Campus Technology Insider Podcast October 2025
Listen: The State of AI in Ed Tech: Insights from D2L CEO John Baker
Rhea Kelly 00:00
Hello and welcome to the Campus Technology Insider podcast. I'm Rhea Kelly, editor in chief of Campus Technology, and your host. And I'm here with John Baker, CEO of D2L, to talk about the state of the ed tech industry and the role of AI in teaching and learning. Welcome, John.
John Baker 00:23
Thanks, Rhea. Looking forward to the conversation today.
Rhea Kelly 00:28
So I was watching your recent keynote address at the D2L Fusion conference, and I learned something about you: that you're learning to play the piano, and actually, that's something we have in common. I'm a pianist, so I just have to start with a little tangent, like, I'm so curious, are you learning like classical, jazz? What are you learning?
John Baker 00:47
The classics right now, and I'm only through my second book. I'm not quite an expert like yourself, but it's great to actually get back into the learning mode with something that I care deeply about, which is music and art. So it's been a fantastic journey so far, and I've got a great teacher.
Rhea Kelly 01:02
Wow, that's great, yeah. And you shared that anecdote as an example of how learning can spark joy, and that kind of framed your tone for the whole keynote. And then you went on to say that technology and AI also have a big role to play in how learning can spark joy. So how do you make that leap, because playing the piano, very human, very like core sort of emotional response, right? And then tech is, you know, that seems like the opposite.
John Baker 01:32
Yeah, I think we always look for meaning in the work that we do. And, you know, I've been building D2L now for 25 years. Like it's not just for the sake of putting in place technology. It really is designing the technology in a way that's going to make things for humans better and easier. If we can automate something, or we can make an experience better with technology, so that we can foster this human connection, that's the real aim. And so it's not about technology for technology sake. It's about putting in place these systems to really spark learning, spark connection, spark that human endeavor of learning.
Rhea Kelly 02:06
One of the things you said was that AI should be part of every learner's journey. So can you talk more about that?
John Baker 02:13
Well, yeah, I think if you think about learning today, a lot of the work that we're doing is introducing these AIs into the learning platform to really support both the faculty and the student. And so for the student, it's really about maybe virtual tutoring or getting feedback or study support or getting an idea of what path they could potentially take that would get them back on track for mastery of an outcome. It's really around connecting the dots. And so, you know, in our case, a lot of that started with making sure that we had the right tools for the faculty, so that faculty can really create these engaging learning moments for the students. And so one of the products that we launched was called Creator+, and it actually comes from the work that we did in Singapore to reimagine how learning occurs in these learning platforms. So instead of it being a bit more of a learning journey that's lonely, where you go from reading a page of content, to maybe watching a video, to having a discussion, to taking a quiz, and you're kind of on this independent journey through this system, and it feels kind of empty, it's how do we put that into a single page. So you're reading some content, you're watching a video, you're having an interactive flashcard exercise maybe, knowledge checks, practices, and then you're getting the voice of the educator back in terms of feedback. So when you go from one topic to the next, you're feeling confident that you can move forward, knowing that you've had these little formative assessments built in that give you that confidence that, hey, I've got that, now I can move to the next topic. But it's also about leveraging these AIs in a way that helps people get better connected. One of the common, I think, myths with personalizing learning or using this type of technology to adapt learning to individuals is that we're going to shift all of learning to an individualized pathway. And what we're trying to do is, no, how do we actually draw more meaning or more in connection using these technologies, so that students can better connect with other students in group work or collaboration, students can connect with the faculty member to get better feedback, better inspiration for what they're pursuing, or maybe connect to the big challenges that exist in the profession that they're pursuing, whether it's nursing or medicine or engineering. And these AIs can free up time. So if I can move forward with more efficiency through a combination of better design, better learning experiences, and maybe virtual tutors and other types of power tools with AI, then it could free up time so that we can do more than we would ever normally think of as possible with the education. So quite often students today, if you talk to them, they'll talk about how they have no time to do anything. And so, you know, if this technology can make it easier for students to get through with more efficiency, it enables them to really maybe start to build programs that synthesize data, or maybe we can put together some coding application for picker problem, so they can actually demonstrate how they can actually solve the problem, versus just understanding or remembering some definitions and then moving forward in terms of the next course. So I think we can elevate what education can actually bring to bear in terms of the quality of the educational experience, which enables us to graduate better nurses, better doctors, better engineers. And that's what I mean by like, bringing that joy, that inspiration, that leveraging that technology to really redefine what an educational experience can be.
Rhea Kelly 05:27
That's an interesting distinction between personalized and individualized. I never really thought about how individualized, in a way, is sort of isolating, and so using the personalization to sort of stimulate more collaboration and connection, that's kind of a new thought for me.
