking at what we have
expectations for students to do. We also need to have an alignment with what we expect faculty
to do so quickly, just running through what that looks like. If we want students to have AI literacy,
we need faculty who have an awareness of AI. They understand what it is and how it works, and
they talk about it to their students on a regular basis. If we want students to have competencies
in AI, we need faculty that have integrated AI into their teaching practices. There's a variety of
different ways in which that can happen, but they're giving the students opportunities to interact
with and develop competencies using those tools. And then if we want students to have
expertise in AI, to be able to build things or to do things that they'll experience in the real world
with AI, then we need faculty who are willing to rethink what they do with their teaching and
innovate in really interesting ways. And so if you take that framework and then develop faculty
professional development around that, then it gives something for people to latch pieces onto.
Right. So it's not just saying, I'm going to come in and tell you what AI is and how it works, and
I'm going to present to you this information and then you're going to be able to just go forward
and do.
Instead, it says, okay, let's first get you up to speed what it is and how to talk to your students
about it, how to use it in your, in your teaching, how to have these conversations. Now let's help
you to think about ways that you can increase efficiency or reduce workload, but also empower
students to be able to try things. And now, once you're at that place, now we can really start to
reimagine. Instead of doing a quiz or an essay, let's imagine a scenario where your students can
have a conversation with a bot that actually walks them through a process, and you can collect
all of the same assessment information that you would have done in an essay or quiz.
But it's a meaningful conversation that you can then use the insights from to better what you do
in the classroom and to increase the activities that you do with your students.
And so taking something like a framework and then using it as part of the reasoning for, and the
method of delivery for professional development then gives the faculty something that on the
outside, it's not just how many people went to this workshop, but it's how many people went to
this workshop and six months later have realized meaningful learning growth in their courses.
And so you can look further out to be able to say what actually is an outcome of this. How does
this impact the teaching and learning experience?
[00:25:14] Jeff Dillon: With the pace of technology's evolution right now, I think a lot of
campuses are feeling pressure around accessibility, equity, making sure every learner can
participate. And those aren't buzzwords for most institutions. They really shape decisions,
funding, and the student experience and in practical ways.
So with the growing attention on accessibility, even the mandates, equity, inclusion, and
education, how does inspire higher ed incorporate those values into consulting and solutions?
[00:25:48] Tawnya Means: So I think of accessibility not as a compliance burden. Right. A lot of
people look at it that way, but I think it's a design philosophy. It's how can you. And it goes back
to beginning of our conversations when I said access is so important, accessibility is so
important, access to learning.
If you are designing learning such that it's going to be accessible to as many learners as
possible, then you are empowering and expanding learning for everyone. You're not eliminating
anyone from being able to get access to that learning. And so while these deadlines that are
coming up are conversations we should have been having for years, I mean, this is not new that
there's accessibility requirements. They've been in place for a very long time. They've gotten
more and more stringent, and they've gotten more advanced as technology advances and as we
see need for continued ability to offer educational content, digital content, in ways that more
people can get access to from a compliance standpoint. But it's really about how do we make
this conversation about accessibility be part of the innovation process.
And so if we bake it into the process, we bake it into the technologies, then it doesn't have to be
retrofitted. It doesn't have to be kind of cobbled together at a later date. It's much, much more
accessible from the beginning.
[00:27:13] Jeff Dillon: Something I always found interesting when talking with people who work
across many campuses, how they define a win. Because success in higher ed isn't always a
clean metric. Sometimes it's a culture shift, sometimes it's a smoother process.
Sometimes it's clear direction from a team that feels stuck. You've seen enough institutions up
close to know what real progress looks like. How do you measure success or impact when you
work with a college? And what metrics or signals matter the most to you.
[00:27:45] Tawnya Means: So there are three that I think are good places to start. One I just
mentioned, this is sustainability. Six months down the road, is anybody still doing it? You know, is
it still having an effect? The second one that I would talk about is engagement. And I think that
we often use engagement from the student perspective, like, are students engaging in the
content and learning and that kind of thing.
But I think engagement goes both ways. It goes from the faculty to the students, from the
students to the faculty, and from the students to each other. And so are they engaged? Are they
thinking about learning differently? Are they actively working, wanting to and enjoying the
learning process? And shouldn't be a chore to learn, right? It should be something we like doing.
And then I think the biggest one, if I were to just say, what's an umbrella term that we could use
is culture? Is the culture changed? We can look at the culture when we start. We can look at the
culture 3, 6, 9, 12 months down the road and say, what's happening in the culture? Do we still
have fear, uncertainty, and doubt, or do we have people starting to open their minds? Do we
have a culture that gives people a safe space to fail and learn from their failures? Do we have
the willingness for people to talk to each other?
Do we see more cross subject and cross discipline and cross college conversations happening?
Do we see people who are helping each other, who are?
I like, again, your cross crowdsourcing idea. Are they. Do they recognize the value from being
able to be involved in those conversations? And so I think those are the metrics that we at least
start with. There's probably some others and more refinement that we can do within each one of
them. But if we start there, that's. That's a meaningful way to see change.
[00:29:26] Jeff Dillon: Well, as we wrap up, I want to zoom back out and we've talked about
technology, teaching strategy, the realities institutions are navigating right now.
But these conversations always come back to the people who make higher ed what it is, the
faculty shaping learning, administrators that are steering the change, and the students counting
on us to get it right. So let me, let me end with this. If you could leave one lasting message for
listeners, faculty, administrators, or even prospective students about the future of higher
education, what would it be?
[00:29:59] Tawnya Means: I think we're going to continue to see change. That's just going to be a
given.
But I think change is not necessarily a bad thing.
You know, education itself, it changed my life, changed the entire trajectory of my life and my
children's lives and everyone who comes after me. And I know that it has the power to change
everyone who's involved in it. And so it's very important that we protect the opportunity for
people to get education and to learn and grow and expand what they do.
And I think educational institutions have a very special place to serve in that. I mean, anyone
can learn anything from YouTube. That's just the way the world is now. But there's also a great
amount of value that comes from an educational institution offering learners a community and
learning from each other and learning from experts and mentors and, you know, life changing
experiences around education. And so I hope that what we do over the next five to 10 years as
we see things change is that we pull into that, that we further the relationship building, that we
turn to things that make us more human as educational technologies and artificial intelligence
and all that, as they kind of shape what's happening in the world that we use our relationships
as. How do we improve who we are as people? How do we improve society? How do we
improve the people around us? How do we focus on character and wisdom and all of those
things that really make us human, that this becomes the bastion of that, the place for that being
projected.
[00:31:47] Jeff Dillon: All right. And for everyone listening, if Tanya's perspective resonated with
you, I'd encourage you to take a look at the work she's doing. Inspire higher ed.
Whether you're tackling a digital transformation, rethinking learning, or just trying to to chart a
smarter path ahead, she's someone worth having in your corner. Thank you, Tanya. It was great
having on the show. I'll put your links in the show notes to Inspires and your LinkedIn.
[00:32:11] Tawnya Means: Thanks so much, Jeff. Appreciate the conversation.
[00:32:15] Jeff Dillon: As we wrap up this episode. Remember, EdTech Connect is your trust
trusted companion on your journey to enhance education through technology.
Whether you're looking to spark student engagement, refine edtech implementation strategies,
or stay ahead of the curve in emerging technologies, EdTech Connect brings you the insights
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