John Baker 05:45
Yeah, when most people say personalizing education, what they're really saying is individualizing it, and I think that's a lonely journey through the educational experience. And there's no reason why we shouldn't have some of that in learning, just like we should have some video and some content that's more written. But if we can help students get connected, so you know, one real simple example in our learning platform is you can @ mention somebody, and so if you're having a discussion, you can @ John Baker, and all of a sudden, now I'm alerted to someone discussing something that might be relevant for me to pay attention to. And so if we can help with this technology to build better connection, better feedback, better engagement, that's going to be transformative for a lot of students.
Rhea Kelly 06:29
It seems like a lot of ed tech companies have been in a rush to incorporate AI into their offerings. There's a lot of AI washing. So how is D2L maybe pacing the incorporation of AI while, you know, embracing innovation? What's your approach to that?
John Baker 06:48
Well, I think what's critical is making sure that you involve your clients in the design of the system. So we run over 400 design sessions a year with clients, many of which are centered around AI, as you can imagine, for the last two or three years. We've also been building our own AI technology for the last 15-plus years. So we've been at the forefront. We've made lots of mistakes. We've done things wrong in the past. And so the key for us in the last three years is really to one, back up and establish what are our core principles and foundation for building out AI responsibly, so making sure we're doing with security in mind, making sure we're dealing with data privacy in mind, making sure that we're taking into account the concerns that our clients have around risk, and making sure that those become the pillars and the foundation for how we build AI to support clients. So a good example would be making sure that humans are in the loop as part of that framework around responsible AI usage, so that as things get developed or built in the system, that a faculty member, for example, is reviewing it, or a student would as well, understand that this technology is being used. And then from that base-level foundation, what we've done with the design work is really focused on what matters the most. So you know, when I started D2L, it was, what's the most important problem I could solve that would have the biggest impact in the world? And that same question gets asked when we're applying AI. And when we looked at the use of AI in our platform, we decided to start with the instructors and the faculty first. I know the downstream impact is on the students, but making sure that faculty were comfortable using these technologies was critical, because much of the generative AI jumped over the enterprise adoption straight to consumer, aka students. And so by bringing faculty into comfortable use of AI and building confidence around that, we felt that was the best pathway for driving adoption. And so what did we start with with AI? We started with, how do we generate content or interactive learning experiences with AI in a much easier way? So, you know, using AI to take a, maybe a video, and turn it into a game or crossword puzzle or glossary or chapter it or automatically put in quizzes inside the video, is just one example of hundreds that we've done around the learning activity generation. Then you get into assessment generation. So you know, one of the big things around AI is it really changes how we want to assess students, and so we've made it easier to generate new assignments, new quiz questions, and anchoring that on the learning science and building it the way that faculty still review. But that automation is transformative, because you can create hundreds of questions very easily now using AI, and then you're editing versus having to create these all from scratch. And then you get into other workflows, if you will, for faculty, around linking it to learning outcomes. That's good with AI. You don't have to manually tag things anymore in the system or making sure that you're providing study support for students, so that you know if they answer a question wrong, they're getting instant feedback generated by AI. And then you get into those student workflows around tutoring or feedback or other types of activities. But you know, starting with that faculty-first mindset, I think, has been a reason why we've seen about 8,000% year-over-year adoption increase with our AI tools. And so it's not AI washing, it's really getting into every month, what's the new feature that we're going to roll out with AI, what workflow we're changing with AI, and anchoring that on really good, solid client input.
Rhea Kelly 10:18
That sounds like, well, faculty training, of course, super important. What do you recommend that institutions do around that when they're prioritizing their AI strategy? It seems like that, that training aspect should be somewhere near the top.
John Baker 10:32
Well, I think there's really five key swim lanes for institutions. One is identifying the risks and tackling that through policy change. So how do we want to set up the AI policy or frameworks for the university? Two it's, it's also around this research agenda. So there's a, there's an impact to the scholarship of teaching and learning with student technology. So how does this change assessment? How does this change, how do we want to tutor? How does this change how we want to learn? And so there's a need to pull together that research, or even do research in this particular area. That then informs curriculum. How do we teach students in this new AI era? How's this going to change computer science, engineering, marketing, nursing, medicine? And so we really need to redefine how we teach these students. That has then a ripple effect into, how do I then upskill the workforce that's out there, not just the students that are here today, but, you know, there's all these nurses and engineers that need new training opportunities. So that's a huge growth driver for a university to embrace AI in new ways. And then the fifth is always like, how do I make this part of my daily practice? So a lot of it's really focused on the business of the university, or the work that's being done by the university, but, but I think bringing into your own personal daily practice helps you understand the impact this could have with faculty and students.
Rhea Kelly 11:50
So you talked about some of D2L's principles around AI. How about future goals? Can you share any of like, what you're prioritizing or what goals you're setting for AI right now?
John Baker 12:02
So for us, it's really making sure that almost every workflow throughout the entire platform is AI-enabled. So there's a concept in technology around mobile first. You've probably heard that in the past. Now there's AI first. And I want to be clear on that it's not about putting AI or the technology first and foremost. It's really just a technology term, which means AI is enabling all the different key workflows within the system to be better automated. And so, you know, AI is now being used to create learning activities. It's now being used to create assignments. It's being used to create assessments, to link this all to learning outcomes, to link this to feedback or insights, to understand what's going on and what's working, to virtual tutoring, to feedback for students. Almost every workflow in our system is being touched with AI today, just to make it easier to use. And it really is a UX or design evolution. So you know, many years ago, we would compete on ease of use. We feel like, you know, with our now, our win rates more than 50% when we go after opportunities today, ease of use was the key thing that drove that increase in win rate. We think AI enabling these workflows, if you want to say, I want to create manually 10,000 questions to assess all my students, so they have big random question pools, doing that manually is a lot harder than having AI generate 10,000 questions for you, or even 100,000 questions for you that you then just review. And so we think this is the evolution of design, evolution of the user experience, and so we need to embrace it quickly in all aspects of what we do. Now, another part of this is integration of AI tools. And so instead of us just building everything ourselves, how do we work with clients to make sure that we prioritize the integration of tools that they also want? So if you look at D2L, we have over 1,800 tools that we integrate into the system, and we'll continue to do more of that with AI. But again, I keep reminding our team, it's all built on that foundation of building trust and security and data privacy. Doing this the right way is better than doing this just fast and furious. It's much better to take more measured approach in terms of doing this. And so far, our pace with clients has been a little bit ahead of most of our clients, not all of them, but a little bit ahead. So I feel we're hitting the mark right now in terms of the delivery on the AI promise.
Rhea Kelly 14:23
It's a big shift from, you know, ease of use being the selling, main selling point, to AI integration being the main selling point. What are you seeing industry-wide? Are, you know, are your competitors doing the same thing, do you think?
John Baker 14:38
Not, not really. So I think we've learned a few lessons over the years. We've seen a number of technology waves come. So AI is, I think, the latest, but previously it was cloud technology, and so moving all clients to the cloud was, it was a big driver for change. Previous to that was mobile. Obviously the internet was one of the first ones that we embraced. AI, I think, is going to be more, more impactful than all the previous ones, and I think largely because it gets us to a point where we can actually redefine what education can offer. Because now you've got these new tools that can enable a better learning experience. It can also drive down costs, so it could just simply be an efficiency dimension that you work on through these technologies. So for example, we can, using AI, we know that we can save about 30% of the course design time. We've seen that in study after study now with our clients that have leveraged our tools to support the building of courses. And so it could just be an efficiency strategy, which is very compelling for making a shift into a better learning platform. But the other dimension is around improving the student experience in terms of, you know, it's not just about remembering and understanding or getting through the basics of this course, because you just don't have the time to cover everything you'd want to as deeply as you'd want to. Now, if you can free up time, because you're using AI, you can get to those higher levels where you're actually really diving deep into problem-solving, or really trying to actually come up with solutions to big industry challenges as part of that same offering. And so we can actually graduate students at a higher level of mastery than we would have been able to do before. So there's a real transformational aspect of this technology. But yet, Rhea, we've not actually seen it show up yet in RFPs, which is stunning to me. You know, I think we will, probably, in the year ahead, see this become a bigger factor for making a shift in learning platforms. And we're not seeing the same level of investment that we're putting into AI enablement with our competitors. You know, as you know, Blackboard is going through a bankruptcy, so there's certainly challenge to put in place the R&D investment, and we've not seen a similar level of investment on, into the core workflows with our other competitors. You know, and it's because it's, it takes a lot of effort and energy and many years of dedication to this, and we're very committed to making sure that we're helping our clients through this big transformation.
Rhea Kelly 16:56
I've talked to other companies like, you know, the sort of the counter argument would be exercising caution, making sure that these are tools that the constituents actually want. So how do you sort of respond to that?
John Baker 17:13
Well, I have no issue with a caution. I think the first swim lane is always about risk mitigation. And so the way that we tackle that is through our foundational framework for how we actually build these technologies, making sure that responsible use of AI is at the first and foremost, security, data privacy, all critical. Which is why we actually built these technologies into a ring-fenced environment, using the client's data, leveraging these big models, but yet making sure that none of the data is going out to a public cloud. These are really important aspects of how we build the technology and mitigate those risks. I think that there's, you know, there's still risks with, for example, MCPs, a way to integrate other AIs, or let other AIs use your system to extract data, to extract information, to support that broader artificial intelligence mission. There's risk still there, and so we've not gone down that approach yet. We may, as things become more secure. So I'm not saying that we're doing everything AI. I'm saying we're trying to take the measured approach to do this the right way. But what you don't want to be in this industry is slow. You know, I think we lost some ground when we didn't make the shift to cloud as fast as we should have. And so we think that making sure that our clients have this AI, AI enablement will be a compelling reason why you'd want to shift from Canvas, from Blackboard, from Moodle, from other systems to Brightspace, to get this benefit, both in productivity, but also to get a better student experience. And so we definitely wanted to move swiftly to capture that opportunity.
Rhea Kelly 18:47
So you mentioned, you know, how you're not quite seeing AI factor in the RFPs quite yet. So I wanted to ask, you know, what should higher ed institutions be putting on their RFP, like, what should they expect from their, their ed tech providers in this new age of AI?
John Baker 19:05
Well, I think they want to have a system that leverages AI to support the key workflows that they're supporting their faculty with. So if, for example, an institution is writing an RFP today for a learning platform, at least for a modern learning platform, in the past, it would have been like cloud enablement, mobile enablement. Now it should be around AI enablement. So how are you leveraging AI in your learning platform to support everything from content creation to quiz to assessment to feedback to the core features of a learning platform? And I think it should be a big factor. The other way to think about it is, it could also just be a way to contribute to the ease of use of these learning platforms. So if you've got a tool that, you know, for example, if you're looking at a feature bake-off or a comparison, hey, you've got a quizzing tool with AI, quizzing tool without AI, well, this one's clearly much easier to use because it enables me to, to achieve the outcome of creating a whole bunch of quiz, quizzes that are much more reliable, much faster. And it could be that ease-of-use rating without actually having to change the RFP itself. It could just be how you evaluate, using a rubric, is this an AI-enabled tool or not?
Rhea Kelly 20:18
Are there any questions you wish institutions would, would ask when they're evaluating D2L?
John Baker 20:25
I think the big effort that we're trying to do is really two fronts. One, how does this technology help improve learning outcomes? So are we going to see better retention, better student engagement, better productivity, better growth, because we're able to do things to open up new markets, like workforce upskilling as an example. So thinking about these learning platforms not just as a way to support the on-campus learning, but to support all modalities of learning on campus, online staff, professional development, workforce upskilling, versus it just being sort of more of a siloed approach. That's probably the first and foremost. And then second, you know, are we getting a, are we getting a partner here? When we typically buy these technologies, it's really around, are we supporting the clients for today, or are we wanting to sign up a partner for the next five to 10 years and really understanding what the roadmap is, what the trajectory of that roadmap has been? Have they really been an innovator in this space? Are they delivering on their promises? What's the client experience going to be like? What's the support going to be like? All of these are critical in terms of making sure you got the right partner, not just for today, but for long into the future. And then third is around the innovation. You know, I really think learning innovation is critical, built on really good learning science. So are we able to do things like competency-based learning? Are we able to do mastery-based models of learning, which enable us to shift education from just measuring how much time you spent in a seat and did you pass or fail the exam, to it being much more driven by outcome, where if students can demonstrate mastery, they progress, and so at that point, you're able to confidently feel that this, we've graduated students that are really exceptional engineers or really exceptional nurses or doctors that really understand what they've got to tackle as they get out into the workforce. Building of that whole big knowledge graph, if you will, that they're going to need to tackle the problems of the future. And so I think we can think about these technologies much more strategically than we did in the past, where it was really just a website management tool or a spot to put up your syllabus. These are much more strategic now for the university or for the college, and I hope we see more of that type of engagement with clients in the future.
Rhea Kelly 22:44
I like that. Are you getting a partner and are you getting an innovator?
John Baker 22:48
Yeah, today, especially as you go through change and disruption, because every industry is going to go through transformation with AI, just like every industry went through transformation with cloud or mobile This is, I think, bigger, and so having the right partner to support the next five years, I don't think has mattered more.
Rhea Kelly 23:07
Well that is a great place to leave it. Thank you so much for coming on.
John Baker 23:11
Thanks Rhea, thanks for all the work that you do. And look forward to talking again.
Rhea Kelly 23:19
Thank you for joining us. I'm Rhea Kelly, and this was the Campus Technology Insider podcast. You can find us on the major podcast platforms or visit us online at campustechnology.com/podcast. Let us know what you think of this episode and what you'd like to hear in the future. Until next time.